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MERIS
Optical
Measurement
Protocols
Doc
Name
Issue
Date
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: August 2011
PAGE : i
MERIS Optical Measurement Protocols.
Part A:
In-situ water reflectance measurements
All rights reserved, ARGANS Ltd
2011
MERIS
Optical
Measurement
Protocols
Doc. no:
Doc
Name
Issue
Date
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: August 2011
PAGE : ii
CO-SCI-ARG-TN-0008
Issue:
2.0
Revision:
1.0
Date:
July 2011
Document Signatures
Name
Function
Company
Signature
Date
Editor
Kathryn
Barker
Project Manager
ARGANS
July 2011
Verification
Jean-Paul
Huot
MVT Coordinator
ESA
July 2011
Approval
Philippe
Goryl
Contract Manager,
ESA
ESA
Updates
Issue
Date
Description
1.0
June 2010
Issue 1 Available online on MERMAID website:
http://hermes.acri.fr/mermaid
July 2010
Minor updates: redistributed to QWG and MVT
July 2011
Updates relating to MERMAID evolution (links with ODESA and new
web interface) and new matchup sites.
2.0
This is a public document, available for download on the MERMAID website:
http://hermes.acri.fr/mermaid/dataproto
All rights reserved, ARGANS Ltd
2011
MERIS
Optical
Measurement
Protocols
Doc
Name
Issue
Date
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: August 2011
PAGE : iii
Acknowledgement
To ACRI-ST (C. Mazeran; C. Lerebourg) and ESA (J-P. Huot) under whose contracts the production and
maintenance of this document falls, and from whom substantial input has been received. ESA Contract
numbers: 21091/07/I-OL and 21652/08/I-OL respectively.
To all MERIS Validation Team members for their interest in MERMAID and their feedback on the
database and the Protocols document, and to the MERIS QWG who have contributed to the MERIS Third
Reprocessing and provided inputs to this document where appropriate.
Protocol contributors
NAME
AFFILIATION
S. AHMED
City College of New York, USA
D. ANTOINE
LOV, France
V. BRANDO
CSIRO, Australia
P-Y. DESCHAMPS
LOA, France
R. DOERFFER
HZG, Germany
B. GIBSON
Coastal Studies Institute, LSU, USA
B. HOLBEN
NASA GSFC
A. HOMMERSOM
Water Insight, Netherlands.
J. ICELY
University of Algarve
M. KAHRU
University of California, USA
S. KRATZER
University of Stockholm, Sweden
H. LOISEL; C. JAMET
Universite du Littoral Cote d'Opale, France
D. MCKEE
University of Strathclyde, UK
K. VOSS; M. ONDRUSEK
NOAA
K. RUDDICK
MUMM, Belgium
D. SIEGEL; S. MARITORENA
University of California, Santa Barbara, USA
K. SORENSEN
NIVA
J. WERDELL (on behalf of NOMAD contributors)
NASA/GSFC
G. ZIBORDI
JRC, Italy
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2011
MERIS
Optical
Measurement
Protocols
Doc
Name
Issue
Date
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: August 2011
PAGE : iv
Table of Contents
1.
2.
3.
Introduction .......................................................................................................................................... 1
1.1
Document purpose and scope ....................................................................................................... 1
1.2
Applicable documents ................................................................................................................... 2
1.3
MERIS L2 water products overview ............................................................................................ 3
1.4
General radiometry and water colour............................................................................................ 5
1.5
Requirements and recommendations for the validation of MERIS w ......................................... 8
The „MERIS MAtchup In-situ Database‟ (MERMAID).................................................................... 13
2.1
Introduction ................................................................................................................................. 13
2.2
Atmospheric parameters in MERMAID ..................................................................................... 18
2.3
MERMAID uncertainties ............................................................................................................ 18
2.4
ρw spectral correction .................................................................................................................. 18
2.5
Measurement and Processing flags ............................................................................................. 20
2.6
Data Access and Policy ............................................................................................................... 22
MERMAID PROTOCOLS I: SeaPRISM (AERONET-Ocean Color) .............................................. 24
3.1
Introduction ................................................................................................................................. 24
3.2
The Aqua Alta Oceanographic Tower (AAOT). PI: Giuseppe Zibordi ...................................... 28
3.3
Abu Al-Bukhoosh. PI: Giuseppe Zibordi ................................................................................... 29
3.4
CERES Ocean Validation Experiment (COVE_SeaPRISM). PI: B. Holben ............................. 29
3.5
Gloria. PI: G. Zibordi .................................................................................................................. 30
3.6
Gustav-Dahlen Tower. PI: Giuseppe Zibordi ............................................................................. 30
3.7
Helsinki Lighthouse. PI: Giuseppe Zibordi ................................................................................ 30
3.8
Long Island Sound Coastal Observatory (LISCO). PI: S. Ahmed, A. Gilerson ......................... 31
3.9
Lucinda Jetty Coastal Observatory (LJCO). PI: V. Brando ........................................................ 32
3.10
Martha‟s Vineyard Coastal Observatory (MVCO). PI: H. Feng................................................. 33
3.11
Pålgrunden Lighthouse, Lake Vänern. PI: Susanne Kratzer ....................................................... 33
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2011
MERIS
Optical
Measurement
Protocols
Doc
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Date
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: August 2011
PAGE : v
3.12
WAVE_CIS_Site_CSI_6. PI: B. Gibson, A. Weidermann ......................................................... 34
3.13
AERONET-OC Key References................................................................................................. 34
4.
MERMAID PROTOCOLS II: Portable Radiometers ........................................................................ 36
4.1
5.
SIMBADA. PI: Pierre-Yves Deschamps. ................................................................................... 36
MERMAID PROTOCOLS III: TACCS ............................................................................................ 42
5.1
North West Baltic Sea. PI: Susanne Kratzer ............................................................................... 42
5.2
Sagres, Algarve. PI: John Icely ................................................................................................... 49
6.
MERMAID PROTOCOLS IV: Fixed-depth Moorings ..................................................................... 53
6.1
Buoy for the acquisition of long-term optical time-series (BOUSSOLE). PI: David Antoine ... 53
6.2
Marine Optical BuoY (MOBY). PI: Kenneth Voss .................................................................... 58
7.
MERMAID PROTOCOLS V: Profiling Instruments ........................................................................ 62
7.1
Bristol Channel and the Irish Sea. PI: David McKee.................................................................. 62
7.2
California Current. PI: M. Kahru ................................................................................................ 65
7.3
Plumes and Blooms. PI: D. Siegel .............................................................................................. 66
8.
MERMAID PROTOCOLS VI: TriOS Ramses.................................................................................. 69
8.1
English Channel. PI: H. Loisel, C. Jamet .................................................................................... 69
8.2
FERRYBOX. PI: K. Sørensen .................................................................................................... 71
8.3
French Guiana. PI: H. Loisel; C. Jamet ...................................................................................... 73
8.4
Helgoland/Cuxhaven Transect. PI: R. Doerffer .......................................................................... 74
8.5
MUMMTriOS. PI: K. Ruddick ................................................................................................... 77
8.6
Wadden Sea. PI: A. Hommersom ............................................................................................... 80
9.
MERMAID PROTOCOLS VII: Miscellaneous datasets ................................................................... 83
9.1
NASA bio-Optical Marine Algorithm Data set (NOMAD). PI: Jeremy Werdell ....................... 83
10.
Appendix 1: Values of the air-sea interface transmittance as function of wind speed, ws, view
angle, ', and salinity (salt and freshwater). ................................................................................................ 89
11.
Combined References ..................................................................................................................... 94
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2011
MERIS
Optical
Measurement
Protocols
Doc
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Date
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: August 2011
PAGE : vi
List of Figures
Figure 2-1: MERMAID Website ................................................................................................................ 13
Figure 2-2: ODESA online processing. (Figure courtesy of ACRI-ST). .................................................... 14
Figure 2-3: Samples from the MERMAID template; formatted PI in-situ data. This is a sample from
AAOT. ........................................................................................................................................................ 14
Figure 2-4: The MERMAID data extraction webpage and extraction options, on the MERMAID website
available (password restricted).................................................................................................................... 22
Figure 2-5: Example extraction items: CSV file of extracted data, descriptive plots and RBG. ................ 23
Figure 3-1: AERONET-OC sites in MERMAID. ....................................................................................... 24
Figure 3-2: The AAOT structure and instrumentation; a) the main tower and operational levels (from
Hooker
et al., 2005), b)
the
CIMEL CE-318 (SeaPRISM)
instrument
(from
http://aeronet.gsfc.nasa.gov/new_web/photo_db/Venise.html). ................................................................. 28
Figure 3-3: COVE SeaPRISM site, 25 km East of Virginia Beach, Virginia: a) site location; b)
Lighthouse platform; c) AERONET sunphotometer. ................................................................................. 29
Figure 3-4: Gloria Platform, Black Sea. ..................................................................................................... 30
Figure 3-5 a) Gustav-Dahlen Tower in the northern Baltic Proper. The inset is a picture of the SeaPRISM
autonomous radiometer installed on the tower; b) The Helsinki Lighthouse in the Gulf of Finland.......... 31
Figure 3-6: LISCO site, Long Island Sound. .............................................................................................. 31
Figure 3-7: LJCO site, Eastern Australia. Images from: http://imos.org.au/ljco.html ................................ 32
Figure 3-8: The tower at MVCO ................................................................................................................ 33
Figure 3-9: The Pålgrunden lighthouse SeaPRISM platform in Lake Vänern, Sweden. ............................ 33
Figure 3-10: WAVE_CIS_Site_CSI_6. a) Platform; b) Instrumentation ................................................... 34
Figure 4-1: Spectral channels of the SIMBADA instrument ...................................................................... 37
Figure 5-1: The TACCS instrumentation rig. a) the in-water instrumentation shown being deployed by PI
Susanne Kratzer, and b) the above-water Ed sensor. ................................................................................... 42
Figure 5-2: Himmerfjärden area, NW Baltic Sea. Note that stations B1 and H2 do not differ optically
from the open sea station (Kratzer et al., 2008). STP: sewage treatment plant at the head of
Himmerfjärden close to station H5. ............................................................................................................ 43
Figure 5-3: Map of the Portuguese coast with the area of study indicated as a black box. Satellite image of
southwest coast of Portugal with the location of sampling sites A, B, C. .................................................. 50
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2011
MERIS
Optical
Measurement
Protocols
Doc
Name
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: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: August 2011
PAGE : vii
Figure 6-1: Artist‟s view of BOUSSOLE (from Antoine et al., 2008), showing the above- and in-water
radiometers, and buoy structure. ................................................................................................................. 54
Figure 6-2: The NASA MOBY instrument set-up at Lanai, Hawaii .......................................................... 59
Figure 7-1: Errors in first two points of level 3 depth-averaged Lu values. ................................................ 64
Figure 7-2: CalCOFI transect locations, California Coast. (from:
http://www.calcofi.org) ................ 65
Figure 7-3: Santa Barbara Channel, California USA. Plumes and Blooms stations are marked with an „x‟.
From Kostadinov et al. (2006). ................................................................................................................... 67
Figure 8-1: Location of the different stations visited in the eastern English Channel and southern North
Sea in 2004. The investigated area is bordered by (I) the mouth of the Seine River in the south and (II) the
mouth of the Escault River in the North. .................................................................................................... 69
Figure 8-2: Location of the stations sampled on 7-11 July 2006 (from Loisel et al., 2009)....................... 74
Figure 8-3: Route and stations of the MERIS validation campaign "c30" on 13. July 2006 ...................... 75
Figure 8-4: a) TRIOS-Spectrometer for measuring upward directed radiance from water and sky radiance,
and b) TRIOS Spectrometer for measuring downwelling irradiance .......................................................... 76
Figure 8-5 Frame with three TriOS-RAMSES hyperspectral radiometers as installed on the research
vessel Belgica (Ruddick, 2006). ................................................................................................................. 78
List of Tables
Table 1-1: Documents pertinent to the MERIS Optical Measurement Protocols. ........................................ 2
Table 1-2: MERIS TOA Spectral Bands (from the MERIS Product Handbook, [AD 4]). ........................... 4
Table 1-3: Air-sea interface terms and values used in the datasets provided to MERMAID (where
provided and where relevant). Empty cells mean the information is not available. ................................... 10
Table 2-1: Datasets in MERMAID and details of the associated PI. Acronyms are fully expanded in the
Abbreviations and Definitions list on Page xii ........................................................................................... 15
Table 2-2: In-situ bandsets in MERMAID ................................................................................................. 19
Table 2-3: MQC flag criteria definition. Flag position is counted from the first numeric character after the
leading „M‟. Unless otherwise specified: 0 = No / Not done, 1 = Yes / done/ provided, 2 = Unknown / not
available / not applicable (N/A). ................................................................................................................. 20
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2011
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Optical
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Protocols
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: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: August 2011
PAGE : viii
Table 2-4: PQC flag criteria definition. Flag position is counted from the first numeric character after the
leading „P‟. Unless otherwise specified: 0 = No / Not done, 1 = Yes / done/ provided, 2 = Unknown / not
available. ..................................................................................................................................................... 21
Table 5-1: General sensor specifications of the TACCS 09 ....................................................................... 44
Table 5-2: Mean slope factors to derive spectral Kd for all TACCS channels from Kd490 in the northwestern Baltic Sea during summer (Kratzer et al., 2008) derived from AC9 data that was measured during
field campaigns in June 2001, August 2002 and July 2008 (Kratzer and Tett, 2009, Kratzer and Vinterhav
2010). The data set was divided up into I) outer fjord & open sea stations (B1-BY31 & H2), and II) inner
fjord stations (H3-H4). ................................................................................................................................ 45
Table 5-3: Percent uncertainties for TACCS Lu (lamda,0+). 1Moore, et al. (2011), 2Type B uncertainty:
educated guess ............................................................................................................................................ 48
Table 6-1: Nominal wavelengths at which BOUSSOLE provides in-water radiometric data to MERMAID
.................................................................................................................................................................... 53
Table 8-1: Number and dates of transect campaigns .................................................................................. 77
Table 10-1: Air-sea interface transmittance (35 psu). ................................................................................. 89
Table 10-2: Air-sea interface transmittance (0 psu). ................................................................................... 91
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: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: August 2011
PAGE : ix
List of Symbols
Symbol
Definition
Dimension / units
Wavelength
nm
Solar zenith angle (s = cos(s))
degrees
Satellite or view zenith angle (v = cos(v))
degrees
Geometry (see fig. 2.1)


s

v, 


Refracted view zenith angle (‟ = sin-1(n.sin(v)))
degrees

π-θ
degrees

Relative azimuth angle between the sun-pixel and

pixel-sensor directions
degrees
Spectral radiance
W m-2 sr-1 nm-1
Radiometric quantities
L(,s,v,)
Inherent Optical Properties (IOPs)
 ( ,  )
Volume scattering function (VSF)
sr-1
Normalised volume scattering function
sr-1 m-1
Total absorption coefficient for wavelength 
m-1
Pigment absorption coefficient at 442 nm
m-1
b()
Total scattering coefficient for wavelength 
m-1
c()
Attenuation coefficient for wavelength 
m-1
m-1
~
 ( )
a()
apig(442)
b b ()
Backscattering coefficient
Apparent Optical Properties (AOPs) and derived quantities
 w(,s,v,)
Water reflectance

Fully normalised water reflectance (i.e. the reflectance
wn()
Eu ( )
Ed()
Es (λ)
dimensionless
if there were no atmosphere, and for s = v = 0)
dimensionless
Upwelling irradiance
W m-2 nm-1
Downwelling irradiance, above the surface
W m-2 nm-1
Total downwelling irradiance just above the sea surface,
W m-2 nm-1
denoted also as Ed (λ, 0+).
Water-leaving radiance
sr-1
Lwn (λ)
Fully normalised water-leaving reflectance
sr-1
Lwn_f/Q
Normalised Water Leaving Radiance - f/Q corrected
sr-1
Lw (λ)
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R(, 0-)
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: August 2011
PAGE : x
Diffuse reflectance at null depth, or irradiance reflectance
dimensionless
(Eu / Ed)
F0 ( )
f
f‟
Q(,s,v,)
Mean extraterrestrial spectral irradiance
W m-2 nm-1
Ratio of R(0-) to (bb/a); subscript 0 when s = 0
dimensionless
Ratio of R(0-) to (bb/(a + bb)); subscript 0 when s = 0
dimensionless
Factor describing the bidirectionality character of
sr-1
R(, 0-) Subscript 0 when s = v = 0; Q = Eu/Lu
Other atmosphere and aerosol properties
α
Angström exponent (α < 0).
dimensionless
ε
Eccentricity of the Earth‟s elliptic orbit
dimensionless
Aerosol optical thickness
dimensionless
τray()
O3()
Rayleigh (or molecular) optical thickness
dimensionless
Ozone optical thickness
dimensionless
Tray (λ)
Rayleigh transmittance
dimensionless
Ta (λ)
Aerosol transmittance
dimensionless
Ozone transmittance
dimensionless
Td (λ)
Total downwelling transmittance (diffuse + direct)
dimensionless
Tu (λ)
Total upwelling transmittance (diffuse + direct)
dimensionless
Surface pressure
hPa
Ozone concentration
cm-atm 
RH Relative humidity
Downwelling total transmittance at sea surface level
percent
dimensionless
Geometrical factor, accounting for multiple reflections and
dimensionless
τa()


TO3 (λ)
Ps
uO3
Td ( ,  s )
Air-water interface
( ' )
refractions at the air-sea interface (Morel and Gentilli, 1996;
defined further in Section 1.4.5)
n
f()

r
refractive index of sea water
dimensionless
Fresnel reflectance at the air-sea interface for the scattering angle 
dimensionless
mean reflection coefficient for the downwelling irradiance at the
sea surface
dimensionless
average reflection for upwelling irradiance at the air-water interface
dimensionless
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: MERIS Optical Measurement
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: 2.0
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: August 2011
PAGE : xi

Root-mean square of wave facet slopes

Angle between the local normal and the normal to a wave facet
p
probability density function of facet slopes for the illumination
dimensionless
dimensionless
and viewing configurations (s, v, )
Miscellaneous
ws
Wind-speed just above sea level
ln
Natural (or Neperian) logarithm
log10
m s-1
Decimal logarithm
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PAGE : xii
Abbreviations and Definitions
AAOT
Aqua Alta Oceanographic Tower
AD
Applicable Document
AERONET
Aerosol Robotic Network
AOP
Apparent Optical Property
AOT
Aerosol Optical Thickness
ARGANS
Applied Research in Geomatics, Atmosphere, Nature and Space
ATBD
Algorithm Theoretical Baseline Document
BBOP
Bermuda Bio-Optics Project
BOUSSOLE
BOUée pour l'acquiSition d'une Série Optique à Long termE
(Buoy for the acquisition of long-term optical time series)
BPAC
Bright Pixel Atmospheric Correction
CalCOFI
California Cooperative Oceanic Fisheries Investigations
CDOM
Coloured Dissolved Organic Matter
Chl
Chlorophyll-a concentration mg m-3
CHORS
Center for Hydro-Optics and Remote Sensing
COVE
Clouds and the Earth's Radiant Energy System (CERES)
Ocean Validation Experiment
CTD
Conductivity Temperature Depth
DPM
Detailed Processing Model
EO
Earth Observation
ESA
European Space Agency
EOLI-SA
Earth Observation Link - Stand Alone
GDT
Gustav Dahlen Tower
GPS
Global Positioning System
HLT
Helsinki Lighthouse Tower
HPLC
High Performance Liquid Chromatography
IOP
Inherent Optical Property
LOA
Laboratoire d'Optique Atmosphérique
LISCO
Long Island Sound Coastal Observatory
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: 2.0
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: August 2011
PAGE : xiii
LISE
Laboratoire Interdisciplinaire des Sciences de l'Environnement
LJCO
Lucinda Jetty Coastal Observatory
LOV
Laboratoire Océanographique in Villefranche sur mer
LUT
Look-Up Table
MEGS
MERIS Experimental Ground Segment
MERIS
Medium Resolution Imaging Spectrometer
MERMAID
MERis MAtch-up In-situ Database
MOBY
Marine Optical Buoy
MODIS
Moderate Resolution Imaging Spectrometer
MOS
Marine Optical System
MQC
Measurement Quality Control
MUMM
Management Unit of the North Sea Mathematical Models
MVCO
Martha’s Vineyard Coastal Observatory
MVT
MERIS Validation Team
NaN
Not a Number
NASA
National Aeronautics and Space Administration
N/A
Not Applicable
NCEP
National Centre for Environmental Prediction
NIR
Near Infrared
NOMAD
NASA bio-Optical Marine Algorithm Dataset
OC
Ocean Color
ODESA
Optical Data Processor of the European Space Agency
OBPG
Ocean Biology Processing Group
PAR
Photosynthetically Available Radiation
PI
Principle Investigator
PQC
Processing Quality Control
QWG
Quality Working Group
RMD
Reference Model Document
RR
Reduced resolution
RTC
Radiative Transfer Code
SeaBAM
SeaWiFS Bio-optical Algorithm Mini-Workshop
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: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: August 2011
PAGE : xiv
SeaBASS
SeaWiFS Bio-Optical Archive and Storage System
SeaWiFS
Sea-viewing Wide Field-of-view Sensor
SPM
Suspended Particulate Matter
SPMR
SeaWiFS Profiling Multichannel Radiometer
STP
Standard Temperature and Pressure (To=273.5 K; Po=1013.25 hPa)
TACCS
Tethered Attenuation Coefficient Chain Sensor
TBD
To Be Determined
TOA
Top Of Atmosphere
TOMS
Total Ocean Mapping Scanner
TSM
Total Suspended Matter (g m-3)
UK
United Kingdom
UTC
Coordinated Universal Time
VSF
Volume Scattering Function
WiSPER
Wire Stabilized Profiling Environmental Radiometer
YS
Yellow Substance absorption coefficient (m-1)
YSBPA
Absorptions of dissolved and bleached particulate matter (m-1)
Case 2(S) water:
Case 2 water dominated by SPM (see ATBD: PO-TN-MEL-GS-0005)
Case 2(Y) water:
Case 2 water dominated by yellow substances (see ATBD: PO-TN-MEL-GS0005)
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PAGE : 1
1. Introduction
Within the framework of the MERIS Data Quality Working Group (QWG) and the MERIS Validation
Team (MVT) fall the validation activities essential for product assessment and quality assurance, such as
analysis and assessment of MERIS atmospheric correction over waters and vicarious adjustment. An
integral requirement for such activities is a reliable source of in-situ radiometric data, inclusive of the
metadata and parameters required for the validation research and decision making.
The MERis MAtchup In-situ Database (MERMAID) was created to satisfy validation aims, making
available an easy-to-use centralised database of merged in-situ optical measurements with concurrent
MERIS acquisitions to Ocean Colour researchers involved in the MERIS mission.
The long-term objectives of this database are to:





Enable the assessment of the MERIS marine Level 2 products delivered by the ENVISAT ground
segment.
Support the monitoring of these MERIS products over the lifetime of the mission by providing a
complete temporal coverage of the mission.
Provide support to atmospheric correction research.
Support vicarious adjustment of the MERIS instrument.
Provide a centralised validation resource to the ESA Optical Data Processor, ODESA.
MERMAID has become the only repository for ESA MERIS matchup data, for both in-situ and MERIS
acquisitions, and ESA-funded researchers have the potential to contribute to the development of this
valuable resource, by contributing their data for matchup with MERIS imagery. Moreover, data is also
sought from external, non-ESA funded sources. Data is provided to the database through agreement with
the Principle Investigator (PI), who has pre-processed their in-situ data to a standard where it can be
matched with the sensor.
MERMAID is an ever-developing and evolving database, and users of the data and readers of this
document are invited to provide feedback, comments and suggestions to [email protected].
1.1 Document purpose and scope
The purpose of this document is to describe the protocols followed by each of the PIs whose data has
been matched with MERIS acquisitions and is included in MERMAID. Along with in-situ data, PIs
provide information on how the in-situ radiometric and bio-optical measurements were taken and
processed prior to contribution. Many PIs already provide this information in the peer-reviewed literature,
so this document is an assimilation and condensation of these protocols, designed to accompany the
database with a comprehensive description of the data held within it. The measurements in the database
are made by a variety of techniques and instruments; the Optical Measurement Protocols provide a
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guideline for the measurement of in-situ water reflectances (ρw: defined in section 1.4.2) by the means
used to acquire the data in the database.
The document does not aim to specifically promote any given technique; rather it confirms the adherence
to accepted protocols. It is important that the investigator describes the methods used for validation
because deviations from standards can cause significant problems in the interpretation of differences
between the in-situ and MERIS data.
The MERIS Optical Measurement Protocols are organised into three parts: marine reflectances,
atmospheric measurements and inherent optical property (IOP) measurements. This document is Part A,
and is concerned with the matchup of MERIS marine reflectances with in-situ measurements. It
documents measurement procedures, data processing by the PI and normalisation for MERMAID, and an
overview of the uncertainties in the data. The document is organised into several parts:
1) Introduction: the requirements for MERIS validation
2) Description of MERMAID
3) The Protocols of the MERMAID datasets currently in MERMAID.
1.2 Applicable documents
Table 1-1: Documents pertinent to the MERIS Optical Measurement Protocols.
Code
Document Title
[1]
N/A
[2]
N/A
MERIS ATBDs
http://envisat.esa.int/instruments/meris/atbd/
MERIS Data Products Overview.
http://envisat.esa.int/support-docs/productspecs/
[3]
PO-TN-MEL-GS-0026
MERIS Reference Model Document (RMD): Third Reprocessing
[4]
N/A
[5]
MERIS ATBD 2.6
[6]
N/A
[7]
D9-b-final1
MERIS Product Handbook
http://envisat.esa.int/pub/ESA_DOC/ENVISAT/MERIS/
Algorithm Identification: Case II.S Bright Pixel Atmospheric
Correction (G. Moore and S. Lavender)
Tilt correction for irradiance sensors (J.-P. Huot).
How a prediction of the radiance of the sky dome helps to improve
the water leaving reflectance measurements? (R. Santer)
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1.3 MERIS L2 water products overview
MERIS provides a number of water products at Level 2. This document is concerned with the water
reflectance, ρw (λ), and primarily that measured in-situ and subsequently matched with MERIS ρw (λ) for
MERMAID. Parts B and C will address the atmospheric products and in-water constituents such as
chlorophyll-a (Chl), yellow substances (YS), also known as coloured dissolved organic matter (CDOM),
and total suspended matter (TSM) concentration.
This is a brief overview of the products available; further details of the L2 processing may be found in the
MERIS Product Handbook (AD [4]), ATBDs (AD [1]) and Data Products Overview (AD [2]).

w : a dimensionless term, water reflectance, valid in all waters. Defined fully in section 1.4.2.

Aerosol products:
o
Aerosol optical thickness at 865nm, a(865) for the whole atmosphere (boundary layer +
troposphere + stratosphere),
o
the slope of the spectral dependence of the aerosol optical thickness between 779nm and
865nm, α(779, 865) for the whole atmosphere.

Chl1: the algal pigment index 1 (Morel and Antoine, 1999), expressed as a chlorophyll concentration
in mg.m-3, given in Case 1 waters.

Chl2: the algal pigment index 2, expressed as a Chl concentration in mg.m-3. Chl2 is related in the
neural network algorithm via a scaling equation to pigment absorption at 442nm, apig(442), given in
all waters. As applied in the MERIS product, and defined in the MERIS RMD (AD [3]), we have:
[Chl ]  21.0 [a pig (442)] 1.04

(1)
TSM, total suspended matter concentration, expressed as concentration in g.m-3, given in all waters.
TSM is related in the neural network algorithm via a scaling factor to a particle scattering at 442 nm,
bp(442), given in all waters. As applied in the MERIS product, and defined in the MERIS RMD (AD
[3]), we have:
TSM ( g m 3 )  1.73. b p (442)
(2)

YSBPA: proxy for the sum of absorptions of dissolved and bleached particulate matter at 442.5nm in
m-1. In the rest of this document YS will be reserved for yellow substance (also known as CDOM)
absorption, and BPA will be used for bleached particle absorption. YSBPA = YS+BPA.

PAR: Photosynthetically Available Radiation.

Case 2_S: a flag indicating the presence of TSM in significant concentration.
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
Case 2_Anom: a flag indicating abnormally high scattering in Case 1 water.

Case 2_Y: a flag indicating YS loaded water. This flag is at the moment inactivated in the ground
segment processing pending validation.
Marine reflectances, the subject of the present document (Part A), are given at 13 spectral bands: bands 1
to 10, 12, 13, 14. Band 11 (761.875nm) and 15 (900nm) are strong absorption bands by O2 and water
vapour, H2O, respectively. All bands are defined in Table 1-2 below. The characterised mean wavelengths
(over the 5 MERIS cameras) are used in the product evaluation procedure.
1.3.1 MERIS Atmospheric correction
Information and detail on the MERIS atmospheric correction, atmospheric parameters, definitions and
coefficients can be found in AD [3], the MERIS Reference Model Document (RMD) for the Third
Reprocessing. The Bright Pixel Atmospheric Correction (BPAC) is now applied as standard and detailed
in both AD[3] and AD[5], as listed in Table 1-1.
Table 1-2: MERIS TOA Spectral Bands (from the MERIS Product Handbook, [AD 4]).
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1.4 General radiometry and water colour
1.4.1 Definition of case 1 and case 2 waters
Natural waters can be classified into water types, Case 1 or Case 2, according to their optical properties
which vary according to what is present in the water (Gordon and Morel, 1983; Morel and Prieur, 1977).
In Case 1 water it is recognised that the principle agent responsible for variations in the IOPs is
phytoplankton and their degradation products only, and that the global variations in IOPs in these waters
can be represented by average models where the chlorophyll concentration is used as the unique index of
these changes.
In Case 2 waters it is often likely that the optical properties of substances other than phytoplankton
dominate the bulk optical properties; those substances vary independently of phytoplankton, particularly
TSM which presents a backscattering, bb (λ), component, and Coloured Dissolved Organic Matter
(CDOM, or yellow substances), presenting issues for Chl retrieval algorithms. Case 2 water bodies
display spatial and temporal variations in their organic and inorganic composition, often on small
temporal and spatial scales. This patchiness may cause issues when it comes to matchup with MERIS RR
imagery.
1.4.2 Definition of the product ρw (λ)
For the following and ensuring radiometric descriptions, all symbols are defined for reference in the
Symbols Table (Page xii).
Surface water is assumed to be Lambertian and its reflectance, w, is defined as:
 w ( ) 
 . Lw ( , v , s , vs )
E s ( ,  s )
(3)
where Lw (λ) is the upward water leaving radiance (which does not account for any specular reflected
direct sun or sky radiance), and Es (λ) is the total downwelling irradiance at sea level, comprising of both
diffuse and direct components.
1.4.3 Downwelling solar irradiance at ground level, Es (λ)
Es is measured directly in-situ, at the sea level, with instrumentation or it may be derived by:
Es ( )  Fo ( )  d 2 Td ( , s _ IS )  cos  s _ IS 
(4)
where:
F0 is the Thuillier et al. (2003) mean extraterrestrial solar irradiance.
d2 is the corrective factor of the extraterrestrial sun irradiance, accounting for the Sun-Earth
distance as a
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function of the Julian day (J) (see the MERIS RMD).`
θs (solar zenith angle) is computed for the time of the in-situ measurement (i.e. θs_IS)
Td is the total atmospheric transmittance for the downwelling path only and includes the
contribution of gaseous absorption. Formulations for computing Td are described for MERIS in
the MERIS RMD.
Another approach taken by some PIs, is to extrapolate Ed (0-) across the surface to derive Ed (0+), an
alternative term for Es. If used, the details are provided in the relevant protocol later in this document.
1.4.4 ρwn_ISME: correction for in-situ solar irradiance in w
Because the solar illumination used in the computation of the in-situ reflectance can be different from that
of the MERIS processing, MERMAID contains a complementary in-situ water reflectance consistent with
the MERIS formulation of Es, as a MERIS and in-situ quality control indicator. In-situ ρw (λ) is
renormalized to Es with the MERIS definition, using the ratio between the irradiance measured at sea
level and the MERIS-like irradiance estimated at ground level (Equation 5). The latter, termed „ρwn_ISME
(λ)‟ once normalised as usual (where „IS‟ is for „in-situ‟ and „ME‟ is for „MERIS‟), is calculated exactly
using the solar irradiance at TOA (as described in the MERIS DPM) and the total downwelling
transmittance, Td (λ), from MERIS LUTs.
Additional columns exist in MERMAID for ρwn_ISME (λ) at the same 13 bands as ρw_IS (λ).
 wn _ ISME ( )   wn _ IS ( ) 
EsIS ( )
EsMERIS ( )
(5)
To enable this, PIs provide to MERMAID their in-situ Es (whether computed as in Equation 4 or
measured directly with instruments). For the sites in MERMAID using CIMEL instruments (namely
AERONET-OC), an extra stage is added to the pre-matchup processing: Es is computed as in Equation (4)
using Gordon and Wang (1994) approximations and values of τray (Hansen and Travis, 1974) from the
RMD (Table 6-1 in the RMD).
1.4.5 Normalisation of Case 1 ρw (λ)
In Equation (3), neither quantities (ρw or Lw) are normalised to zenith sun or to nadir viewing angle, which
is a requirement for consistency with MERIS. The normalisation procedure applied to in-situ radiometric
data in MERMAID is the same as that used in the present MERIS Processor, MEGS (v8.0). The
normalisation utilises a look-up table for f /Q, and follows Morel and Gentilli (1993), Morel et al. (1995)
and Morel and Gentilli (1996). In MERMAID, the procedure for normalisation is as follows:
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 f 0 ( , a , Chl ) 


Q0 ( , a , Chl ) 
0

 wn ( )   w ( ) 

( ' , ws )  f ( , a , Chl , s , ' ,  ) 


 Q( , a , Chl , s , ' ,  ) 
(6)
where:
 sin( ) 

 n 
 '  arcsin 
where n is the refractive index of sea water (dimensionless),
0  ( '  0, ws  0)
is the „Gothic R‟ factor as described in Equation (7).
 f 0 ( , a , chl ) 


 Q0 ( , a , chl ) 
is the f/Q factor for an illumination/viewing configuration at the zenith/nadir,
Chl
is known from in-situ or computation from ρw (λMERIS) using the MERIS
algal_1 Chl algorithm,
τa
is an assumed constant value in MERMAID
The “Gothic R”, , factor (Morel and Gentilli, 1996) is defined by:
 (1   ) (1   f ( ' )) 
( ' )  

n2
 (1  r f )

(7)
where:
 f ( ' ) is the Fresnel reflectance at the air-sea interface for the scattering angle  '  (dimensionless)
 is the mean reflection coefficient for the downwelling irradiance at the sea surface (dimensionless)
r is the average reflection for upwelling irradiance at the water-air interface (dimensionless)
 are available in the MERIS RMD (AD [3]).
f (,s), is a function relating the apparent optical properties (and specifically the irradiance
reflectance) to IOPs (Morel et al, 2002):
 E ( ,  s )   a ( ) 
 

f ( , s )   u
 Ed ( , s )   bb ( ) 
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where Eu (λ) is the upwelling irradiance and Ed (λ) the downwelling irradiance.
a (λ) is the absorption coefficient
bb (λ) is the backscattering coefficient
Q (,‟,s,), is defined as:
Q ( , s , ' ,  ) 
E u ( ,  s )
Lu ( , s , ' ,  )
(9)
1.4.6 AERONET-OC (Ocean Color sites) normalisation
AERONET-OC data are fully normalised according to Morel et al. (2002), and relies on Chl-a determined
from the application of regional bio-optical algorithms to the normalised radiances, Lwn (λ), as in Zibordi
et al. (2009a). The full normalisation of Lwn also accounts for (cos(θs) . d2 .Td; as in Equation 4), thus
allowing for use of F0 to make the conversion to ρwn.
The LUT used for the normalisation is that of Morel, and are available only for a single value of τ a, 0.2.
Normalisation is applied assuming case 1 waters only.
The processing of AERONET-OC data is documented in Zibordi et al., (2009b, 2004) and is consistent
with that applied for MERMAID (described in section 1.4.5).
For MERMAID, AERONET-OC radiances are converted into normalised water reflectance, ρwn (λ) by:
 wn ( ) 
 .Lwn _ f / Q ( )
F0 ( )
(10)
1.4.7 Normalisation of Case 2 reflectances.
The theory and method for determining exact normalised water reflectance is limited to Case 1 which are
homogeneous and relatively clear water masses with Chl ≤ 3 mg m-3, due to the use of an empirical
function for remotely-sensed Chl. The algorithm for normalisation of water reflectance in Case 2 waters is
still in development for MERMAID and a Case 1 normalisation is applied for all sites at present.
1.5 Requirements and recommendations for the validation of MERIS w
In the validation of MERIS w a number of in-situ radiometric measurements are required, ideally at
MERIS bands (Table 1-2).
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1. Unnormalised reflectance, ρw to allow for consistency in the normalisation procedure.
2. Downwelling irradiance above the sea surface Ed0+ (λ), i.e. Es (λ).
Ed(0-,λ) is not sufficient due to fluctuations associated with focusing and defocusing of sunlight by
surface waves (Zaneveld et al., 2001) making such measurements noisier than Es (λ) made above the
surface (even though Ed(0-,λ) can be affected by ship or buoy motion).
3. Vertical profile of downwelling irradiance Ed (z) at MERIS wavelengths with reference of Ed (0+) at
surface (W m-2 nm-1) taken simultaneously.
4. Vertical profile of upwelling nadir radiance Lu (z) with reference of Ed (0+) at surface (W m-2 nm-1 sr1
) taken simultaneously.
5. Vertical profile of upwelling irradiance Eu (z) at MERIS wavelengths with reference of Ed(0+) at
surface (W m-2 nm-1) taken simultaneously.
6. Measurements of Ed and Eu or Lu at a minimum of 2 fixed depths in the water column, close to the
surface, and with reference Es taken simultaneously.
According to Mueller et al., (2003c), at present the most reliable in-situ method of determining waterleaving radiance Lw (λ) is to extrapolate an in-water profile measurement of Lu (z, λ) to the sea surface to
estimate Lu (0-,λ). Using the Fresnel laws, the water-leaving radiance can be computed as:
Lw ( , , )  Lu (0  ,  , ' , )
[1   f ( ' , )]
n2
(11)
where ρf (θ,θ‟) is the Fresnel reflectance of the sea-air interface for the associated directions θ (incident)
and θ‟(refracted), and n is the refractive index of seawater, and can be approximated with a value of 1.34
(Austin, 1974). The Fresnel transmittance is represented by the term [1-ρf] on the right hand side of
Equation (11), and can be approximated by the value of 0.975.
MERMAID PIs have used a variety of approaches and constants for these terms, as summarised in Table
1-3. In Section 10 (Table 10-1 and Table 10-2) are provided exact values of transmittance at the air-sea
interface, which may be used by the MVT (and presently used by two PIs, J. Icely and S. Kratzer).
Transmittance through the air-sea interface is a function of wavelength, temperature and salinity and can
be tabulated as function of these 3 parameters. It is a recommendation that LUTs of exactly computed airsea transmittance are made available by the MERIS QWG to the MVT and that PIs use them according to
measurement conditions (temperature and salinity).
If the PI's decide to use an approximated value for Fresnel transmittance and the refractive index for
seawater then an adjustment may be incorporated in the MERMAID processing: dividing Lw (λ) from the
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PI by the approximation 0.543 and multiplying by the tabulated air-sea transmittance to account for its
spectral variability and the dependence with temperature and salinity.
Es (λ) is then used to determine RRS by:
RRS ( ) 
Lw ( )
E s ( )
(12)
The RRS is then related to ρw (λ) by:
 w ( )   RRS
(13)
Table 1-3: Air-sea interface terms and values used in the datasets provided to MERMAID (where provided
and where relevant). Empty cells mean the information is not available.
Transmittance at
the air-sea
interface
MERMAID
PI
MERMAID
DATASET
(1   f )
n2
D. Antoine
R. Doerffer
A. Hommersom
J. Icely
M. Kahru
S. Kratzer
H. Loisel
D. McKee
K. Voss
K. Ruddick
D. Siegel
K. Sorensen
J. Werdell
BOUSSOLE
Helgoland
Wadden Sea
Sagres
California
Current
NW Baltic Sea
Fr. Guyanan
and E. English
Channel
Bristol channel
& Irish Sea
MOBY
MUMMTriOS
Plumes and
Blooms
Ferrybox
NOMAD
Fresnel
reflectance at
the air-sea
interface
Refractive
index of
seawater
Fresnel
transmittance
at the air-sea
interface
f
n
1  f
0.97
0.54
0.54
Factors in Table
10-1
0.543
0.543
0.025
1.34
0.021
1.345
0.02
1.34
0.02
1.34
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1.5.1 Measurement procedures and corrections
Ship and instrument position relative to sun
It is critical when making optical field measurements from a ship that due care is taken to avoid shading
and reflection due to or at the ship‟s body. All measurements must be carried out apart from the ship body
to avoid these effects and Mueller et al. (2003c) detail several methods to achieve this. This is an essential
criterion because a correction is not possible. However, in turbid Case 2 water the effect of the
underwater body of the ship is less critical due to the longer optical paths, although care must still be
taken for consistency. Free-falling profilers provide the possibility to operate the instrument sufficiently
away from the ship. Another source of uncertainty that appears in turbid waters is that the ship often
totally disrupts the vertical and horizontal structures of the water mass, so that the representativeness of
measurements is uncertain. Using as small ship as possible is a solution here (as far as logistics permit).
Furthermore, due care should be taken to avoid self-shading by the instrument in use; Mueller et al.
(2003c) provide a correction protocol for this, based on Gordon and Ding (1992) and Zibordi and Ferrari
(1995).
Dark readings
The dark current of optical sensors is frequently temperature dependent. As a consequence, accurate
radiometric measurements require that careful attention be given to dark current variability. Mueller et al.,
(2003c) recommend that each optical measurement be accompanied by a measurement of the instrument
dark current.
Patchiness
Optical measurements in patchy waters are of little value for validation because of the difficulty of
defining matchups. But they retain their value for the establishment of models. In that case a number of
IOP samples should be taken at the same time as reflectance samples to establish a statistical relationship.
Patchy waters may be sampled, although protocols for the matchup procedure are yet to be defined. The
strengthened focus on improved validation in Case 2 waters means that currently all data is accepted from
a PI. However extreme care must be exercised because it is impossible to relate concentrations to optical
measurements if a sample has been taken some 10 metres apart from the water body observed by the
optical instrument or if optical measurement and sample are not taken at the same time.
1.5.2 Ideal criteria for validation
There are a number of ideal criteria that should be met when making in-situ optical measurements:

Water dynamics low, to get data points which are valid for the geographical position for a few hours;

Water depth >> optical depths at wavelength of maximum transparency;

Vertical homogenous water;

Horizontal homogenous water;
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
Sufficiently far from land to avoid inclusion of land surface in pixel and influence of land reflectance
on atmospheric path radiance (> 5km);

Sun zenith angle s at the time of measurement /satellite pass should be < 60°. Note that pixels with a
larger s are flagged in the MERIS L2 product;

For a direct comparison between reflectance measurements and data derived from MERIS only clear
sky conditions with preferably low aerosol concentrations are acceptable;

Radiometric measurements should be discarded for validation when contaminated by thin stratus,
cirrus clouds or fog.
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Doc
Name
Issue
Date
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: July 2011
PAGE : 13
2. The ‘MERIS MAtchup In-situ Database’ (MERMAID)
2.1 Introduction
The MERMAID database (Figure 2-1) was initiated in
2007 at ACRI-ST with the collation of radiometric
data from established time-series measurement sites.
In 2008 it officially became „MERMAID‟ (Barker et
al., 2008) and efforts were increased by ARGANS Ltd
to acquire more in-situ datasets. ACRI-ST and
ARGANS work together to improve the database and
extraction website. ARGANS‟ current efforts are
aimed at gathering further radiometric measurements,
and also now atmospheric parameters (to be addressed
in a subsequent protocols document). ARGANS is the
initial point of contact for the PI, whereby an
agreement of use is negotiated and the data is provided
in a suitable format. ACRI-ST is responsible for
matching the data with MERIS products and making
the database available online via a web interface.
The
MERMAID
data
format
document
(http://hermes.acri.fr/mermaid/format/format.php)
outlines the parameters in MERMAID. MERMAID is
hosted at http://hermes.acri.fr/mermaid. All queries,
suggestions and feedback can be made to
[email protected], and new PIs should make contact
Figure 2-1: MERMAID Website
via this address.
2.1.1 Minimum data requirements: Optical data and auxiliary information
MERMAID is flexible in how PIs submit their data, however it requested that PIs provide as a minimum:

Water reflectances, ρw (visible and NIR, at MERIS bands if possible); either multi or hyperspectral.
Or, hyperspectral convolved to the last definition of the 15 MERIS spectral filters;

The associated water-leaving radiances, Lw (λ) and downwelling surface irradiance, Es (λ), or Ed (λ
,0+), from which ρw were computed (or relevant CIMEL or TriOS parameters);

Associated Chl-a measurements (if available), with a description of the method to derive it;

Sun zenith angles if available;

Associated meta data (latitude, long, date, time in UTC);

A written protocol to be included in the MERIS Optical Measurement Protocols document; it is a
requirement of potential usage in matchups that adherence to an accepted protocol is confirmed.
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Optical
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Date
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: MERIS Optical Measurement
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: 2.0
Rev.:
1.0
: July 2011
PAGE : 14
Additional information ideally consists of the sun zenith angle measurement, θs, and, if available, a
measurement of Chl-a, which is a requirement for the ρw (λ) normalisation procedure. If the θs is not
provided, it is computed as a function of latitude and longitude (both in decimal degrees), and time (UTC
time of observation). If in-situ Chl-a is not provided, it is computed from in-situ ρw using the MERIS
chlorophyll algorithm.
2.1.2 MERMAID as a validation tool for ODESA: Additional parameter requests
ODESA, the Optical Data processor of ESA
(Figure 2-2, http://earth.eo.esa.int/odesa/),
provides users a complete level 2 processing
environment for MERIS, as well as for the
future ESA optical sensors on board Sentinel 3.
ODESA supplies the user community with the
MERIS Ground Segment development platform
MEGS®, including source code, embedded in
an efficient framework for testing and for
validation activities. Such facilities include
match-up processing & analysis using
MERMAID, and to this end MERMAID can
now accept other data than optical.
If available MERMAID now accepts
concentrations such as TSM and CDOM, and
primary inherent optical properties (IOPs) i.e.
total absorption, at (λ); backscattering bb (λ)
and the component IOPs (i.e. those contributing
to at (λ) and bb (λ)).
Figure 2-2: ODESA online processing. (Figure
courtesy of ACRI-ST).
2.1.3 MERMAID in-situ data format
MERMAID presently does not strictly specify a format for data submission. On receipt, the data are
formatted to a format suitable for the web interface (a section of which is exemplified in Figure 2-3). The
in-situ template consists, as minimum, of the geographical and temporal information, θs, Chl-a (if
available), depth and ρw (λ). Traceability of the data is essential and the template retains the site and the PI
name. Any additional parameters submitted are included in columns after these mandatory fields.
Figure 2-3: Samples from the MERMAID template; formatted PI in-situ data. This is a sample from AAOT.
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MERIS
Optical
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Protocols
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: MERIS Optical Measurement
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: 2.0
Rev.:
1.0
: July 2011
PAGE : 15
2.1.4 Current datasets in MERMAID
Table 2-1 summarises all the datasets currently in MERMAID and the associated contact details of the respective PIs.
Table 2-1: Datasets in MERMAID and details of the associated PI. Acronyms are fully expanded in the Abbreviations and Definitions list on Page xii
DATASET
AAOT
AERONET-OC
Abu AlBukhoosh
COVE_
SeaPRISM
Gloria
GustavDahlen Tower
LISCO
LJCO
Helsinki
Lighthouse
Pålgrunden
MVCO
WAVE_CIS_
Site_CSI_6
LOCATION
N. Adriatic Sea
45.31oN, 12.50oE
Arabian Gulf
25N 53E
Cove, Virginia
36.9oN, 75.7oE
Black Sea
44.3oN, 29.2oE
Baltic Sea
58N, 17E
Long Island Sound, USA
40.5oN, 73.2oE
Queensland, NE Australia
18.3oS, 146.2oE
Baltic Sea
59N, 24E
Lake Vänern, Sweden
58N, 13E
Martha‟s Vineyard, USA.
41N, 70W
Gulf of Mexico
28.8oN, 90.4oE
PARAMETERS
IN MERMAID
PI
Lwn (λ), a (λ)
G. Zibordi
Lwn (λ), a (λ),
Chl
Lwn (λ), a (λ),
Chl
Lwn (λ), a (λ),
Chl
Lwn (λ), a (λ),
Chl
Lwn (λ), a (λ) ,
Chl
Lwn (λ), a (λ) ,
Chl
Lwn (λ), a (λ) ,
Chl
Lwn (λ), a (λ) ,
Chl
Lwn (λ), a (λ) ,
Chl
Lwn (λ), a (λ) ,
Chl
G. Zibordi
B. Holben
G. Zibordi
G. Zibordi
S. Ahmed/
A. Gilson
V. Brando
G. Zibordi
S. Kratzer
D.
Vandemark
B.Gibson
A.
Weidermann
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PI Affiliation
Joint Research Centre, Ispra,
Italy (JRC)
Joint Research Centre, Ispra,
Italy (JRC)
NASA GSFC
Joint Research Centre, Ispra,
Italy (JRC)
Joint Research Centre, Ispra,
Italy (JRC)
City College of New York
CSIRO, Australia
Joint Research Centre, Ispra,
Italy (JRC)
University of Stockholm,
Sweden
University of New Hampshire,
USA
Coastal Studies Inst. Louisiana,
USA & NRL, Mass. USA
2011
PI email contact
guiseppe.zibordi
@jrc.it
guiseppe.zibordi
@jrc.it
[email protected].
nasa.gov
guiseppe.zibordi
@jrc.it
guiseppe.zibordi
@jrc.it
ahmed / gilerson
@ccny.cuny.edu
Vittorio.Brando
@csiro.au
guiseppe.zibordi
@jrc.it
Susanne.kratzer
@ecology.su.se
doug.vandemark
@unh.edu
[email protected] &
Alan.Weidemann
@nrlssc.navy.mil
MERIS
Optical
Measurement
Protocols
DATASET
LOCATION
PARAMETERS
IN MERMAID
PI
Algarve
Sagres, 36/37N. 8E
ρw (λ), Es (λ)
J. Icely
BOUSSOLE
W. Med. 43.367oN, 7.9oE
D. Antoine
Bristol
Channel and
Irish Sea
California
Current
English
Channel
French
Guiana
MOBY
Bristol Channel &
Irish Sea
Variable: 51/54N, -3/-4E
California Coast. Variable:
32-34oN, 120-121oW
English Channel
ρw (λ), Chl,
Es (λ)
ρw (λ), Ed (λ)
Lu (λ), Es (λ).
M. Kahru
ρw (λ)
H. Loisel/
C. Jamet
H. Loisel/
C. Jamet
K. Voss
D. McKee
French Guiana
ρw (λ)
Lanai, Hawaii
20.822oN, 157.187oW
Lw (λ), Es (λ).
MUMM_
TriOS
Variable
ρw (λ), Ed (λ), K. Ruddick
NOMAD
Variable
Lw (λ), Es (λ).
J. Werdell
N.W. Baltic
Sea
Plumes and
Blooms
SIMBADA
NW Baltic
Variable: 58N, 17E
ρw (λ), Es (λ)
S. Kratzer
Variable
ρw (λ) a (λ)
P-Y.
Deschamps
Wadden Sea
Wadden Sea
52-53N, 4-6W
RRS (λ)
A.
Hommersom
Lse (λ),Lsk(λ), Lw
(λ), SPM, Chl-a.
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Date
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
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: 2.0
Rev.:
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: July 2011
PAGE : 16
PI Affiliation
PI email contact
Sagremarisco Lda,
Portugal
Laboratoire d'Océanographie de
Villefranche, France (LOV).
University of Strathclyde, UK.
alicely2
@gmail.com
Antoine
@obs-vlfr.fr
david.mckee
@strath.ac.uk
University of California, San
Diego
laboratoire d'oceanologie et de
geosciences (LOG)
laboratoire d'oceanologie et de
geosciences (LOG)
National Oceanic and
Atmospheric Administration,
USA (NOAA).
Management Unit of the North
Sea Mathematical Models,
Belgium. (MUMM)
NASA Goddard Flight Centre,
USA.
University of Stockholm,
Sweden
[email protected]
Laboratoire Optique
Atmospherique - Université de
Lille (LOA).
University of Amsterdam
Deschamp
@univ-lille1.fr
Cedric.Jamet
@univ-littoral.fr
Cedric.Jamet
@univ-littoral.fr
Kenneth Voss
@noaa.gov
K.Ruddick
@mumm.ac.be
Jeremy.werdell
@gsfc.nasa.gov
Susanne.kratzer
@ecology.su.se
D. Siegel
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2011
annelies.hommersom
@ivm.vu.nl
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Optical
Measurement
Protocols
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Date
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: July 2011
PAGE : 17
2.1.5 Matchup with L2 MERIS data
MERIS Level 0 data are received by ACRI-ST through DDS (Data Dissemination System) and locally
archived. From the geographic and temporal information, ACRI-ST processes the relevant L0 products
with the MERIS Ground Segment data processing prototype, (MEGS 8.0) up to L1. MEGS is developed
and maintained in ACRI-ST and is in line with the MERIS IPF (Instrument Processing Facility). A
custom processing of the L1 up to Level 2 is required as some of the MERMAID data are intermediary
processing products and are therefore not available in standard L2 products. The generation of these
intermediary products is handled through ODESA. From these MERIS data is extracted a range of
products coincident with the in-situ information.
Extraction is achieved on 5x5 reduced resolution (RR) pixels around the site corresponding to in-situ
acquisition. The default extraction criteria selected on MERMAID web page follows the procedure
described by Bailey and Werdell (2006) when applicable. This procedure concerns time elapse between in
situ and satellite measurement, flags selection and statistical screening:

Time elapse: Difference in time between MERIS and the in-situ measurement does not exceed 3
hours. In the web interface the user can specify their preferred time difference up to +/-12 hours. +/12 hours is the search limit for matching MERIS overpasses.

Flags: At least 50% of the pixels in the box (selected macropixel) are not flagged as land, cloud,
high/medium-glint, ice haze, PCD-1-13 (uncertain normalised surface reflectance) or PCD-19
(uncertain aerosol type/optical thickness). The latter two flags correspond to a failure in atmospheric
correction and thus depend highly on the algorithm itself. However, Bailey and Werdell (2006)
recommend their inclusion.

Statistical screening: For a given wavelength, the mean, and standard deviation of ρw (  w , σ) is
computed over non-flagged pixels. Based on these two parameters, two statistical tests are performed
on a band per band basis, allowing some reflectances to be selected and other not:
o
The “filtered mean”: A value in a macropixel is rejected if (  w     w  )  FC * .
FC the filtering coefficient is set to 1.5 but it can be specified.
o
The “coefficient of variation” (CV criteria): the entire macropixel is rejected if
    w    CV   . The CV coefficient is set to 0.15 but it can be specified band per
band.
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: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
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: 2.0
Rev.:
1.0
: July 2011
PAGE : 18
2.2 Atmospheric parameters in MERMAID
Included in the MERMAID database are a number of atmospheric parameters: τa(870), τa(665) and α. If
the PI has these to provide, τa(865) and τa(665) are included directly in MERMAID. Presently, just
AERONET-OC sites provide these parameters to MERMAID, and in the MERMAID processing, α is
computed from τa following the Gordon and Wang (1994) approximation:
  
 865 

 a ( )   a (865) . 
(14)
In the case of AERONET-OC 870 nm is received, therefore it is used instead of 865 nm.
The bands used to compute α are either 870 nm and 665 nm, or 870 nm and 675 nm, depending what is
received from the AERONET-OC site. This is indicated in the PQC column of an extraction (Processing
Quality Control), in the 7th and 8th bit of the flag string (see Section 2.5 and the relevant extraction file for
more information).
2.3 MERMAID uncertainties
The various measurement protocols attached to each of the datasets in MERMAID will introduce
uncertainties specific to the measurement system and which should be assessed in order to qualify the
measurements in question as being usable for validation purposes. PIs are therefore encouraged to provide
traceability of their measurements and credible uncertainty estimates.
2.4 ρw spectral correction
For the AERONET-OC sites Aqua Alta Oceanographic Tower (AAOT), Gustav-Dahlen Tower (GDT),
Helsinki Lighthouse Tower (HLT) Zibordi et al. (2009a) have developed a series of algorithms based on
local measurements of IOPs to band-shift correct radiance measurements at the AERONET-OC bands to
MERIS (or any other sensor) bands. G. Zibordi performs the correction for AAOT, but for the present
time the GDT and HLT data remain at AERONET-OC bands.
Table 2-2 summarises the bands at which in-situ data is received and included in MERMAID. For those
not at MERMAID bands, the current method for MERMAID matchup is to use the data at the bands
nearest to the MERMAID bands (but not > 5nm).
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: MERIS Optical Measurement
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: 2.0
Rev.:
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: July 2011
PAGE : 19
Table 2-2: In-situ bandsets in MERMAID
DATASET
AERONET-OC
MERMAID
CENTRE BANDS
412.5
442.5
490
510
560
620
665
681.25
708.75
753.75
778.75
865
885
AAOT
Abu-Al-Bukhoosh
COVE_SeaPRISM
Gloria
Gustav-Dalen Tower
413
413
413
412
412
443
440
441
441
439
490
500
489
491
500
-----
560
555
551
555
554
------
665
-668
---
-675
-675
675
------
------
------
-869
869
870
870
------
Helsinki-Lighthouse
413
441
491
--
555
--
668
--
--
--
--
870
--
LISCO
LJCO
MVCO
Pålgrunden
WAVE_CIS
413
412
412
412
411
442
441
439
440
442
491
491
500
490
491
------
551
551
555
555
555
------
668
668
-668
668
--674
---
------
------
------
870
870
870
868
869
------
412.69
442.56
489.88
509.81
559.59
619.60
664.57
680.82
708.32
753.37
778.41
--
--
BOUSSOLE
412
443
490
510
560
--
665
683
--
--
--
--
--
Bristol Ch. & Irish Sea
412
443
489
510
554
665
--
700
--
--
--
--
California Current
412
443
490
510
555
625
665
--
710
--
--
--
--
English Channel
412
442
490
511
559
619
664
--
--
--
775
--
--
Algarve
412
442
490
510
560
620
664
--
--
--
776
864
--
MOBY
412.5
442.5
490
510
560
620
665
681.25
708.75
753.75
778.75
865
885
MUMMTriOS
French Guiana
412.5
442.5
490
510
560
620
665
681.25
708.75
753.75
778.75
865
885
NOMAD
411
443
489
510
619
665
683
--
--
--
--
--
NW Baltic Sea
412
443
490
510
555/560
560
620
665
681
708
--
--
--
--
Plumes and Blooms
412
443
490
510
555
665
--
--
SIMBADA
410
443
490
510
560
620
670
--
--
750
--
870
--
Wadden Sea
412
443
490
510
560
620
665
681
708
--
--
--
--
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PAGE : 20
2.5 Measurement and Processing flags
Flags are required to define the level of quality control (QC) applied to the in-situ data. Two QC indicator
columns are included in MERMAID, each made of a string of 18 characters pertaining to a “flag”, i.e. a
particular aspect of the measurement protocol processing procedure.
MQC (Measurement Quality Control): defines the quality control checks made by the PI, prior to
submission. It pertains to the provision, or not, of a clearly defined measurement and processing protocol
by the in-situ data provider. An example MQC string is: M120000001101111210; the numbers are the
string options in the position indicated in Table 2-3, in this example protocol is provided, indicated in
position 1, no correction for straylight is made (position 3), and so on.
Table 2-3: MQC flag criteria definition. Flag position is counted from the first numeric character after the
leading ‘M’. Unless otherwise specified: 0 = No / Not done, 1 = Yes / done/ provided, 2 = Unknown / not
available / not applicable (N/A).
Flag
String
ID
position
options
1
2
3
4
5
6
7
8
9
10
11
12
13
14
01
012
012
012
012
01
01
01
01
0 1 2 (L1.5)
01
012
012
0123
15
16
01
012
17
18
01
0 1 2 (L1.5)
MQC
Flag
Conditions and criteria
Protocol provided by PI
Correction of self-shading (2 = N/A as self-shading avoided).
Correction for straylight (2 = N/A)
Made dark measurements (and used in processing)
Measured immersion coefficients (and used in processing)
Instrument calibration history provided
Data processed to MERIS band characterisation
Hyperspectral integration done
Error budget provision
In-situ data filtering (PI‟s QC checks)
In-situ ρw already normalised or f/Q and  corrected
Tilt measurement made
Calibration of tilt sensor
Type of Es: Es or Ed(0+) (0 = N/A, 1 = Es measured in-situ, 2 = Ed(0+)
measured in-situ/derived in-situ, 3 = Es computed)
Es tilt corrected
Type of Lu: Lw or Lu(0-) (and extrapolated to Lw(0+). (0 = N/A, 1 = Lw, 2 =
Lu(0-) (and extrapolated to Lw(0+).
Lu tilt corrected
(AERONET-OC only) Data quality level: 0 = N/A, 1 = L1.5, 2 = 2.0 (see
AERONET website http://aeronet.gsfc.nasa.gov, for more details)
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PQC (Processing Quality Control): defines the post-submission quality control performed on the in-situ
data by ARGANS, and includes information on the normalisation procedure. The flag provides
information on the MERMAID in-situ processing for both the optical data received (e.g. ρw) and the
atmospheric parameters (e.g. α) newly added to the database. An example PQC is: P1010100 i.e. the ρw
passed the QC test (position 1), and it got Case 1 normalisation, not Case 2 (positions 3 and 4).
Table 2-4: PQC flag criteria definition. Flag position is counted from the first numeric character after the
leading ‘P’. Unless otherwise specified: 0 = No / Not done, 1 = Yes / done/ provided, 2 = Unknown / not
available.
Flag
String
ID
position
Options
PQC
Flag
1
2
3
4
5
6
01
012
01
01
01
01
7
8
01
01
Conditions and criteria
Passed in-situ ρw QC
Hyperspectral integration
Case 1 Normalisation by MERMAID *
Case 2 Normalisation
Band shifted correction [AERONET-OC data only; presently only AAOT]
Nearest neighbour (refer to MERIS Optical Protocols):
0 = data at bands greater than ±5nm from MERIS
1 = data at bands less than ±5nm from MERIS
**NOMAD only: Flag is 0 when data is at 560 nm and 1 when at 555 nm
AlphaNIR (1 & 2) derived from 870-675 nm
AlphaNIR (1 & 2) derived from 870-665 nm
*See MQC flag #11 to check if normalisation has already been performed by PI.
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2.6 Data Access and Policy
2.6.1 User login and Password
MERMAID is subject to a strict data access policy viewable at
http://hermes.acri.fr/mermaid/policy/policy.php.
The database is made available to the MERIS QWG, the MVT and the contributing PIs through an
access-restricted data extraction page, for which a unique password is provided. PIs are given access if
they have submitted in-situ data and matchups are confirmed. Restricted access such as this allows for
better security and for site-use monitoring.
The password and login details must not be passed on to others; the MERMAID team must be contacted
and the colleague in question will be considered but not guaranteed access.
We welcome use of MERMAID outside the scope of the MERIS maintenance and evolution project.
Interested users who are not part of the MQWG, MVT or are not PIs, can request access with a unique
password through a Service Level Agreement. Please email [email protected] to express interest and
provide a description of your project.
2.6.2 MERMAID web interface.
The web interface (Figure 2-4) is versatile,
allowing users to specify their own extraction
criteria. In addition to selecting sites and dates, the
user can, for instance, extract matchups for a 1,
3x3 or 5x5 pixel grid, and for a time difference of
up to 3 hours. Geometry options are available to
the user, as are flag selection and statistical
screening options, all allowing for adaptable and
flexible matchup selection.
Processing version
Site selection and date range
Physical screening and flag acceptance options
Statistical screening
Correction on ρw for theoretical Es
Figure 2-4: The MERMAID data extraction
webpage and extraction options, on the MERMAID
website available (password restricted).
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2.6.3 Data submission
PI‟s should write to [email protected] to enquire about data submission. ARGANS is the next point of
contact for the PI, who is requested to submit data in any format (e.g. ASCII, HDF), as long as it is
adequately labelled and is accompanied by a protocol describing measurement and processing methods.
2.6.4 MERMAID extraction package
Once selections have been made, MERMAID extractions are provided as „Filzip‟ files: zip files
containing the extracted data, statistics and uncertainties files, regression plots and histograms. An
example is shown in Figure 2-5.
Proc. Version,
Site, PI
Figure 2-5: Example extraction items: CSV file of extracted data, descriptive plots and RBG.
2.6.5 Acknowledgements and Proprietary Rights
The MERMAID data policy (http://hermes.acri.fr/mermaid/policy/policy.php) requires that when
MERMAID extractions are used in publications, the Principal Investigators of in situ data (PIs) should
always be contacted for approval, be offered co-authorship and acknowledged. The PIs and their contact
details are listed on the website and in Section 2.1.4.
ACRI-ST and ARGANS should always be acknowledged too, as quality control, post-processing, MERIS
processing, extractions, database system and web facility are proprietary and operated on behalf of ESA.
Appropriate acknowledgement suggestions are made on the data policy page.
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MERMAID Optical Protocols
This section presents the in-situ measurement protocols accompanying datasets supplied to MERMAID,
according to the MERMAID data policy. Also included here are protocols received from PIs from whom
data is expected; updates to this document will occur as new data and protocols are received.
3. MERMAID PROTOCOLS I: SeaPRISM (AERONET-Ocean Color)
3.1 Introduction
The Aerosol Robotic Network (AERONET) has an ocean colour (OC) component (AERONET-OC),
making use of autonomous above water radiometers (SeaPRISM) fixed on platforms located in coastal
regions. The network standardises measurements performed at different sites, with the same
instrumentation and data processing.
Twelve sites exist, of which MERMAID presently has 11 (Figure 3-1; USC_SEAPRISM is not yet
included):
Figure 3-1: AERONET-OC sites in MERMAID.
3.1.1 Products in MERMAID
AERONET-OC provides processed, quality-controlled data accessible online with a specified data policy
(http://aeronet.gsfc.nasa.gov/new_web/ocean_color.html). The products in MERMAID are the normalised
water reflectance, ρwn (λ) as computed from AERONET-OC normalised water-leaving radiance, Lwn (λ),
aerosol optical thickness a (λ) and Chl.
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3.1.2 Standardised measurement and processing procedure
SeaPRISMs are calibrated just before and after each field deployment (generally lasting 6-12 months). On
average, changes of less than 1% have been observed in instrument sensitivity during successive
deployments in 2006 and 2007. Data transmission is made through the METEOSAT meteorological
satellite that ensures almost real-time data handling. Collected data are processed and quality- assured at
the Goddard Space Flight Centre (GSFC) of the National Aeronautics and Space Administration (NASA).
Each SeaPRISM measurement sequence is executed every 30 minutes within ±4 hours around the local
noon, and comprises:
1. A series of direct sun measurements E as a function of λ, solar zenith and azimuth angles
(respectively θ0 and 0) for the determination of the aerosol optical thickness τa (λ), an ancillary
quantity required for the normalisation of water-leaving radiance, Lwn (λ);
2. A sequential set of NT sea-radiance measurements for determining total radiance from the sea, Lt (λ, θ,
) and of Ni sky-radiance measurements for determining the downwelling radiance at ground level,
Lsky (λ, θ′′,), serially repeated for each λ (where θ′′ =π-θ and  is the relative azimuth with respect to
the sun). Lt (λ, θ, ) and Lsky (λ, θ′′, ) values are determined at θ = 40° and  = 90°.
If the sun is cloud covered then E (λ, θ0, 0) measurements cannot be performed and the whole acquisition
sequence is cancelled. The sky and sea measurements for determining Lsky (λ, θ′′, ) and Lt (λ, θ, ) are
performed with Ni = 3 and NT = 11.
The total radiance measured at the uncontaminated sea surface, Lt (λ), is a combination of Lw (λ) plus two
sources of reflected light or glint: the sky and the sun. Sun glint is avoided by pointing the instrument
away from the sun by at least 90° away from the solar plane but not into any perturbations associated with
the platform. Aggressive filtering can be used to remove any glint spikes caused by oblique wave facets
(Hooker et al., 2002; Zibordi et al., 2002). Then, the only quantity needed for retrieval of Lw (λ) from Lt
(λ) is an estimate of the contribution of the sky radiance, Lsky (λ).
Additional measurements are performed at 870 and 1020 nm for quality checks, turbid water flagging,
and for the application of alternative above-water methods (Zibordi et al., 2002).
Data Processing of Lwn (λ)
A set of criteria is defined for the processing of AERONET-OC measurements and determination of Lwn
(λ). Principally, processing is only applied to measurement sequences fulfilling the following criteria
(Zibordi et al., 2009b):
1) there is no missing value;
2) dark values are below a given threshold;
3) measurements are performed with 0 values included within site-dependent limits to minimise
superstructure perturbations in Lt (λ, θ, ,), i.e. tower shading;
4) aerosol optical thickness data have been determined;
5) the wind speed is lower than 15m s-1.
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For each measurement sequence qualified for the data processing, Lsky (λ, θ′′, ) is determined by
averaging the Ni sky-radiance data. Lt (λ, θ, ) is determined from the average of a fixed percent of the NT
sea-radiance measurements exhibiting the lowest radiance levels. This approach has been suggested by
independent studies (Hooker et al., 2002; Zibordi et al., 2002) highlighting the need for an aggressive
filtering of above-water measurements to minimise the perturbing effects of surface roughness in Lt (λ, θ,
).
From Lt (λ, θ, ) and Lsky (λ, θ′′, ), the water-leaving radiance Lw (λ, θ, ), i.e. the radiance emerging from
the sea quantified just above the sea surface, is computed as:
Lw ( , , )  Lt ( , , )   f ( , 0 , , ws ) Lsky ( , ' ' ,  )
(15)
where: ρf (θ, θ0, , ws) is the sea surface reflectance as a function of the measurement geometry identified
by θ, θ0, , and of the sea state expressed through wind speed, ws. The value of ρf (θ, θ0, , ws) at a given θ
and , can be theoretically determined as a function of θ0 and ws (Mobley, 1994).
Normalisation is carried out as part of the AERONET-OC processing scheme which is the same that that
used for MERMAID (and as described in section 1.4.6). For AERONET-OC, normalisation is performed
using F0 and formulations (as in Zibordi et al., 2004) requiring a series of transmittance computations.
The quantity td (λ) used in the AERONET-OC normalisation procedure is computed utilizing τa (λ)
determined from SeaPRISM measurements (the exponent being -0.16 in this instance). The Rayleigh
optical thickness (τray) used for computation of AAOT Rayleigh Transmittances is derived from Bodhaine
et al. (1999), which differs from nominal MERIS usage of Hansen and Travis (1974).
As Es is not available from AERONET-OC website, for the MERMAID pre-matchup processing for
AERONET-OC, Es (needed for computation of ρw_ISME(λ); section 1.4.4) is computed using Gordon and
Wang (1994) approximations and Hansen and Travis (1974) τray (values found in the MERIS RMD).
3.1.3 Quality assurance
All AERONET products are classified at three different quality assurance (QA) levels. Data at Level 1.0
only include Lwn (λ) determined from complete measurement sequences satisfying the basic criteria
addressed in data pre-processing. Level 1.5 Lwn data are derived from Level 1.0 products. Zibordi et al.
(2009b) detail the differences between levels 1.0 and 1.5, but for MERMAID, L2 is used. Fully qualityassured Level 2.0 data refer to Lwn (λ) determined from Level 1.5 products for which:
1) Level 2 aerosol optical thickness data exist;
2) pre- and post-deployment calibration coefficients for LT and Lsky measurements were determined and
exhibit differences smaller than 5%;
3) the Lwn (λ) spectral shapes are shown to be consistent through tests based on statistical approaches;
4) the Lwn (λ) passing all former tests do not exhibit dubious values during a final spectrum-by-spectrum
screening performed by an experienced scientist.
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While most QA tests rely on the application of thresholds, the methodology applied for the assessment of
the spectral consistency makes use of statistical methods effective in detecting artefacts in the shape of
Lwn (λ) spectra (D'Alimonte and Zibordi, 2006). In particular, the applied scheme rejects spectra
exhibiting:
1) low statistical representativeness within the data set itself („self-consistency’ test);
2) anomalous features with respect to a reference set of quality-assured data („relative-consistency’ test).
3.1.4 Uncertainties
Lwn uncertainties (quadrature sum) for AAOT are currently stated by Zibordi et al. (2009b) as 5.1% (421
nm), 4.5% (443), 4.7% (488 nm), 4.7% (551 nm) and 7.8% (667 nm). Zibordi et al. (2009b) go into
further detail on how these values are derived; the quadrature sum percentages are the result of
uncertainties in different contributing terms such as: absolute calibration; sensor sensitivity change
between calibrations; correction applied for removing dependences to the viewing angle and anisotropy of
light field in seawater; determination of Td; determination of ρf due to wave effects and data filtering;
value of ws; environmental effects.
Normalisation of all AERONET-OC data (as described in section 1.4.6) is applied assuming case 1 waters
only, and this is taken into account when defining the uncertainty budget of the normalised data.
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3.2 The Aqua Alta Oceanographic Tower (AAOT). PI: Giuseppe Zibordi
3.2.1 Introduction
The Aqua Alta Oceanographic Tower (AAOT) is part of AERONET-OC, a framework supporting ocean
colour validation activities through standardised radiometric measurements in coastal water (Zibordi et
al., 2009b; Zibordi et al., 2002; Zibordi et al., 2006; Zibordi et al., 2004). The AAOT is located in the
Northern Adriatic Sea (45o 18.51 N, 12o 30.30 E), east of Italy, 8 nautical miles off the coastline of
Venice, and of 17 m depth, and at a site characterised by both Case 1 and Case 2 water types, and of a
mostly continental (sometimes marine) marine aerosol type
3.2.2 Measuring system and configuration
The AAOT (Figure 3-2) consists of four levels. At the fourth level the above-water instrumentation is
positioned, and includes the SeaPRISM system which is an adapted CE-318 autonomous sun-photometer.
The accurate sun-tracking required for SeaPRISM measurements imposes that the deployment platform is
a grounded structure. This structure needs to be at a distance from the mainland suitable to assume that
the adjacency effects are negligible in satellite data (Zibordi et al., 2002).
a)
b)
Figure 3-2: The AAOT structure and instrumentation; a) the main tower and operational levels (from
Hooker
et
al.,
2005),
b)
the
CIMEL
CE-318
(SeaPRISM)
instrument
(from
http://aeronet.gsfc.nasa.gov/new_web/photo_db/Venise.html).
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3.3 Abu Al-Bukhoosh. PI: Giuseppe Zibordi
Abu Al-Bukhoosh is located at 25.49 ºN, 53.15 ºE in the Arabian Gulf. The PI of this site is G. Zibordi.
3.4 CERES Ocean Validation Experiment (COVE_SeaPRISM). PI: B. Holben
The Clouds and the Earth's Radiant Energy System (CERES) experiment is one of the highest priority
scientific satellite instruments developed for NASA's Earth Observing System (EOS). The CERES Ocean
Validation Experiment (COVE) provides continuous world-class measurements at the Chesapeake
Lighthouse for validation of CERES and other satellite products. This instrument site is located on the
Chesapeake Lighthouse ocean platform, a Coast Guard platform located 25 km East of Virginia Beach,
Virginia (Figure 3-3).
COVE is located outside of the surf zone and far enough away from shore to make it an excellent
validation site for space-borne retrievals of cloud and aerosol microphysics. The platform itself is small
(25x25 meters) and aerosol climatology at this location indicates optical depths and Angstrom exponents
that are consistent with polluted urban aerosols. Not all airmasses at Chesapeake Lighthouse are polluted,
however, as Easterly winds from occasional synoptic systems and frequent sea breezes provide a marine
aerosol source.
Instrumentation is located at the housing level and on the roof of the accompanying lookout tower at 37
meters above the surface, and includes the AERONET sunphotometer, uplooking and downlooking
multifilter rotating shadowband radiometers (MFRSRs), as well as pressure, temperature, relative
humidity, global positioning system integrated precipitable water vapor (GPS-IPW), wave height and
period. Much of the current instrumentation has been providing continuous data since March, 2000. A
local area network (LAN) at the facility and a microwave link to shore provide robust digital
communications.
Figure 3-3: COVE SeaPRISM site, 25 km East of Virginia Beach, Virginia: a) site location; b) Lighthouse
platform; c) AERONET sunphotometer.
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3.5 Gloria. PI: G. Zibordi
The Gloria site (Figure 3-4) is an oil platform 12 nautical miles from the Romanian coast in the Black
Sea, south of the Danube plume and north of Constanta (44.56o N; 29.36o E).
Figure 3-4: Gloria Platform, Black Sea.
3.6 Gustav-Dahlen Tower. PI: Giuseppe Zibordi
AERONET-OC station Gustav-Dahlen Tower (GDT) is located in the Northern Baltic Sea, 10 nautical
miles off the Swedish coast, and in an average depth of around 16 m (Figure 3-5 a). This location is at
58.59 ºN, 17.47 ºE. The GDT is owned and managed by the Swedish Maritime Administration and the
AERONET PI of this site is G. Zibordi. In addition to SeaPRISM measurements, marine observations are
carried out 25 nautical miles east of the tower site within the framework of the National Monitoring
Program managed by the Swedish Environmental Protection Agency, which is focused on human impact
on seas and coastal areas, supports monthly monitoring of various environmental parameters including
Chl (Zibordi et al., 2009a).
3.7 Helsinki Lighthouse. PI: Giuseppe Zibordi
The Helsinki Lighthouse (Figure 3-5 b) is owned and managed by the Finnish Maritime Administration,
and located at 59.949° N and 24.926° E, in the Gulf of Finland, and approximately 12 nautical miles
south east of the harbour of Helsinki in an average water depth around 13 m. The PI of this site is also G.
Zibordi. Bio-optical data are also collected close to the tower through autonomous systems operated on
ferries (see Zibordi et al., 2009a and references therein). The Chl-a data included for this site in
MERMAID are determined from regional algorithms; they do not come from field measurements.
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b)
Figure 3-5 a) Gustav-Dahlen Tower in the northern Baltic Proper. The inset is a picture of the SeaPRISM
autonomous radiometer installed on the tower; b) The Helsinki Lighthouse in the Gulf of Finland.
3.8 Long Island Sound Coastal Observatory (LISCO). PI: S. Ahmed, A. Gilerson
The LISCO site (Figure 3-6) is situated in Western Long Island Sound, 2 miles offshore (40.95o N; 73.34o
E).
Figure 3-6: LISCO site, Long Island Sound.
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3.9 Lucinda Jetty Coastal Observatory (LJCO). PI: V. Brando
The Lucinda Jetty Coastal Observatory (LJCO, Figure 3-7) is located on the end of the 5.8 km long
Lucinda Jetty (18.52 S, 146.39 E) in the coastal waters of the Great Barrier Reef World Heritage Area
close to the Herbert River Estuary and the Hinchinbrook Channel. It is operated by CSIRO.
Two different data streams are acquired: above water measurements of the water radiance and in water
measurements of the optical properties. A CIMEL SeaPRISM and Satlantic HyperOCR are used for each
type of measurement, respectively. An in situ water optical package is also deployed to measure:

Conductivity, temperature, pressure, dissolved oxygen, chlorophyll fluorescence and turbidity
(WETLabs WQM);

Coloured dissolved organic matter fluorescence (WETLabs WETStar fluorometer);

Particulate and dissolved absorption and attenuation spectral coefficients (WETLabs ac-s);

Total backscattering coefficients (WETLabs BB9).
All instruments were commissioned on 28 October 2009.
The data acquisition is managed with a Data Acquisition and Power Conditioning System (DAPCS)
developed by WETLabs. The DAPCS is specifically designed to enable high speed/bandwidth
communications and power control to support data collection from a broad suite of environmental
sampling instruments.
Data is acquired in real time by the Linux Server and PC installed on site. The raw data-stream is
uploaded via broadband to CSIRO‟s data storage in Canberra where is pre-processed and QA/QC-ed.
Figure 3-7: LJCO site, Eastern Australia. Images from: http://imos.org.au/ljco.html
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3.10 Martha’s Vineyard Coastal Observatory (MVCO). PI: H. Feng
Among other facilities, Martha‟s Vineyard Coastal Observatory (MVCO) includes a tower 3 km from
shore and in 15 m depth, with a mounted SeaPRISM contributing to the AERONET objectives for this
region. Janet Fredericks is the MVCO manager and Hui Feng the PI of the SeaPRISM operation.
Figure 3-8: The tower at MVCO
3.11 Pålgrunden Lighthouse, Lake Vänern. PI: Susanne Kratzer
The SeaPRISM instrument is placed on a lighthouse platform („Pålgrunden‟ Lighthouse) in Lake Vänern,
Sweden (Figure 3-9), 58.76 ºN, 13.15 ºE, about 2 miles north of the town of Granvik, Lake Vänern. The
PI of this site is Susanne Kratzer, from Stockholm University, Sweden, but the managing organisation is
the Swedish National Maritime Administration. Pålgrunden Lighthouse stands at 30 m in height. This
CIMEL was previously deployed at the Swedish Meteorological and Hydrological Institute (SMHI),
Norrköping (AERONET station number 194), and prior to deployment at Pålgrunden the filters were
changed to 412, 443, 488, 551, 667, 870, 1020 nm.
Figure 3-9: The Pålgrunden lighthouse SeaPRISM platform in Lake Vänern, Sweden.
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3.12 WAVE_CIS_Site_CSI_6. PI: B. Gibson, A. Weidermann
The WAVE_CIS site is located on the roof of ST52B Quarters Platform (Figure 3-10a). This is part of a
triple oil rig platform in which the other two structures make up the production platforms.
Figure 3-10: WAVE_CIS_Site_CSI_6. a) Platform; b) Instrumentation
3.13 AERONET-OC Key References
Bodhaine, B. A., Wood, N. B., Dutton, E. G. &Slusser, J. R. (1999). On Rayleigh Optical Depth
Calculations. Journal of Atmospheric and Oceanic Technology 16: 1854-1861.
D'Alimonte, D. & Zibordi, G. (2006). Statistical Assessment of Radiometric Measurements From
Autonomous Systems. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 44(3): 719728.
Hooker, S. B., Lazin, G., Zibordi, G. & McClean, S. (2002). An evaluation of above- and in-water
methods for determining water leaving radiances. Journal of Atmospheric and Oceanic Technology 19:
486-515.
Mobley, C. D. (1999). Estimation of the remote-sensing reflectance from above-surface measurements.
Applied Optics 38: 7442-7455.
Morel, A., Voss, K. J. & Gentilli, B. (1995). Bidirectional Reflectance of Oceanic Waters: A Comparison
of Modeled and Measured Upward Radiance Fields. Journal of Geophysical Research 100: 13143-13150.
Morel, A., Antoine, D. & Gentilli, B. (2002). Bidirectional reflectance of oceanic waters: accounting for
Raman emission and varying particle scattering phase function. Applied Optics 41(30): 6289-6306.
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Morel, A. & Gentilli, B. (1993). Diffuse reflectance of oceanic waters. 2. Bidirectional aspects. Applied
Optics 32: 6864-6872.
Morel, A. & Gentilli, B. (1996). Diffuse Reflectance of Oceanic Waters. 3. Implications of
Bidirectionality for the Remote-Sensing Problem. Applied Optics 35: 4850-4862.
Zibordi, G., Hooker, S. B., Berthon, J.-F. & D'Alimonte, D. (2002). Autonomous above water radiance
measurements from stable platforms. Journal of Atmospheric and Oceanic Technology 19: 808-819.
Zibordi, G., Mélin, F. & Berthon, J.-F. (2006). Comparison of SeaWiFS, MODIS and MERIS
Radiometric Products at a Coastal Site. . Geophysical Research Letters 33: L06617.
Zibordi, G., Holben, B., Slutsker, I., Giles, D., D'Alimonte, D., Mélin, F., Berthon, J.-F., Vandemark, D.,
Feng, H., Schuster, G., Fabbri, B. E., Kaitala, S. & Seppälä, J. (2009b). AERONET-OC: a network for
the validation of Ocean Color primary radiometric products. Journal of Oceanic and Atmospheric
Technology (Accepted): 57.
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4. MERMAID PROTOCOLS II: Portable Radiometers
4.1 SIMBADA. PI: Pierre-Yves Deschamps.
4.1.1 Introduction
This protocol comes from the User Manual on the SIMBADA website (http://www-loa.univlille1.fr/recherche/ocean_color/src/); there is no publication available although those interested may refer
to Deschamps et al., (2004) for information about an earlier version of the dataset, SIMBAD, for which
the processing and instrument configuration is very similar. This protocol is concerned only with
SIMBADA. SIMBAD had only five spectral bands; this dataset has 11 spectral channels. There is a slight
overlap with NOMAD, due to an alternative processing scheme used by Robert Frouin for NASA of some
of the SIMBADA data for NOMAD. The quality of the processed data is presumed to be the same (Pers.
Comm: P-Y Deschamps, 13th November 2008). The duplicates discovered when formatting for
MERMAID were kept.
4.1.2 Measuring system and configuration
The SIMBADA instrument is an above-water radiometer designed and manufactured by the Laboratoire
d'Optique Atmosphérique (LOA) of the University of Lille, France. It measures both water-leaving
radiance and aerosol optical thickness in 11 spectral bands (each bandwidth of 10 nm), centred at 350,
380, 412, 443, 490, 510, 565, 620, 670, 750, and 870 nm, (see
Figure 4-1) by viewing the sun (sun-viewing mode) and the ocean surface (sea-viewing mode)
sequentially. The same optics, with a field-of-view of about 3°, the same interference filters, and the same
detectors are used in both ocean-viewing and sun-viewing mode. A different electronic gain, high and
low, is used for each mode, respectively. The optics are fitted with a vertical polariser, to reduce reflected
skylight when the instrument is operated in ocean-viewing mode. Pressure, temperature, and viewing
angles are also acquired automatically. Attached in the front of the instrument, a GPS antenna acquires
automatically the geographic location at the time of measurement and a display indicates various
information.
4.1.3 Measurement Protocol
The SIMBADA radiometer measures direct sunlight intensity by viewing the sun, and water-leaving
radiance by viewing the ocean surface at 45° from nadir and 135° from the sun's vertical plane. It is
powered by batteries, which allow about 8 hours of continuous use.
Measurements have to be made in clear sky conditions (<2/8 of clouds and not obscuring the sun disk),
outside the glitter region (relative angle between solar and viewing directions of 135°), and at a nadir
angle of about 45°. For those angles, reflected skylight is minimised as well as residual ocean polarisation
effects. The measurements can be made on a steaming ship; there is no need to stop the ship to make
measurements. To normalise water-leaving radiance, incident solar irradiance is not measured, but
computed using the aerosol optical thickness data. The operator can select, in addition to ocean-viewing
and sun-viewing modes, dark current and calibration modes. Each series of measurements lasts 10
seconds. Frequency of measurements is about 8 Hz.
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Figure 4-1: Spectral channels of the SIMBADA instrument
The experimental procedure is to make, consecutively, one dark measurement, three sun measurements,
three sea measurements, three sun measurements, and one dark measurement.

DARK mode: Cardboard is placed at the end of collimator and/or dark cloth, so that no light can
enter the instrument. The measurement lasts 10 seconds.

SUN mode: The instrument is aimed at the sun, and the measurement lasts about 10 seconds. A
beep indicates the end of the measurement. The sun's azimuthal angle is stored in memory.

SEA mode: Measurement is made at the side of the ship and aimed at the ocean, after having
positioned the instrument at 135° from the sun's vertical plane by using the relative azimuthal
angle from the sun's vertical plane displayed on the top middle and after having positioned the
instrument at nadir angle of 45°. The measurement lasts 10 seconds. To avoid viewing the ship
trail or foamy sea, it is better to scan continuously the sea between 30° and 60°. It is important the
tilt is not more than about 20°, so that the polariser remains in a suitable position.
The SIMBADA measurements should be made during daytime, when the sun disk is not obscured by
clouds, outside foam and whitecaps. Ideally, weather permitting, the measurements should be made 1) at
each station during daytime (if the ship stops offshore), and 2) while the ship is moving around local noon
(time of SeaWiFS overpass). The best ship location to make the measurements is the bow. Since
SIMBADA does not like sea water, "en route" measurements should be made only when there is no risk
of wetting the instrument.
The following meteorological data should be acquired concomitantly, whenever possible: date, time,
latitude, longitude., cloud cover and type, air temperature, dew point (or wet bulb) temperature, surface
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pressure, visibility, wind speed, wind direction, whitecaps (none, low, moderate, or high), water
temperature, surface Chl, phaeophytin, etc. Some of these data may be available from the bridge log.
Radiometric Calibration
In the following equations the numerical count for Sun and sea measurements, CN, is considered to be
corrected for dark current. The dark-current count, therefore, is omitted for clarity. These two
measurements require different calibration methods, which are described below.
Sun-Viewing Mode
The instrument in sun-viewing mode is calibrated by use of the Bouguer–Langley method: measuring the
sun intensity through a stable atmosphere as a function of air mass and extrapolating the measurements to
zero air mass. After passing through the atmosphere, the Sun intensity (irradiance) in each spectral band
can be expressed as:
I ( , s )  Fo ( ) d 2 exp[  ( )m( s )]
(16)
Where τ (λ) is the total optical thickness of the atmosphere (assumed to be constant during the
calibration), m is the air mass, and d is the corrective factor for the sun-Earth distance. The F0 (λ) values
are obtained from Thuillier et al. (2003), (formerly Neckel and Labs, 1984), m is computed as a function
of θs following Kasten and Young (1989), and d is computed according to Paltridge and Platt (1977).
Equation (16) is valid only in the absence of absorption by water vapour and minor gases.
Sea-Viewing Mode
The instrument in sea-viewing mode is calibrated by use of an integrating sphere, whose output spectral
radiance is calibrated with equipment and methods that are traceable to the National Institute of Standards
and Technology and that are further controlled in radiometric inter-comparison activities. The equivalent
radiance of the sphere in each band, L, is first computed as follows:
L( )  [  L( )R( )d ] /[  R( )d ]

(17)

Where λ is wavelength, L is the radiance delivered by the sphere, R is the spectral response of the
SIMBAD instrument, and the integral is over the spectral range of each band. The calibration coefficients
(k) are computed from L and the digital counts (CN).
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Aerosol Optical Thickness and Angstrom Coefficient
Aerosol optical thickness from the measurements in sun-viewing mode is deduced from the total optical
thickness of the atmosphere τa (λ) (computed from the digital counts, m and θs). τa (λ), is then corrected
for molecular scattering and gaseous absorption, due mostly to ozone. This gives the aerosol optical
thickness in each band, τa (λ), as;
 a ( )   ( )   ray ( , P0 )  O3 ( , uO3 )
(18)
Where τray (λ) and τO3 (λ) are the Rayleigh and ozone optical thickness in band λ, respectively. The τray
(λ) depends on surface air pressure, P0. It is computed by use of a depolarisation factor of 0.0279. The
ozone contribution is computed from the vertically integrated ozone amount, uO3, obtained from
climatology (Keating et al., 1989) or derived from Total Ozone Mapping Scanner (TOMS) observations.
The Angstrom coefficient, α, defined by the law τa (λ) ≈ λ-α , is determined by regressing on a log–log
scale τa (λ) versus the equivalent wavelength of a band, λ, by using the instrument‟s five spectral bands.
The determination of α is more difficult at low-aerosol optical thickness simply because the uncertainty
on τa (λ) is rather constant in absolute value but becomes increasingly large in relative value as τa (λ)
decreases.
Total Atmospheric Transmittance (downwelling)
The total (i.e. direct plus diffuse) downwelling atmospheric transmittance, Td (λ), must be estimated to
normalise the water-leaving radiance measurements into reflectance, ρw (λ). It is expressed as the product
of the transmittance due to gaseous absorption, mostly of ozone, TO3 (λ), and the transmittance due to
molecular (Tray (λ)) and aerosol scattering (including aerosol absorption), Ta (λ).
Td (λ) is computed by use of a radiative transfer model based on the successive orders of scattering
method (Deuzé et al., 1989) with θs, τray, and τa as variable input (where „ray‟ denotes „Rayleigh‟). The
effect of aerosol type is small and can be neglected.
Marine Reflectance
Because the variable of interest is diffuse marine reflectance (Equation 20), the polarised ρw (λ) measured
by viewing the surface (sea-viewing mode), is obtained from the recorded numerical count (CN) by using
the following formula:
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 k( ) CN( ) d 2
 w ( ) =
F0 ( ) cos( s )
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(19)
ρw should be measured in a specific viewing geometry, i.e., at a nadir angle of 45° and at an azimuth angle
of 135° with respect to the sun, in order to minimise skylight reflection effects. The inclinometer and
magnetometer angles are used to select the optimum viewing geometry. Measurements made at a nadir
angle outside the range 45° ± 5° and at a relative azimuth angle outside the range 135° ± 10° are not
processed. The reflectance ρw is then corrected for residual skylight and atmospheric transmittance to
yield the vertically polarised diffuse water reflectance, ρw‟:
 w ( )' =  w ( ) -  o ( )/Td ( )
(20)
Where ρo (λ) is the reflectance due to skylight reflection. This reflectance is computed accurately from the
τray (λ), τa (λ) and type (i.e. α), and the surface wind speed, according to Fougnie et al. (1999).
The radiometric measurements might be contaminated by whitecaps caused by wind action on the surface
or by foam and bubbles generated by the ship or by residual glitter. Sunlight scattered by clouds may also
be reflected by the surface in the instrument‟s field of view. Thresholds on ρw(865) are applied to
eliminate the most perturbed measurements, and then ρw at the other bands are iteratively corrected for,
making the assumption that extra reflectance due to whitecaps, clouds, etc., does not depend on
wavelength in the spectral range 443–870 nm. Thus only ρw‟ in spectral bands 1–4, i.e. the bands centered
at 443, 490, 560, and 670 nm, respectively, is obtained after correction. Equation (20) can be applied
effectively because the radiometric measurements are acquired simultaneously in the instrument‟s five
spectral bands (cloud effects strongly depend on surface-wave slope, and whitecaps may be changing
quickly with time). However, treating whitecaps as gray bodies even though they are not white spectrally
(Fougnie and Deschamps, 1997; Frouin et al., 1996; Nicolas et al., 2001) is sufficient because only the
less-perturbed measurements are selected. Over turbid coastal waters, the diffuse reflectance is not null at
870 nm; consequently, this correction is not valid for those waters.
Molecules and hydrosols polarise the light scattered by the water body. Because SIMBADA
measurements are made through a vertical polariser, polarisation effects must be corrected to yield the
total ρw.
Reprocessing to MERIS bands
The SIMBADA data were reprocessed in July 2009; they were spectrally convolved with the MERIS
band filters, and converted into reflectances using extraterrestrial solar irradiances from the Thuillier
(2003) database as recommended by the QWG (no longer the Neckel and Labs, 1984 values).
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4.1.4 Uncertainties
TBD
4.1.5 Key References
Deuzé, J.-L., Herman, M. & Santer, R. (1989). Fourier series expansion of the transfer equation in the
atmosphere–ocean system. Journal of Quantitative Spectroscopy and Radiative Transfer 41: 483-494.
Deschamps, P.-Y., Fougnie, B., Frouin, R., Lecomte, P. &Verwaerde (2004). SIMBAD: A Field
Radiometer for Satellite Ocean-Color Validation. Applied Optics 43(20): 4055-4069.
Fougnie, B. & Deschamps, P.-Y. (1997).Observation et mode´lisation de la signature spectrale de
l‟e´cume de mer. In Proceedings of the 7th International Colloquium on Physical Measurements and
Signatures in Remote Sensing, Vol. 1, 227-234 (Eds G. Guyot and T. Phulpin). Rotterdam.
Fougnie, B., Frouin, R., Lecomte, P. & Deschamps, P.-Y. (1999). Reduction of skylight reflection effects
in the above-water measurements of diffuse marine reflectance. Applied Optics 38: 3844-6856.
Frouin, R., Schwindling, M. & Deschamps, P.-Y. (1996). Spectral reflectance of sea foam in the visible
and near-infrared: insitu measurements and remote sensing implications. Journal of Geophysical
Research 101: 14361-14371.
Kasten, F. & Young, A. T. (1989). Revised optical air mass tables and approximation formula. Applied
Optics 28: 4735-4768.
Keating, G., Pitts, M. C. & Young, D.-F. (1989).Improved reference models for middle atmosphere ozone
_New CIRA_. In Middle Atmosphere Program Handbook for MAP, Vol. 31, 37-49 (Ed G. Keating).
Urbana, Illinois: Scientific Committee on Solar-Terrestrial Physics Secretariat, University. of Illinois.
Neckel, H. & Labs, D. (1984). The solar radiation between 3300 and 12500 Å. Solar Physics 90: 205–
258.
Nicolas, J.-M., Deschampes, P.-Y. & Frouin, R. (2001). Spectral reflectance of oceanic whitecaps in the
visible and near infrared: aircraft measurements over open ocean. Geophysical Research Letters 28:
4445–4448
Paltridge, G. W. & Platt, C. M. R. (1977).Radiative processes in meteorology and climatology. In
Development in Atmospheric Science New York: Eslevier.
Thuillier, G., Hersé, M., Labs, D., Foujols, T., Peetermans, W., D., G., Simon, P. C. & Mandel, H. (2003).
The solar spectral irradiance from 200 to 2400 nm as measured by the SOLSPEC spectrometre from the
ATLAS and EURECA missions. Solar Physics 214: 1-22.
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5. MERMAID PROTOCOLS III: TACCS
5.1 North West Baltic Sea. PI: Susanne Kratzer
5.1.1 Measuring systems
The Tethered Attenuation Coefficient Chain Sensor (TACCS 09, Satlantic Inc., Canada,
http://www.satlantic.com/) is a multi-channel radiometer including 7 channels (SeaWiFS + 620 nm) for
upwelling radiance (Lu: 412, 443, 490, 510, 555, 620 and 670 nm; seen in Figure 5-1a), 3 channels for
downwelling irradiance above the surface (443, 491, and 670 nm; seen in Figure 5-1b). The spectral
attenuation coefficient, Kd (490) can be estimated from a chain of four sensors for Ed (0+, λ) at 490 nm, Ed
(490). The Ed (490) sensors are fixed on a cable at 2, 4, 6 and 8 m depth (Kd (490) chain). The natural
logarithm of the measured Ed (0+, λ) is plotted against depth and the slope of the line taken as Kd (490).
All channels have a bandwidth of 10 nm. Note that when the TACCS was deployed in the water, as
delivered by the manufacture in 2000, the instrument was not sitting straight in the water. Extensive trials
had to be made with adding on additional diving weights close to the bottom of the instrument in order to
make it look straight up to the sky, and also in order to make it more stable and more resistant to wave
movements. 2008, the Lu channel at 555 nm was exchanged to 560 nm (the instrument was initially built
for sea-truthing of SeaWiFS). When the instrument was acquired in 2000 the 620 nm channel was chosen
to have one additional channel matching MERIS, and because this band may be influenced by
phycocyanin from cyanobacteria.
The TACCS was deployed in the Himmerfjärden, North West Baltic Sea during three campaigns during
August 2002, July 2008 and May 2010. The stations of deployment in 2002 are shown in
Figure 5-2, and the Associate Professor Susanne Kratzer from Stockholm University, Sweden, is the PI
(seen deploying the TACCS in Figure 5-1).
Figure 5-1: The TACCS instrumentation rig. a) the in-water
instrumentation shown being deployed by PI Susanne Kratzer,
and b) the above-water Ed sensor.
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STP
STP
MERIS FR, 300 m
Askö
H5
H4
H3
H2
B1
MERIS RR, 1.2 km
Figure 5-2: Himmerfjärden area, NW Baltic Sea. Note that stations B1 and H2 do not differ optically from
the open sea station (Kratzer et al., 2008). STP: sewage treatment plant at the head of Himmerfjärden close to
station H5.
In order to derive reflectance from the TACCS, spectral Kd must be modelled. This we can do with AC9
data measured at the same time. The AC9 plus (WETLabs), is a state-of-the-art instrument to measure
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spectral attenuation and absorption in nine channels, from which spectral scattering can be derived. It is
also fitted with a CTD and an ECO VSF3, a volume scattering function metre, which is used to derive
backscatter. If measured AC9 data is not measured at the specific station the spectral slopes published in
Kratzer et al. (2008) can be used. Measurements were made with the AC9 in 2002, 2008 and 2010, but
for the present time, the AC9 data from 2008 and 2010 have not yet been processed. Table 5-2 shows the
spectral slopes for the north-western Baltic Sea (summer months 2001-2002), categorised into coastal and
open sea data, and used for the processing of the 2008 TACCS data included in MERMAID. Kratzer et
al. 2008 describe the division into coastal and open sea data. The data will be updated at a later time, as
the AC9 processed data becomes available.
Table 5-1: General sensor specifications of the TACCS 09
In-air
In-water
Es
downwelling irradiance
sensor
Sensor Model
Lu
upwelling radiance
sensor
Ed
downwelling irradiance
(K-chain) sensor
ED-50
OCR-100
ED-20
cosine response
10o (0.025 steradians) in
water
cosine response
Spatial Characteristics
Field of view
4.78 mm diameter
Entrance aperture
Collector area
86.0 mm2
86 mm2
Detectors
Custom 13 mm2 silicon photodiodes
Spectral Characteristics
Wavelength range
443-670 nm
400-700 nm
Number of channels
3
7
1
Spectral bandwidth
10 nm
10 nm
10 nm
Filter type
Custom low fluorescence interference
Discrete
wavelengths(centers)
443, 490, 670 nm
412, 443, 490, 410, 560, 490 nm
670, 620 nm
10-4
10-4
Optical characteristics
Out of band rejection
5x10-4
Out of field rejection
Cosine response
10-4
within 3% 0 -60o
within 10% 60-89o
Temporal characteristics NA
within 3% 0 -60o
within 10% 60-89o
NA
NA
System time constant
0.015 seconds
0.015 seconds
0.015 seconds
-3dB frequency
10 Hz
10 Hz
10 Hz
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Table 5-2: Mean slope factors to derive spectral Kd for all TACCS channels from Kd490 in the north-western
Baltic Sea during summer (Kratzer et al., 2008) derived from AC9 data that was measured during field
campaigns in June 2001, August 2002 and July 2008 (Kratzer and Tett, 2009, Kratzer and Vinterhav 2010).
The data set was divided up into I) outer fjord & open sea stations (B1-BY31 & H2), and II) inner fjord
stations (H3-H4).
TACCS
Band
Slope factors,
outer stations,
B1-BY31 & H2
Slope factors,
inner fjord,
H3-H4
Wavelength (λ)
Mean
St. Dev.
Mean
St. Dev.
412
443
490
510
555
620
670
2.424
1.673
1.000
0.838
0.652
1.110
1.611
0.17
0.08
0.00
0.03
0.05
0.06
0.11
2.043
1.502
1.000
0.878
0.713
0.930
1.204
0.10
0.04
0.00
0.01
0.03
0.06
0.11
5.1.2 Measurement Protocols
System units and software
A power/telemetry cable runs from a deck unit, MDU-100, to the TACCS instrument. The deck unit is
connected to a 12V-battery and a computer; thus serves as a power source to the TACCS and as a RS-422
to RS-232 level converter for data transmission. The computer runs the acquisition software for raw data
logging and display, SatView version 2.9.2 from Satlantic, and complements the data acquisition with a
GPS with NMEA data stream (RS232) connected to the computer to fix the location and GPS-GMT time
of the cast. At each station, the instrument was set to sample for 2 minutes at a rate of 1 sample per
second, having first been allowed to float 10-20 m away from the boat in order to avoid shading, and
having allowed the instrument to adjust to the surrounding water temperature for at 10 min. The data was
converted from binary to calibrated engineering units using the Satlantic SatCon software. In order to
derive reflectance from the TACCS data, the spectral shape of the diffuse attenuation must be derived,
given that only a measure of Kd (490) derived from the Kd chain was available. This was done by using
AC9 data measured during 2001-2002 (Kratzer et al., 2008).
5.1.3 Data Processing
The AC9 data was corrected for salinity and temperature, and processed according to WETLabs method 2
(Wetlabs, 2009), which assumes that the scattering correction is a fixed proportion of the scattering
coefficient . Spectral scattering, b (λ), was derived as difference between spectral beam attenuation, c (λ)
and spectral absorption, a (λ), for all AC9 channels, i.e. 412 nm, 440 nm, 488 nm, 510 nm, 532 nm, 555
nm, 630 nm, 676 nm, and 715 nm. For deriving spectral Kd, a (λ) and b (λ) were first derived at TACCS
channels by linear interpolation between the AC9 channels (TACCS channel at 443 nm, 488 nm, 630 nm,
and 676 nm). The following algorithm from Kirk (1994) was then used to estimate spectral Kd:
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1
K d ( )  0 (a( ) 2  ( g1 0  g 2 ) a( ) b( ) ) 0.5
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(21)
Where the mean cosine of the refracted solar beam just below the surface µ o= 0.86 is assumed; and the
constants g1= 0.425 and g2= 0.19.
The data set was divided into i) outer fjord & open sea stations (B1-BY31 & H2), and ii) inner fjord
stations (H3-H4). The reflectance, ρw, was estimated from the TACCS radiometer in the following way:
The upwelling radiance, Lu, just below the surfaces was estimated from Lu at 50 cm depth by propagating
each reading to the surface using the estimated Kd values for each radiance channel. The radiance above
the surface was derived from the Lu below the surface by multiplying the radiance values with the factors
provided in the NASA protocols (Mueller and Austin, 1995). Then, ρw was estimated according to
Equation (3).
5.1.4 Deployment from AAOT and processing
The following description of uncertainties is based on a field inter-comparison and validation of in-water
radiometer and sun photometers for MERIS validation in Portugal during February 2010 (Moore et al.,
2011) and on the MVT intercalibration during the Arc2010 in July 2010.
The TACCS was secured to the AAOT (see Section 3.2) via the power/telemetry cable, and to reduce the
strain on the electrical connection during sampling and recovering phase of the instrument (note there is a
deployment cable strengthening the power/telemetry cable). The instrument was taken 30 meters from the
AAOT location by a zodiac to avoid shading effects from the tower. The TACCS was deployed by first
lowering the k-chain carefully into the water, followed by the buoy. Careful measures were taken to avoid
splashing of water onto the Es sensor during instrument deployment. After the buoy is deployed, the
instrument is allowed to drift up to 40 m away from the AAOT and to acclimatize to the surrounding
water temperature for 10 minutes before the acquisition software is started.
At the beginning of a station, the station name and position were input into the station log file and the file
was named accordingly using the PC-time stamp as sequential file order. Handwritten field notes were
taken regarding the visible sea state and sky conditions and any visible behaviour of the instrument in the
water (buoyancy above/below normal, extreme tilt, etc). The SatView software was programmed to
continuously log all casts for each station at a rate of 1 sample per second during 3 minutes with one
minute pause between each log. Dark readings were taken on deck immediately after recovery, to
minimize temperature dependent effects onto the dark readings. The instrument was deployed and
operated by two people, and each deployment took approximately 15-20 minutes per station.
Data processing
The raw binary log files were converted into calibrated physical units, using the calibration file of the
ARC2010 inter-calibration experiment. The data conversion program used was SatCon v1.5 from
Satlantic. A fixed location of the AAOT (Latitude =45.3139o N, Longitude=12.5083o E) was used as
location of the TACCS during all stations. It was assumed that within a radius of 40 meters the TACCS is
measuring the same water body as the WiSPER (Wire Stabilized Profiling Environmental Radiometer),
and that the water column around the AAOT is vertically homogeneous in order to derive the spectral
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shape of the diffuse attenuation. A type B uncertainty of 1% is assumed due to the relative position of the
TACCS from the AAOT.
The mean time between the start and the end time of the cast were used as a reference time for intercomparison with the TACCS logs. The acquired radiometric quantities (in physical units) at time t, Lu (λ,
t), Ed (490, z, t) and Es (λ, t) were visually screened for stability over time series (spikes and records
indicating instrument error are removed). If extreme noise or a high count of errors were found the
TACCS log was discarded. This was in the case of WiSPER cast v950603, when the instrument had been
taken out of the water to compensate buoyancy/tilt effects by adding 1.5 kg of extra weight to the buoy.
The robust-mean estimate -H15 (AMC, 1989) was calculated both for light and dark measurements of the
acquired radiometric quantities and then dark correction was applied. The TACCS data processing has
been summarized by Moore et al. (2011). In order to obtain Kd (490) and Ed (490, 0-) a log linear
regression was applied to the four Ed (490,z). The Ed (490, 0+) is estimated by propagating Ed (490,0-) up
to the surface according to:
Ed (490,0  )  Ed (490,0  ) factored _ eu
Where:
(22)
factored _ eu  f (sea state, ,  w490,  )
(23)
The predicted relationship between KLu (490,0-) and Kd (490,0+) at the depth of the Lu sensor and the four
k-chain depths was modeled using Hydrolight, and the uncertainty was found to be in the order of 1%,
depending on water type. The Kd spectrum is calculated from the AC9 data, according to Kirk (1994) as
mentioned above (Equation 21). To extrapolate the subsurface Lu(λ) at 0.5m to Lu(λ,0-), first Kd (λ) is
normalized by Kd (490):
K d _ norm 
K d (490)
K d ( )
(24)
According to Moore et al. (2011), it is assumed that to the first order the diffuse attenuation coefficient,
KLu (λ), is equal to Kd (λ), thus:
Lu ( ,0  ) 
Lu ( ,0.5m)
e
0.5 K d _ norm
Lu (λ,0+) is estimated from a surface interface term without taking into account the wind speed that is
dependent on the refractive index of water (Moore et al., 2011). Self-shading corrections are applied to
the Lu (λ,0+) according to NASA protocols (Mueller, 2003a).
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The Es (λ) spectrum is calculated by deriving the spectral shape of an interpolated irradiance model, Emod
(λ), from a modified Gregg and Carder (1990) model, with an uncertainty of 1%. The Es (λ) is normalized
to the Es (490) to correct for tilt and roll:
Es (490,0  )
Es ( ) chain 
E s ( )
Es (490)
Uncertainties assessment
The TACCS assessment of uncertainties is described in Moore et al. (2011). During the Arc2010 an
uncertainty of 10% is assumed from the fact that only one AC9 cast per station is used to derive the Kd
spectrum, thus it is assumed that the derived Kd spectrum is constant during all casts for each station.
Another source of uncertainty may be caused by using the AERONET Level 1.5. Real Time Cloud
Screened data, where the solar azimuth angle is used among other variables as reference for TACCS
calculations. It was found that the median time difference is about 03:39 minutes, the average time
difference is 05:40 minutes with standard deviation of 06:50 and a maximum time difference of 31:05
minutes. An additional uncertainty of 10% is assumed for using the AERONET data and a 2% uncertainty
due to the TACCS measurement off-set from the WiSPER time. Note that during standard TACCS
deployments a one to one relation with the AC9 cast is expected. When the AC9 data is not available,
published spectral slopes published can be used (Appendix 1). The Percentage of the difference between
the calculated Es (λ), Es (λ)chain and Es(mod) from Gregg and Carder (1990) are given in Table 5-3.
Table 5-3: Percent uncertainties for TACCS Lu (lamda,0+).
educated guess
Source
1
Moore, et al. (2011), 2Type B uncertainty:
Value
measured (%)
K-chain_lamda
measured (%)
other_wavelengths
Source
K-chain, sensor position error (m)
0.01
0.004
0.005
1
K-chain, float offset (m)
0.01
0
0
1
K-chain, Ed Radiometric Error (%)
3
0.09
0.12
1
Lu absolute error (%)
3
1.5
1.5
1
Lu position error (m)
0.02
0.3
0.4
1
Es, relative spectral error (%)
2
0
0
1
Kd spectral estimate (%) from AC9
10
0
1.05
1
TACCS time offset from AERONET closest
time to WiSPER time (%)
10
1
1
2
TACCS time offset from WiSPER time (%)
2
0.5
0.5
2
TACCS GPS location (%)
1
0.5
0.5
2
2
2
1
5.89
7.08
Hydrolight bio-optical assumptions
OVERALL
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5.1.5 Key References
AMC (1989). Robust Statistics - How Not to Reject Outliers, Part 1: Basic Concepts. Analyst 114: 16831697.
Gregg, W. &Carder, K. L. (1990). A simple spectral solar irradiance model for cloudless maritime
atmospheres. Limnology and Oceanography 35: 1657-1675.
Kirk, J. T. O. (1994). Light and Photosynthesis in Aquatic Ecosystems (Second Edition). Cambridge
University Press.
Moore, G. F., Icely, J. I. &Kratzer, S. (2011).Field Intercomparison and Validation of In-water
Radiometer and Sun Photometers for MERIS Validation. In ESA Living Planet Symposium,
Special Publication SP-686. In press.
Mueller, J. L. &Austin, R. W. (1995).Ocean Optics Protocols for SeaWiFS Validation, Revision 1. In
NASA Tech. Memo., Vol. 25(Eds S. B. Hooker, E. R. Firestone and J. Acker). Greenbelt,
Maryland: NASA Goddard Space Flight Center.
Mueller, J. L. (2003a).Chapter 6: Shadow Corrections to In-Water Welled Radiance Measurements: A
Review. In Ocean Optics Protocols For Satellite Ocean Color Sensor Validation, Vol. Revision
5, 32 (Eds J. L. Mueller, G. Fargion and C. McClain). Greenbelt, Maryland: NASA GSFC.
Werdell, P. J., Bailey, S. W., Fargion, G., Pietras, C. M., Knobelspiesse, K., Feldman, G. C. &al., e.
(2003). Unique data repository facilitates ocean color satellite validation. EOS Transactions
84(3): 379.
Wetlabs (2009).ac Meter Protocol Document. http://www.wetlabs.com/products/pub/ac9/acproto.pdf.
5.2 Sagres, Algarve. PI: John Icely
5.2.1 Introduction
The Portuguese team on the ESA MVT have started validation measurements at a study site off Cape
Sagres on the south-west coast of Portugal (Figure 5-3). This region has distinct winter and summer
oceanic conditions that reflect the large scale wind patterns induced by Meridional displacements of the
Azores High (Relvas, 1999). Spectra were measured of water reflectance, w(), along a transect
perpendicular to the coast that includes both coastal and oceanic sites (A,B, C in Figure 5-3). These data
have been used by Cristina et al. (2009) to validate MERIS satellite products for both Case 1 and Case 2
water which can then be used to optimise current algorithms relating in-situ to remote sensing data. The
data have been provided to MERMAID for matchup to MERIS RR, according to MERMAID protocols.
The principle reference for these data is Cristina et al. (2009) from which this information is taken.
5.2.2 Measuring system and measurement Protocol
Sampling campaigns for the validation of MERIS data products occurred on 8 September; 4, 13 and 26
October and on the 8 and 17 November 2008 to coincide with the passage of the ENVISAT satellite every
three days over the Iberian Peninsula. The online EOLI-SA programme and the offline ESA catalogues
were used to predict the dates and passage times of ENVISAT, but field campaigns were generally
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restricted to days when meteorological sites predicted clear skies and relatively calm sea conditions.
Figure 5-3 shows the approximate locations off the coastline at Cape Sagres of Site A, B and C at 2, 10
and 18 km, respectively. A wide range of physical, biological and optical variables were sampled, but this
protocol is restricted to the reflectance measurements that were timed to coincide with the MERIS
overpass within +/-30 minutes at Station A and B and within +/- 1 hour at Station C.
The Satlantic hyperspectral radiometer was set to record for 2 minutes at a rate of approximately 1 sample
per second (depending on integration time), at a distance of 20 m away from the boat in order to avoid
irradiance interference from the shadow of the boat. The data collected from the radiometer were taken
from underwater measurements of spectral upwelling irradiance, Lu (), at 0.62 nm, and spectral
downwelling irradiance at 490 nm, Ed (490) with sensors that were fixed on a cable at 2, 4, 8 and 16 m
depth. Above the sea surface, downwelling incident irradiance, Es () was also measured. These three
parameters provided data from dark and light signals between wavelengths (λ) of 348.34 and 803.45 nm.
The radiometric measurements were consistent with the protocols for the validation of MERIS water
products (this document).
Figure 5-3: Map of the Portuguese coast with the area of study indicated as a black box. Satellite image of
southwest coast of Portugal with the location of sampling sites A, B, C.
There is concurrent logging of GPS data to provide an exact tile and estimate of the station position for
matchups. There is some variation in exact station position, since by the nature of the radiometer these are
Lagrangian observations.
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5.2.3 Data Processing
The data from each sensor was converted from binary to calibrated engineering units using Satlantic
SatCon software. The data from the sensors of Ed (490), Es () and Lu () were then corrected for the dark
signal; explicit dark readings were taken for the Ed (490) sensors and both Es (λ) and Lu (λ) sensors have
internal dark shutters. The two hyper-spectral sensors were co-aligned, by linear interpolation, to a 1nm
grid, since the spectrographs have slightly different spectral sampling points.
For the Ed (490) sensors the natural logarithm of the measured Ed (490) was regressed against depth and
the slope was used to determine attenuation coefficient, Kd at 490 nm, and Kd‟ according to (25) below;
the intercept is used to determine Es (490).
K d ' (490)  K d (490)  K w (490)
(25)
Where: Kd is the diffuse attenuation coefficient. Values of Kw are taken from Morel and Antoine (1994) in
the MERIS and in Table 4.5 of the RMD.
Kd’ at other wavelengths was calculated by converting the Kd (490) obtained from the Ed (490) depth
profile into the apparent chlorophyll. The chlorophyll value obtained was used to estimate Kd’ at other
wavelengths using the coefficients of Morel and Antoine (1994) and Equation (26):
K d '  , Chl    ( ) [Chl ]e 
(26)
The calculation of Kd’ (λ) is simply an inversion of (25).
In order to determine the values of w (0+) there are a number of necessary corrections/transformations.
The Lu (), the upwelling irradiance, has first to be extrapolated up to the sea surface. The measurements
of Lu () are taken at an offset depth of 0.62 m to avoid interference from surface waves. These values are
extrapolated to just below the sea surface using Equation (27):


Lu 0  ,  
L  
e
u
0.62K d  
(27)
Where: Kd is the spectral diffuse attenuation coefficient obtained from (26).
A self-shading correction is applied to Lu (0-,λ), based on the model of Gordon and Ding (1992) and this
correction also follows the ocean optics for satellite protocols for satellite ocean colour sensor validation
(Mueller, 2003a). The correction requires the spectral absorption coefficient, a (λ) which was
approximated as Kd (λ), and the ratio of diffuse to direct irradiance. The direct and diffuse irradiance were
calculated following Gregg and Carder (1990), using the ozone concentration, water vapour concentration
and aerosol optical thickness from the MERIS matchup pixel. The total irradiance was used as a check on
the Es () derived from normalisation, whereby Es () are normalised to the Es (490) obtained by the from
the Kd analysis in order to correct for tilt and roll.
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Finally, self-shading corrected radiance, Lu„(0-, λ), is interpolated up to the level of the surface sensor
using Equation (11). For Sagres processing, the term
(1   f )
n2
is approximately 0.54, but exact values for
a nadir viewing profiler in seawater are given in Table 10-1.
These measurements were used to estimate w, based on Equation (3). The radiometric data were
determined at the MERIS wavelengths using linear interpolation of the hyper-spectral data. This is
appropriate since the Satlantic bandwidth is approximately 10-12 nm. It should be noted that there is a
small error at the 681.25nm band, since the MERIS bandwidth is different here.
5.2.4 Uncertainties
TBD
5.2.5 Discussion and conclusion
The study by Cristina et al.(2009) shows that there some agreement between w the MERIS products and
the in-situ data sets which increases from the station A to the station C, probably due to the decrease of
the influence of the land adjacency effects on the satellite data. Scatter plots and their match-up statistics
show a large spread of data, especially in the blue band of the spectrum. Cristina et al. conclude that the
algorithms for relating these in-situ data with MERIS data could still be improved. However, however it
will be worth comparing the matchups derived from MEGS with the Cristina et al. matchups and
discussions had regarding differences and similarities and future validation campaigns.
5.2.6 Key References
Cristina, S., Goela, P., Icely, J. I., Newton, A. &Fragoso, B. (2009). Assessment of water-leaving
reflectance of the oceanic and coastal waters using MERIS satellite products off the southwest
coast of Portugal. Journal of Coastal Research Special Issue (56): 5.
Gregg, W. &Carder, K. L. (1990). A simple spectral solar irradiance model for cloudless maritime
atmospheres. Limnology and Oceanography 35: 1657-1675.
Gordon, H. R. &Ding, K. (1992). Self-shading of in-water optical instruments. Limnology and
Oceanography 37(3): 491-500.
Relvas, P. (1999).The Physical Oceanography of the Cape São Vicente Upwelling Region Observed
From Sea, Land and Space. In School of Ocean Sciences. Menai Bridge: University of North
Wales, Bangor.
Morel, A. &Antoine, D. (1994). Heating Rate Within the Upper Ocean in Relation to its Bio-Optical
State. Journal of Physical Oceanography 24: 1652-1665.
Mueller, J. L. (2003a).Chapter 6: Shadow Corrections to In-Water Welled Radiance Measurements: A
Review. In Ocean Optics Protocols For Satellite Ocean Color Sensor Validation, Vol. Revision
5, 32 (Eds J. L. Mueller, G. Fargion and C. McClain). Greenbelt, Maryland: NASA GSFC.
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6. MERMAID PROTOCOLS IV: Fixed-depth Moorings
6.1 Buoy for the acquisition of long-term optical time-series (BOUSSOLE). PI: David
Antoine
6.1.1 Introduction
The BOUSSOLE Project is composed of three complementary elements: a) a monthly cruise program, b)
a permanent optics mooring, and c) a coastal Aerosol Robotic Network (AERONET-OC; Holben et al.,
1999) station , detailed in Antoine et al. (2006). The specific aim of the project is to provide a
comprehensive time series of near-surface (0–200 m) oceanic and atmospheric inherent optical properties
(IOPs) and apparent optical properties (AOPs).
The BOUSSOLE BUOY (Figure 6-1) is deployed in the Ligurian Sea, one of the sub-basins of the
Western Mediterranean Sea. Water depth varies between 2,350–2,500m in this area, and it is 2,440m at
the mooring point, which is located at 7o 54E, 43o 22N. The BOUSSOLE cruise and mooring programme
(Antoine et al., 2006; Antoine et al., 2007; Antoine et al., 2008) was specifically designed to provide a
time-series of optical properties in the Mediterranean Sea, in support of MERIS.
For MERMAID, D. Antoine provides Chl, ρw (λ) at the bands in Table 6-1 (therefore requiring only
normalisation), θs, and the relevant metadata.
Table 6-1: Nominal wavelengths at which BOUSSOLE provides in-water radiometric data to MERMAID
Centre-Bands
MERMAID
412
443
490
510
560
620
665
681
708
BOUSSOLE
412
442
490
510
560
--
665
683
--
6.1.2 Measuring system and configuration, and measurement protocol
One-minute acquisition sequences are performed every 15 minutes, with all instruments working
simultaneously. The buoy radiometer suite is made of Satlantic 200-series radiometers measuring Ed (λ),
Eu (λ), and Lu (λ) (nadir) at two depths (4 and 9 m on horizontal arms) and at the following seven discrete
wavelengths: 412 (alternatively 555), 443, 490, 510, 560, 670 and 681 nm. A Satlantic Multichannel
Visible Detector System (MVDS) 200-series radiometer measures Es (λ) at 4.5m above the water surface
and at the same seven wavelengths. Other instrumentation provides parameters for the processing of
radiometry measurements; an Advanced Orientation Systems, Inc. (AOSI, New Jersey, USA) two-axis tilt
and compass sensor at 9m (EZ-Compass-dive), and a Sea-Bird Electronics (Bellevue, Washington) 37-SI
CTD measuring conductivity, temperature, and pressure at 9 m. Other instrumentation is described in
Antoine et al. (2006), and includes two WETLabs ECOFLNTU Chl fluorometers at 4 and 9 m.
Platforms developed for oceanographic purposes are susceptible to problems in deploying radiometers,
due to the perturbations induced by the instruments themselves and often more significantly by the
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platform, onto which they are installed, i.e. shading. Stability is also a problem; necessary for
measurements of nadir radiance or planar irradiance. BOUSSOLE was designed specifically to overcome
such problems. The platform minimises shading effects by reducing the cross-sectional area of structural
components, and its wave-interaction characteristics ensure the stability of the instruments. The design
constraints for the new platform were:
1. Measure Eu, Ed, and Lu (nadir) at two depths, plus Es at the surface;
2. Minimise the shading of the instruments;
3. Maximise the stability of the instruments; and
4. Permit deployment at a site with a water depth of 2440 m, and swells up to 8m (small horizontal
currents).
Figure 6-1: Artist’s view of
BOUSSOLE (from Antoine et al.,
2008), showing the above- and inwater radiometers, and buoy
structure.
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The basic design principle for the buoy is that of a reversed pendulum, with Archimedes thrust replacing
gravity. A large sphere (with a diameter of about 1.8 m) is stabilised at a depth out of the effect of most
surface waves, and connected at the end of a long cable anchored on the sea bottom. This sphere creates
the main buoyancy of the system. A rigid, tubular, structure is fixed above the sphere, which hosts the
instrumentation on horizontal arms (at 4 and 9m depths). With the BOUSSOLE design there is no large
body at the surface generating shade and the stability of the instruments is ensured even for quite large
swells.
6.1.3 Data Processing of Lwn (λ)
BOUSSOLE processing is detailed in Antoine et al. (2008) with the salient details provided here.
The initial step of the data processing is a data reduction that derives one representative value of Es (λ), Ed
(λ), Eu (λ) or Lu (λ) for each of the 1-minute acquisition periods; during which about 360 measurements
are taken (the acquisition frequency of the radiometers is 6 Hz). The procedure consists of taking the
median of the 360 measurements (details in Antoine et al., 2007), and allows getting rid of the
perturbations caused by the wind-roughened air-sea interface. Therefore, it provides a value that would
ostensibly be measured if the sea surface was flat. In addition, it is verified that the coefficient of variation
within the 360 Es (λ) measurements is below 5%, which ensures that the above-surface irradiance was
stable during the 1-min acquisition sequence.
From the two values of Lu (z, λ), the upwelling nadir radiance at null depth z = 0- (immediately below the
sea surface) is then obtained as (omitting the wavelength dependence for brevity):
Lu (0  )  Lu ( z  4) e KdLz fn( z, s , Chl )
(28)
where z is the measurement depth (not exactly 4 m when the buoy is lowered or when swell goes through
the superstructure). This stage of processing is the largest source of uncertainty for the BOUSSOLE. KL is
the diffuse attenuation coefficient for the upwelling nadir radiance. The latter is computed from the
measurements of Lu collected at the two depths:
KL 
 (log(( Lu ( z  9)) / ( Lu ( z  4)))
z
(29)
Where Δz is exactly 5 m. The rationale for, and the implementation of, the function appearing in the right
hand side of Equation (29) are provided in Antoine et al. (2008).
The value of Lu (0-) is then corrected for instrument self-shading as per Gordon and Ding (1992). The
parameters entering into this correction are the instrument radius, which is 4.5 cm (common to all
Satlantic 200-series radiometers), the total absorption coefficient, which is computed following Morel and
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Maritorena (2001) using the Chl concentration, and the ratio between the direct-sun and diffuse-sky
irradiances. This ratio is computed following Gregg and Carder (1990), using the atmospheric pressure
and relative humidity measured in the vicinity (2 nm) of BOUSSOLE by a meteorological buoy, the
ozone content provided by the US National Centre for Environmental Prediction (NCEP) SeaWiFS near
real-time ancillary data, and a horizontal visibility corresponding to a Shettle and Fenn (1979) maritime
aerosol with τa of 0.2 at 550 nm.
From the corrected value of Lu (0-), the water-leaving radiance at nadir, Lw, is obtained as in Equation
(11).
The remote sensing reflectance, RRS, is then obtained as in Equation (12), before which Es is corrected for
the buoy tilt. The correction is a function of the orientation of the two axes of the tilt measurement with
respect to the sun azimuth, and computes the ratio of the diffuse (unaffected by the tilt) to direct (affected
simply through the cosine of the sun zenith angle) light for clear-sky conditions (Gregg and Carder,
1990). RRS is further multiplied by π in order to get ρw, which is consistent with the definition of the
product delivered by the MERIS mission (AD [4]).
A diffuse attenuation coefficient for the downward irradiance in the upper layers is also computed as:
Kd  
log(( E d ( z )) / ( E d (0  ))
z
(30)
where: z is the deepest of the two depths (nominally 9 m), and Ed (0-) is simply Es reduced by transmission
across the air-water interface, i.e., Es * 0.97 (Austin, 1974).
The final processing step for the buoy data consists in either eliminating or correcting data corrupted by
bio-fouling. The growth of various types of marine organisms, such as algae and bacteria, is unavoidable
with moored instruments, although it is much less severe in the clear offshore waters at BOUSSOLE than
it can be, for instance, in turbid coastal environments. The cleaning of the instruments takes place every
two weeks.
6.1.4 Quality assurance
BOUSSOLE data is processed especially for MERMAID.
6.1.5 Uncertainties
There are several sources of potential uncertainty, explained in detail in Antoine et al. (2006) and Antoine
et al. (2008). Uncertainties on all terms are considered as random, Gaussian distributed, independent one
of each other, so that the final error budget is computed as the square root of the sum of the squares of the
individual error terms. Antoine et al. (2006) reach an overall uncertainty of 5.41% for BOUSSOLE and
revise this to a quadratic error budget of 6% in Antoine et al. (2008), due to the various uncertainties due
to radiometric calibration of field radiometers (3%), calibration decay over time (2%), toward surface
extrapolation (3%), self-shading (3%), and bidirectional effects (2%).
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6.1.6 Key References
Antoine, D., Chami, M., Claustre, H., d'Ortenzio, F., Morel, A., Becu, G., Gentilli, B., Louis, F., Ras, J.,
Roussier, E., Scott, A., Tailliez, D., Hooker, S. B., Guevel, P., Deste, J.-F., Dempsey, C. & Adams, D.
(2006).BOUSSOLE: A Joint CNRS-INSU, ESA, CNES, and NASA Ocean Color Calibration and
Validation Activity. Greenbelt, MD.: NASA/GSFC.
Antoine, D., Guevel, P., Deste, J.-F., Becu, G., Louis, F., Scott, A. & Bardey, P. (2007). The
'BOUSSOLE' Buoy - A New Transparent-to-Swell Taut Mooring Dedicated to Marine Optics: Design,
Tests and Performance at Sea. Journal of Atmospheric and Oceanic Technology In Press.
Antoine, D., Ortenzio, F., Hooker, S. B., Bécu, G., Gentilli, B., Tailliez, D. & Scott, A. (2008).
Assessment of uncertainty in the ocean reflectance determined by three satellite ocean color sensors
(MERIS, SeaWiFS and MODIS-A) at an offshore site in the Mediterranean Sea (BOUSSOLE project).
Journal of Geophysical Research 113(C07013, doi:10.1029/2007JC004472): 22.
Austin, R. W. (1974).The remote sensing of spectral radiance from below the ocean surface. In Optical
Aspects of Oceanography, 317-344 (Eds N. G. Jerlov and E. Steemann-Nielsen). New York: Academic
Press, London.
Bailey, S. W. & Werdell, P. J. (2006). A multi-Sensor Approach for the On-Orbit Validation of Ocean
Color Satellite Data Products. Remote Sensing of the Environment 102: 12-23.
Gordon, H. R. & Ding, K. (1992). Self-shading of in-water optical instruments. Limnology and
Oceanography 37(3): 491-500.
Gregg, W. & Carder, K. L. (1990). A simple spectral solar irradiance model for cloudless maritime
atmospheres. Limnology and Oceanography 35: 1657-1675.
Morel, A. & Gentilli, B. (1996). Diffuse Reflectance of Oceanic Waters. 3. Implications of
Bidirectionality for the Remote-Sensing Problem. Applied Optics 35: 4850-4862.
Morel, A. & Maritorena, S. (2001). Bio-optical properties of oceanic waters: A reappraisal. Journal of
Geophysical Research-Oceans 106(C4): 7163-7180.
Shettle, E. P. & Fenn, R. W. (1979).Models for the aerosols of the lower atmosphere and the effects of
humidity variations on their optical properties. In Environment Research Papers, Vol. 676, 31
Massachusetts: Air Force Geophysics Laboratory, Hanscom AFB.
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6.2 Marine Optical BuoY (MOBY). PI: Kenneth Voss
6.2.1 Introduction
The Marine Optical Buoy (MOBY, Figure 6-2) (Clark et al., 1997; Clark et al., 2003) is a fixed mooring
system providing continuous time series of normalised water-leaving radiances Lwn (λ) since 1996 for the
purpose of on-orbit calibrating ocean colour sensors. Although MOBY is primarily designed for the
NASA sensors SeaWiFS and MODIS, the hyperspectral data is also processed for MERIS bands.
MOBY is a moored tethered buoy, consisting of two complete systems, one of which is moored and
operational at any given time. The MOBY operations site is located in Honolulu, on the south shore of the
island of Oahu, at the University of Hawaii‟s Marine Centre. The MOBY site is located in 1200 m of
water approximately 18 km from the west coast of the Hawaiian Island of Lanai. The mountains on the
islands of Molokai, Lanai, and Maui provide a lee from the dominant trade winds, reducing the sea swell
and cloud cover at the site. Full details on the MOBY system can be found in Clark et al. (2003).
From the password-protected Gold directory providing the MOBY data, MERMAID receives: Lw (λ), and
Lwn (λ), and Es (λ). However, to ensure consistency with MERMAID, Lw (λ) and Es (λ) are used to
calculate ρw (λ) rather than directly using the Lwn (λ). Normalisation proceeds as described in section
1.4.5. The main reference for MOBY is the NASA Ocean Optics Protocols, Volume 3 and Volume 6
(Mueller et al., 2003); the key points pertinent to MERMAID are summarised here.
6.2.2 Measuring system and configuration
MOBY is a 12 m spar buoy (including the lower instrument bay) designed as an optical bench for
measurements of Ed (z, λ) and Lu (z, λ) at depths of 1 m, 5 m, 9 m, and 12 m (see Figure 6-2). The MOBY
spar is tethered to a second surface buoy, which is slack moored, i.e. isolated by subsurface floats, to an
anchor on the sea floor. Sensors for wind speed, wind direction, air temperature, relative humidity, and
barometric pressure are mounted on the main mooring buoy. The Marine Optical System (MOS), the
heart of MOBY, consists of two single-grating CCD spectrographs connected via an optical multiplexer
and fibre optic cables to the Ed (z, λ) and Lu (z, λ) optical heads mounted at the ends of the buoy‟s 3
standoff arms. To provide low-loss transmission at ultraviolet wavelengths, 1 mm diameter silica fibreoptic cables are used to connect the optical heads to MOS. Lu (12, λ), at z = 12 m, is measured through a
window in the bottom of the MOS housing itself. A seventh fibre optic cable connects a surface irradiance
Es (λ) cosine collector, mounted 2.5 m above the surface float, to the spectrographs. Each pair of in-water
optical heads is mounted on a standoff arm, to minimise radiometric artefacts due to shadows and
reflections from the buoy, and to minimise self-shading the Lu radiometer housings are small in diameter
(7cm) (Clark et al., 2003; Gordon and Wang, 1994).
6.2.3 Measurement Protocol
Processing follows the description provided in Mueller et al. (2003b). A single MOBY observation
comprises a sequence of four to seven spectral radiance and irradiance measurement cycles for the optical
collectors located at the different depths on the spar. Datasets are acquired daily for the nominal satellite
equatorial crossing times for SeaWiFS and MODIS Aqua overpasses.
On MOBY, Lu (z, λ) is measured at 4 depths that are rigidly separated at fixed intervals on the buoy.
These depths are nominally z1 = 1 m, z2 = 5 m, z3 = 9 m, and z4= 2.5 m. The radiance measurement at 2.5
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m is not currently used to determine water-leaving radiance, Lw (λ). Ed (z, λ) is measured only at nominal
depths z1, z2 and z3.The MOS measures radiation input from one Lu (z, λ), Ed (z, λ) or Es (λ) head at a
time. A typical sequence would be to measure Lu (λ, z) from a depth, preceded and followed by Es (λ)
surface reference spectra and associated dark spectra. Then this sequence is repeated at the 2nd and 3rd
depths to complete the profile for Lu (λ, z). Note that there are a total of 35 measurements for radiances at
the 3 depths, surface irradiance Es (λ) and sensor dark spectra. The 35 measurements are grouped into
overlapping subsets of 15 measurements, representing the cycle associated with upwelled radiance
measurements at each depth. This entire procedure requires between 30 min and 1 hr to complete.
Figure 6-2: The NASA MOBY instrument set-up at Lanai, Hawaii
6.2.4 Data processing of Lwn (λ) and quality assurance
MOBY is designed to take measurements at 0.6 nm intervals, to suit the NASA ocean colour sensors, and
weighted band-averaged values, of Lwn are computed. Details of temporal averaging (unit integration
time) and the spectral response functions are detailed in Clark et al. (2003), however the parameters
pertinent to MERMAID are described here.
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Determining Lw (λ)
MOBY makes measurements at three depths near the ocean surface. The shallowest measurements (at 1
m) are propagated upward to just below the ocean surface by calculating the upwelling spectral radiance
attenuation coefficient, KL (λ), using:
KL 
 L ( z ,  ) E st2 
1
ln  u t1 1

z 2  z1  E s ( ) Lu ( z 2 ,  ) 
(31)
where z and z are the two depths at which measurements are made (z < z ). Es (t1) and Es (t2) are the
averages of the Es measurements before and after the in-water Lu measurements to remove the effects of
solar irradiance changes from those measurements. The convention for this calculation is that the depth at
the surface is zero and that the values of z increase with depth.
1
2
1
2
Then the radiance change between depth z and the surface is calculated using:
1
Lu (0 ,  )  Lu ( z1 ,  )e KL ( )z1
(32)
The depth zi is selected according to the following hierarchical rules:
1. If the data from the top arm are valid, then that depth is selected.
2. Else, the data from the middle arm, if valid, are selected.
3. Else, the data sequence is rejected entirely.
To determine Lw (λ) from Lu (λ), the measurement of upwelling radiance from a selected depth zi is
propagated to the surface using Equation (11). The upward transmittance through the interface, the
Fresnel transmittance, for nadir viewing radiance, is approximately constant with the value 0.543.
For MOBY measurements, the propagation of light to the surface is made from the topmost arm of the
buoy (z1=1 m). However, there are periods when the topmost arm is either broken or missing. For these
periods, the centre arm (z1=5 m) is used in its place.
Tilt effect considerations and Es (λ)
There are no pressure transducers in each sensor head; there is only one, recording with each scan in the
MOS system. Additionally, the fixed arm depths are used to extrapolate Lu (λ) to the surface, and
therefore tilt is not accounted for (Pers. Comm. Flora, 28th Jan 2010). Es (λ) from MOBY is from
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measurements; Es (λ) is not computed via Gordon and Wang (1994) approximations (Pers. Comm. Flora,
28th Jan 2010).
6.2.5 Quality Control
MOBY has sensors for dark readings and depth variation, as well as those for wind velocity, surface
barometric pressure, air temperature, relative humidity, water temperature and conductivity and
chlorophyll-a fluorescence. A weakness of MOBY is the amount of time it takes to go through a complete
measurement cycle. Pressure is measured just prior to or during the Lu(λ) measurement; however, the
integration time for an Lu(λ) measurement is in the order of 30 seconds for the full spectral range, so the
depth at time of measurement is only an approximation (Pers. Comm. Franz, 13th Oct. 2009).
MOBY data are corrected for dark readings, as specified in the NASA protocols, and also for straylight.
6.2.6 Uncertainties
The current claim of uncertainty for MOBY is, for so-called 'good scans' and not including a shadowing
correction, approximately 5 % for MODIS channels 8 through 12, increasing to 12.5 % for channel 13
due to a large shadowing correction (Brown et al., 2007). If only data from good scans labelled good days
after quality control checks are applied and a shadowing correction is applied to the data set, the
uncertainty is expected to reduce to less than 3 % for MODIS channels 8 through 12, increasing slightly,
to 3.3 %, for channel 13. The shadow-uncorrected uncertainties should be used for the present.
6.2.7 Key References
Austin, R. W. (1974).The remote sensing of spectral radiance from below the ocean surface. In Optical
Aspects of Oceanography, 317-344 (Eds N. G. Jerlov and E. Steemann-Nielsen). New York: Academic
Press, London.
Clark, D. K., Gordon, H. R., Voss, K. J., Ge, Y., Broenkow, W. & Trees, C. (1997). Validation of
Atmospheric Correction Over the Oceans. Journal of Geophysical Research 102D: 17209-17217.
Clark, D. K., Yarborough, M. A., Feinholz, M. E., Flora, S., Broenkow, W., Kim, Y. S., Johnson, B. C.,
Brown, S. W., Yuen, M. & Mueller, J. L. (2003).MOBY, A Radiometric Buoy for Performance
Monitoring and Vicarious Calibration of Satellite Ocean Colour Sensors: Measurements and Data
Analysis Protocols. In Ocean Optics Protocols for Satellite Ocean Colour Sensor Validation, NASA
Technical Memo. 2003-211621/Rev4, VolVI, 3-34 (Eds J. L. Muller, G. Fargion and C. McClain).
Greenbelt, MD.: NASA/GSFC.
Gordon, H. R. & Wang, M. A. (1994). Retrieval of water-leaving radiances and aerosol optical thickness
over the oceans with SeaWiFS: A preliminary algorithm. Applied Optics 33(3): 443-452.
Mueller, J. L., Fargion, G. & McClain, C. (2003b).Ocean optics protocols for satellite ocean color sensor
validation, Revision 4. Vol. I - VII, 141 Greenbelt, Maryland: NASA.
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7. MERMAID PROTOCOLS V: Profiling Instruments
7.1 Bristol Channel and the Irish Sea. PI: David McKee
7.1.1 Introduction
D. McKee has provided a dataset of reflectances from a study of IOPs and AOPs in the Bristol Channel
and the Irish Sea in UK and Irish waters. A Satlantic freefall equipped with seven wavelengths (412, 443,
491, 510, 554, 665, 700 nm) is used. The main references for these data are the NASA Ocean Color
Protocols (Mueller et al., 2003a) the ProSoft 7.7 User Manual (Satlantic, 2007), and McKee (Pers.
Comm., 2008).
Note: the dataset on the MERMAID website is affected by the ProSoft processing bug which has now
been fixed. Explanation of the bug follows in this protocol and the updated dataset will be available
online soon. An advisory note is displayed prior to extraction of this dataset.
7.1.2 Measuring system and measurement protocol
The Satlantic (Satlantic Inc., Nova Scotia, Canada) SeaWiFS Profiling Multichannel Radiometer (SPMR)
is a multispectral instrument designed specifically for the purposes of SeaWiFS validation. It generates
measurements of upwelling radiance, Lu, and downwelling irradiance, Ed, across the visible spectrum
(412, 443, 489, 510, 554, 665 and 700 nm), with associated bandwidths of 10 nm. Designed as a
freefalling profiler, the SPMR instrument decouples measurements from ship motion and minimises ship
shadowing; the instrument orientate in the vertical position with the instrument deployed far enough from
the research vessel to avoid ship shadow effects. On board inclinometers provide orientation information
allowing data to be removed that does not satisfy predetermined criteria. The original system was
supplied with a surface irradiance (Es) sensor which was mounted high on the superstructure to give high
frequency, concurrent surface irradiance data during profiles. Unfortunately this unit failed after the first
couple of cruises and could not be replaced. The SPMR was calibrated by Satlantic on two occasions; the
original calibration for Irish Sea cruises and a second calibration for later cruises in the Bristol Channel.
The SPMR was deployed well away from the side of the vessel to minimise ship-shadow effects,
generally 20m or more. The free-fall nature of the instrument means it can be used like an underwater kite
- paying out enough cable and letting it move up and down the water column a few times usually
establishes a reasonable distance between the ship and the sensor.
The θs was not provided but computed from the provided dates, times, latitudes and longitudes.
Radiometric measurements were made during normal working hours (09:00 to 18:00 local) and under a
variety of atmospheric conditions, often cloudy; clear skies are relatively rare in this region.
Also provided to MERMAID are measurements of Chl, measured using 90% acetone extraction and
spectrophotometric analysis. There are two sets of equations used: (a) trichromatic equations of Jeffrey
and Humphrey (1975) to give Chla (and b, c, carotenoids) - this is „A1‟, and a second method gives Chla
and phaeopigment (after acidification) - this is „A2‟. A1 is used for MERMAID.
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7.1.3 Satlantic SeaWiFS Profiling Multichannel Radiometer Reprocessing
Data provided to MERMAID consist of single casts for each station. Each cast was selected as the
optimum available for that station taking into account: stable surface irradiance (where this information
was available), minimal tilt angle, and quality of derived diffuse attenuation products (for extrapolation to
/ through sea surface).
SPMR data were processed using Prosoft v7.7.11.
The program converts raw signals detected by the instrument into higher level products such as water
leaving radiance and reflectance profiles. At the first levels (1a/1b/2), calibration and reference data are
applied to the collected signals. Any measured points greater than 10 times the cast standard deviation
were removed, as well as points where the tilt of the instrument was greater than a defined value (10
degrees). Processing to level 2s involves defining a pressure coordinate system. The Ed and Lu sensors,
located at the top and bottom of the instrument respectively, are separated on the SPMR by a distance of
1.25 m. The measurements per depth are corrected to a common depth defined by the position of the Ed
sensor. To progress to level 3, the data was sorted into depth-averaged bins of 0.5 m. Optical sensor data
(Lu etc.) were natural log transformed to “straighten” the data prior to averaging.
The final stage incorporates radiometric equations to calculate level 4 products. Linear polynomial fits
were applied to data using a 5 point window for depth profiles of lnLu and lnEd. The slope of best fit lines
through log-transformed Ed and Lu versus depth gives Kd and KLu as a function of depth. Values of Ed and
Lu immediately beneath the sea surface (Ed (0-,λ) and Lu (0-,λ)) are obtained as the intercepts of the best fit
line passed through the 5 depth profile values nearest the surface. Accounting for air-sea interface effects,
Lu and Ed are extrapolated through the surface to give Lw(0+,λ) as in Equation (11), and Ed(0+,λ) as in:
E d (0  ,  )
E d 0 ,   
1

(33)
where α is the Fresnel reflection albedo for irradiance from sun and sky (0.043). The above-surface values
of radiance and irradiance then provide inputs for calculating apparent optical properties, for example
remote sensing reflectance, RRS, as in Equation (12).
During the course of data processing (ProSoft version 7.7.11), an error was uncovered with the procedure
responsible for extrapolating optical values to the surface. The first two entries of Lu profiles derived at
level 3 were marginally lower than those presented in the level 2s data. An example of this is shown in
Figure 7-1. The error was found to be consistent across all wavelengths and was only present for the Lu
sensor. The binning algorithm used by ProSoft for L3 Lu data was determined as the cause of the error,
whereby the program was unable to effectively deal with NaN values. The SPMR configuration places Lu
sensors at the bottom of the profiler, about 1.25m deeper than Ed sensors mounted at the top of the unit. Ed
data profiles therefore routinely start ~1.25m shallower than Lu profiles. These “blank” Lu data points
were subsequently being replaced by NaNs (not a number – used by MATLAB) which were inadequately
handled by the depth-average binning. A correction routine was developed to address this issue, which
ignored the first two data points when performing extrapolations on Lu. Removal of the two Lu bins
closest to the surface unfortunately extends the range for extrapolation, but we consider the assumption of
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a uniform surface layer over these depths to be a reasonable approximation. This approach has the merit
of at least removing known problematic points.
Figure 7-1: Errors
in first two points of level 3 depth-averaged Lu values.
Water leaving radiance, Lw (λ) was calculated using Equation (11), where a default value of 0.021 was
used for f and default value of 1.345 used for n. Ed (0+, λ) was used as a substitute for Es (λ) in
MERMAID to convert the Lw (λ) to ρw (λ).
7.1.4 Uncertainties
No uncertainties have been provided to date.
7.1.5 Key References
Jeffrey, S. W. &Humphrey, G. F. (1975). New spectrophotometric equations for determining chlorophylls
a, b, c1 and c2 in higher plants, algae and natural phytoplankton. Biochemie und Physiologie der Pflanzen
167: 191-194.
Mueller, J. L., Bidigare, R. R., Trees, C., Balch, W. M., Dore, J. & Drapeau, D. T. (2003a).Ocean Optics
Protocols for Satellite Ocean Colour Sensor Validation, Revision 5, Volume V: Biogeochemical and BioOpitcal Measurements and Data Analysis Protocols., 36 Greenbelt, MD: NASA/GSFC.
Satlantic (2007).Prosoft 7.7 User Manual. Vol. Revision E.
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7.2 California Current. PI: M. Kahru
Vertical profiles of downwelling spectral irradiance and
upwelling radiance were measured with underwater
radiometers (Biospherical Instruments MER-2040 and MER2048) as part of the California Cooperative Oceanic Fisheries
Investigations (CalCOFI; Figure 7-3) bio-optical program
(Kahru and Mitchell, 1999; Mitchell and Kahru, 1998), and
following SeaWiFS bio-optical protocols (Mueller and Austin,
1995). Mitchell and Kahru (1998) provide detailed explanations
of the measurement procedures followed. Downwelling spectral
irradiance (Ed) and upwelling radiance (Lu) at the following
nominal wavelengths were measured by the MER-2040: 340,
380, 395, 412, 443, 455, 490, 510, 532, 555, 570, and 665 nm.
A MER-2041 deck-mounted reference radiometer also measured
downwelling irradiance at the following nominal wavelengths:
340, 380, 395, 412, 443, 490, 510, 555, 570, 665, 780, and 875
nm, PAR. Instrument self-shading correction (Kahru and
Mitchell, 1998; Gordon and Ding, 1992) was routinely applied
and profile with the ship shadow and/or variable illumination
were eliminated. Nearshore stations with increased reflectance
due to suspended sediments were also excluded. The
advantage of this dataset compared to the heterogeneous Figure 7-2: CalCOFI transect
locations, California Coast. (from:
SeaBAM dataset is that it has been collected with the same
http://www.calcofi.org)
well calibrated instruments and processed using similar
procedures. Measurements of Chl-a were taken in the CalCOFI program using the fluorometric method
(Holm-Hansen et al., 1965; Venrick and Hayward, 1984) consistent calibration protocols.
The MER-2040/2041 system described in had detailed system characterization and radiometric
calibration performed by the manufacturer, Biospherical Instruments, Inc. (BSI), and the Center for
Hydro-Optics and Remote Sensing (CHORS) of San Diego State University according to procedures
specified by the SeaWiFS Protocols (Mueller and Austin, 1995). Further details are provided in Mitchell
and Kahru (1998).
The MER unit was generally deployed immediately before or immediately after the CalCOFI water bottle
cast to ensure minimal offset in time and space for the optics and the pigment data set. Immediately
following each cast, a dark scan of the MER radiometer was run by attaching opaque PVC caps on the
radiometer heads and recording the data for several minutes.
The CalCOFI bio-optical profiles were processed with a modified version of the Bermuda Bio-Optics
Project (BBOP) data-processing system (Siegel et al., 1995). Mitchell and Kahru (1998) also explain in
detail the BBOP processing and pre-processing employed on the CalCOFI dataset.
Remote sensing reflectance, RRS, was computed as in Equation (12), using air-sea interface transfer
coefficients 0.54 and 1.04 for, respectively, Lu and Ed (Austin, 1974).
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7.2.1 Key References
Austin, R. W. (1974).The remote sensing of spectral radiance from below the ocean surface. In Optical
Aspects of Oceanography, 317-344 (Eds N. G. Jerlov and E. Steemann-Nielsen). New York:
Academic Press, London.
Gordon, H. R. &Ding, K. (1992). Self-shading of in-water optical instruments. Limnology and
Oceanography 37(3): 491-500.
Holm-Hansen, O., Lorenzen, C. J., Holmes, R. W. &Strickland, J. d. H. (1965). Fluorometric
Determination of Chlorophyll. J. Cons Perm Int Expl Mer 39: 3-15.
Kahru, M. &Mitchell, B. G. (1998). Spectral Reflectance and Absorption of a massive Red Tide off
Southern California. Journal of Geophysical Research 103(21): 21601-21610.
Kahru, M. &Mitchell, B. G. (1999). Empirical Chlorophyll Algorithm and Preliminary SeaWiFS
Validation for the California Current. International Journal of Remote Sensing 20: 3423-3429.
Mitchell, B. G. &Kahru, M. (1998).Algorithms for SeaWIFS Standard Products Developed with the
CALCOFI Bio-Optical Data Set. In CALCOFI Report, Vol. 39, 15pp.
Mueller, J. L. &Austin, R. W. (1995).Ocean Optics Protocols for SeaWiFS Validation, Revision 1. In
NASA Tech. Memo., Vol. 25(Eds S. B. Hooker, E. R. Firestone and J. Acker). Greenbelt,
Maryland: NASA Goddard Space Flight Center.
Siegel, D. A., O'Brian, M. C., Sorensen, J. C., Konnoff, D. A. &Fields, E. (1995).BBOP Data Processing
and Sampling Procedures., Vol. 19, 77 pp.
Venrick, E. L. &Hayward, T. L. (1984).Determining Chlorophyll on the 1984 CalCOFI surveys. . In
California Coorperative Oceanic Fisheries Investigations Reports., Vol. 25, 74-79.
7.3 Plumes and Blooms. PI: D. Siegel
The following protocols are taken from and expanded upon in more detail in Kostadinov et al. (2007),
Toole and Siegel (2001) and Toole et al. (2000). The Plumes and Blooms program follows the NASA
Ocean Optics Protocols (e.g. Mueller, 2003b).
The primary goal of the Plumes and Blooms ocean color observational program is to assess the spatial
and temporal structure of sediment plumes and phytoplankton blooms in the Santa Barbara Channel.
Twice monthly, seven station transect cruises across the Santa Barbara Channel from Goleta Point to
Carrington Point off Santa Rosa Island are conducted (Figure 7-3). This cross-channel transect permits
the sampling of a wide range of oceanic conditions with chlorophyll concentrations ranging from 0.05 to
7.0 mg m-3 and total suspended sediments ranging from 0.0 to 3.4 mg l-1. At each station, the Plumes and
Blooms program routinely makes three independent estimates of remote sensing reflectance, RRS.
7.3.1 Reflectances
A Biospherical Instruments Profiling Reflectance Radiometer, PRR-600 (Toole et al., 2000) was used to
obtain profiles of upwelling radiance, Lu (λ), and downwelling irradiance, Ed (λ), at 412, 443, 490, 510,
555, and 656 nm. The free-falling PRR-600 was cast separately on a loose tether to minimize ship
shadowing. Data in the upper 12 m were used to extrapolate the Lu (λ), and Ed (λ) data to just below the
surface. RRS just below the surface was then computed as in Equation (12). Conversion to above water
was done with the air-sea interface terms in Table 1-3. Further details on data processing are given in
Toole et al. (2000).
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7.3.2 Additional parameters
In addition to the optical sampling, a complementary data set is collected at each station. This data set
includes conductivity-temperature and depth profiles; particulate absorption by the filter pad method;
coloured dissolved organic absorption spectra; and concentrations of inorganic nutrients, phytoplankton
pigments, total suspended materials. All samples are collected, stored, prepared and analysed using
existing techniques recommended by the U.S. JGOFS and SeaWiFS programs (see
www.icess.ucsb.edu/PnB/MethodsManual.html).
Figure 7-3: Santa Barbara Channel, California USA. Plumes and Blooms stations are marked with an ‘x’.
From Kostadinov et al. (2006).
Surface chlorophyll a concentrations were obtained by fluorometry from Niskin bottle samples following
the study by Strickland and Parsons (1972) and using a Turner Designs 10AU fluorometer. A Shimadzu
UV2401-PC (a Perkin-Elmer Lambda 2 before mid-2003) spectrophotometer was used to obtain the
spectra of the phytoplankton absorption coefficient aph (λ), the CDOM absorption coefficient ag (λ), and
the detrital absorption coefficient ad (λ) at each station from the surface bottle samples.
A HobiLabs Hydroscat-6 was used to obtain profiles of the backscattering coefficient bb (λ) at each
station for λ = 442, 470, 510, 589, 671, and 870 nm. Pure water calibrations (done at the factory and
UCSB semiannually) were applied. The HS-6 measures the total volume scattering function β at 140o. β is
then converted to the total backscattering coefficient using bb (λ) = 2πχp(β - βw) + bb w (λ) where bw and bb
w (λ) come from the study by Morel (1974) and χp = 1.18 (Boss and Pegau, 2001). The upper 15 m of data
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from the downcasts were filtered and averaged to obtain a surface backscattering value. The σ (λ)
correction was then applied to correct for light attenuated in the measurement path of the instrument
(Maffione and Dana, 1997) using concurrent AC-9 surface data. Spectra which were not monotonically
decreasing were rejected as unreliable.
A WetLabs AC-9 absorption and attenuation meter (Moore et al., 1992) was used to obtain profiles of insitu absorption and beam attenuation coefficients at each station [a (λ) and c(λ) at 412, 440, 488, 510,
555, 630, 650, 676, and 715 nm].
7.3.3 Key references
Boss, E. & Pegau, W. S. (2001). The Relationship of Light Scattering at an Angle in the Backward
Direction to the Backscattering Coefficient. Applied Optics 40: 5503-5507.
Maffione, R. A. &Dana, D. R. (1997). Instruments and Methods for Measuring the Backward-scattering
Coefficient of Ocean Waters. Applied Optics 36(24): 6057-6067.
Moore, C., Zaneveld, J. R. V. &Kitchen, J. C. (1992).Preliminary Results from an In-situ Spectral
Absorption Meter. In SPIE Society of Optical Engineering, Vol. 1750, 330-337.
Morel, A. (1974).Optical Properties of Pure Seawater. In Optical Aspects of Oceanography., 1-24 (Eds N.
G. Jerlov and E. Steeman-Nielsen).
Mueller, J. L. (2003b).In-water Radiometric Profile Measurements and Data Analysis Protocols. Vol.
211621 Revision 4, Volume 2, 7-20: NASA.
Kostadinov, T. S., Siegel, D. A., Maritorena, S. A. &Guillocheau, N. (2007). Ocean Color Observations
and Modeling for an Optically Complex Site: Santa Barbara Channel, California, USA. Journal
of Geophysical Research 112(C07011): doi: 10.1029/2006JC003526.
Strickland, J. D. H. &Parsons, T. R. (1972). A Practical Handbook of the Sea Water Analysis. Fisheries
Research Board Canada Bulletin: 167-311.
Toole, D. &Siegel, D. A. (2001). Modes and Mechanisms of Ocean Color Variability in the Santa Barbara
Channel. Journal of Geophysical Research 106(C11): 26985-27000.
Toole, D., Siegel, D. A., Menzies, D., Neumann, M. J. &Smith, R. C. (2000). Remote-Sensing
Reflectance Determinations in the Coastal Ocean Environment: Impact of Instrumental
Characteristics and Environmental Variability. Applied Optics 39(3): 456-469.
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8. MERMAID PROTOCOLS VI: TriOS Ramses
8.1 English Channel. PI: H. Loisel, C. Jamet
Intensive field cruises were conducted from March to June 2004 to characterize the bio-optical and
radiometric variability of the eastern English Channel and southern North Sea. Lubac and Loisel (2007)
describe fully the campaign and results. The stations sampled during the cruise periods (15–18 March,
11–15 April, 10–15 May, 25–30 June) are displayed in Figure 8-1.
The investigated area is bordered by the mouth of the Seine River in the south, and by the mouth of the
Escault River in the north. This region is affected by typical coastal process such as strong tide ranges,
river inputs, resuspension due to the low bathymetry, and mixing of various water masses. The studied
area is also characterized by relatively intense spring blooms of phytoplankton species, such as the
prymnesiophyceae Phaeocystis globosa (Breton et al., 2006; Rousseau, 2000).
Figure 8-1: Location of the different stations visited in the eastern English Channel and southern North Sea
in 2004. The investigated area is bordered by (I) the mouth of the Seine River in the south and (II) the mouth
of the Escault River in the North.
Hyperspectral (every 3 nm) radiometric measurements were performed in the 350–750 nm spectral range
from three TriOS radiometers. The first (on the deck) and second (in water) radiometers were equipped
with an optical fibre and a cosine collector that were pointed upward to measure the above surface
downward irradiance, Es (λ), and the in-water irradiance profile, Ed (z,λ), respectively. The third
radiometer is equipped with a field of view of 7° in air, and is pointed downward to measure the nadir
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upward radiance profile, Lu (z,λ). Wavelength dependent correction factors, also called immersion
factors, are applied to correct the reduction of the solid angle and the decrease of the light transmissivity
due to the water immersion of the sensor (Mueller and Austin, 2003). To limit impact of external factors,
93 stations were selected for their favourable environmental conditions (clear sky, low winds, and smooth
water surfaces). The sun zenith angle values range between 30° and 80° for these selected stations (with a
mean value of 51°, and a standard deviation of ±16°).
The remote sensing reflectance, RRS(λ), is calculated as in Equation (12). Lw(λ) was determined as in
Equation (11) with the air-sea interface terms given in Table 1-3.
To determine Lu(0−,λ), Lubac and Loisel (2007) used a near surface vertical profile of Lu (z,λ), which
had previously been corrected from the instrument self-shading effect according to the procedure
described in (Leathers and Downes, 2004). The attenuation coefficient for upward radiance, KLu (z0,λ),
is then computed as the local (around the depth z0=5 m) slope of the ln(Lu (z,λ)) self-shading corrected
profile, and is used to determine Lu (0 ,λ) from the upward radiance measured in the upper layer (Hooker
and Morel, 2003; Mueller, 2003b; Smith and Baker, 1984):
−
Lu (0  ,  )  Lu ( z,  ) e
( K Lu ( z0 , ) z )
(34)
8.1.1 Error estimations
The error between self-shading corrected Lu (0-,λ) and self-shading uncorrected Lu (0 ,λ) is less than 4%
in the visible. This weak impact is due to the relatively high sun zenith angles (50°) and to the small
instrument radius (3 cm). Relative error due to instrument self-shading is calculated as: (1−e) / e, where e
−
=exp(−κ·a(λ) · r) (Leathers and Downes, 2004), with r the instrument radius (r =0.03 m), κ function of
the in-water solar zenith angle, and a(λ) the sum of aw(λ), aCDOM (λ), and ap (λ), not measured but
estimated from the sum of ap (λ) and aNAP (λ) calculated from the models of Bricaud et al. (1995) and
Babin et al. (2003), respectively.
8.1.2 Key references
Babin, M., Stramski, D., Ferrari, G. M., Claustre, H., Bricaud, A., Obolensky, G. &al., e. (2003).
Variations in the Light Absorption Corefficients of Phytoplankton, Non Algal Particles, and
Dissolved Organic Matter in Coastal Waters Around Europe. Journal of Geophysical Research
108: 3211 (doi: 3210.1029/2001JC000882).
Breton, E., Rousseau, V. &Parent, J. Y. (2006). Hydroclimatic Modulation of Diatom/Phaeocystis blooms
in nutrient-enriched Belgian Coastal Waters (North Sea). Limnology and Oceanography 100:
13321-13332.
Bricaud, A., Babin, M., Morel, A. &Claustre, H. (1995). Variability in the Chlorophyll-Specific
Absorption-Coefficients of Natural Phytoplankton - Analysis and Parameterization. Journal of
Geophysical Research-Oceans 100(C7): 13321-13332.
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Lubac, B. &Loisel, H. (2007). Variability and classification of remote sensing reflectance spectra in the
eastern English Channel and southern North Sea. Remote Sensing of the Environment 110: 45-58.
Hooker, S. B. &Morel, A. (2003). Platform and Environmental Effects on Above-Water Determinations
of Water-Leaving Radiances. Journal of Atmospheric and Oceanic Technology 20: 187-205.
Mueller, J. L. (2003b).In-water Radiometric Profile Measurements and Data Analysis Protocols. Vol.
211621 Revision 4, Volume 2, 7-20: NASA.
Mueller, J. L. &Austin, R. W. (2003).Characterisation of Oceanographic and Atmospheric Radiometers.
Volume II: Instrument Specifications, Characterisation and Calibration. In Ocean Optics
Protocols For Satellite Ocean Color Sensor Validation, Revision 4Greenbelt, MD: NASA/GSFC.
Smith, R. C. &Baker, K. S. (1984).The Analysis of Ocean Optical Data. In Ocean Optics VIISPIE, Vol.
478, 119-126 (Ed M. A. Blizard).
8.2 FERRYBOX. PI: K. Sørensen
8.2.1 Introduction
Ferrybox is the name of a coordinated project aimed at collecting in-situ marine scientific data for marine
observation and monitoring. Funded by the EU Science Framework 5 Ferrybox enabled the cooperation
of 11 organisations and established the coordinated use of commercial ferry ships for the collection of
scientific data. The 11 partners operated on 9 shipping routes around Europe, from the eastern
Mediterranean to the Baltic. The Ferrybox systems consist of a fully automated flow-through system with
sensors and automatic analysers for the measurement of physical, biological and chemical parameters,
which uses ferryboats and other ships of opportunity as the carrier system, and these route and vessels
have been exploited by the optics community in Norway (NIVA) to mount TriOS Ramses instruments for
optical measurements. Some of the advantages of using these Ferrybox carrier vessels to mount TriOS
systems include easy maintenance in the harbour (no additional ship time is needed) and that the
information from a transect is often better than from a single location. For more information on Ferrybox
go to http://www.ferrybox.com/index.html.en.
Presently the data from the Norwegian TriOS is undergoing analysis and processing, and has not yet been
submitted to MERMAID. The measurement protocol is available in advance, as described in Høkedal and
Sørensen (2007).
8.2.2 Measuring system and measurement Protocol
Mounted on ferries covering most of the Norwegian coast are sets of optical sensors. Each set consists of
two radiance sensors (one viewing the surface of the sea, one at the sky) and one irradiance sensor, in
addition to GPS-sensor controlling the system. The collected data are used in calculating radiance
reflectance which is also one of the MERIS-products. The systems only require maintenance on weekly or
longer intervals, and are hardly affected by deposits of salt or airborne particles.
The radiance and irradiance sensors are from the German company TriOS, mounted on two ships, „Color
Festival‟ in the Skagerrak and „Trollfjord‟ along the Norwegian from 60ºN to the Russian border. Each
system set consists of one irradiance sensor (for downward irradiance) and four radiance sensors, two for
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upward and two for downward radiance. These 5 sensors are together with a GPS receiver connected via
an interface box to a computer which records the data.
For ocean colour data to be used it is an absolute demand that the footprint is not disturbed by the ship,
either by wakes and the shadow of the ship. Additionally the azimuth angle between the sun and the
sensor should ideally be 135º to minimise the sun glint. Given this, and together with the route of the
ferries the sensors are installed in the following way: On „Color Festival‟ the downward viewing sensors
are mounted slightly forward at the starboard and port side (which is optimal with a ship heading
northward during daytime). The route of „Trollfjord‟ is more complicated; however the sensors are
mounted at the port side of the ship, forward and aft viewing respectively.
8.2.3 Data Processing
The parameter derived from the TriOS system processing is ρw (λ) as defined by Equation (3).
Lw is calculated from measurements of nadir-radiance below the surface (which are extrapolated to the
surface, then the water-leaving part is determined from the refractive index of water). This gives the right
hand side of Equation (35) which is compared with the reflectance given by MERIS.
On a continuously moving platform ferry subsurface measurements for determining Lw are, for obvious
reasons, impossible. Instead, radiance is measured above surface with a downward viewing radiometer.
However, this measures not just Lw, but the sum of this and the downward direct and diffuse light
reflected at the surface, i.e. Lt = Lw + Lwrefl. To estimate the latter addend of this sum the downward
diffuse contribution Lsky at the nadir angle (π- θ) is commonly measured, assuming this is the radiance
reflected into radiometer (or proportional to it). Thus, we get:
Lrefl
w ( , ,  )   f Lsky ( ,    ,  )
(35)
Where, for a flat surface the Fresnel reflection f takes a value around 2%. With a wind roughened surface
the value of 2.8% has been determined for an overcast sky.
However, these values of f are not plausible because the reflected light does not only consist of Lsky (π); due to the rough surface the entire upper hemisphere Lwrefl is dependent on Lsky (Ω) (which depends on
the solar elevation, where Ω denotes the solid angle); additionally Lwrefl also depends on viewing direction
and wind speed. Such functionality is far more complicated than the scope of this protocol, so instead a
simpler solution is to presume that Lsky (Ω) is better correlated with Es than Lsky (λ, π- , ). Therefore, we
write:
Lrefl
w ( , ,  )   fe E s ( )
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where fe is the equivalent Fresnel reflection, expressed as sr-1. It is independent of wavelength, but will
vary amongst the measured spectra. To determine fe we presume that due to high absorption the water
reflection coefficient is assumed to be nul somewhere in the wavelength domain from 800 to 900 nm.
With the observed values of upward radiance and downward radiance it is then straight forward to find
the value of fe for each measurement.
On the ferry the radiometers are mounted in fixed angles relative to the ship. As a consequence of this θs
(between the sun and the radiometer) depends on the sun‟s position as well as the course of the ship. Here
we will not go into details but mention that the measurements are filtered for shadow of the ship at the
footprint of the radiance sensor, θs less than 90o, and finally solar elevation less than 30 o.
8.2.4 Uncertainties
If the ferry follows an optimal transect combined with a careful choice of observing angles (to avoid ship
shadow on the sensors footprint as well as sun-glint from the surface) it is shown that data can be
collected most of the day, including during satellite passage. Satellite coverage and cloud conditions limit
the number of possible match-ups, not the ship-time which usually is the limiting factor. Results show
typically 20% deviation between reflectance determined from MERIS and in-situ data.
8.2.5 Key Reference
Høkedal, J. & Sørensen, K. (2007).Validation of MERIS-reflectance from Ferries. In ENVISAT
Symposium. Montreux, Switzerland, 23-27 April 2007.
8.3 French Guiana. PI: H. Loisel; C. Jamet
The location of the sampled stations in French Guiana is indicated in Figure 8-2; the campaign and results
are fully described in Loisel et al. (2009). Remote sensing reflectance, RRS (), measurements were
performed at each station using two TriOS hyperspectral (every 3 nm) radiometers: one measuring the
downwelling irradiance on the deck, Es (0 ,λ), and one measuring the in water upwelling radiance just
below the sea surface, Lu (0-, ). The immersion factors, as well as the impact of the self-shading are
accounted for as in Lubac and Loisel (2007). These measurements were performed from a very small flat
bottomed boat, far away from any perturbations of the main boat. RRS () is calculated as in Equation (12)
with the air-sea interface transmittance term value (to convert Lu to above water) given in Table 1-3.
+
The remote sensing reflectance spectra exhibited a great variability in shape and amplitude; however, all
these RRS () spectra fall into the five classes defined by Lubac and Loisel (2007).
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Figure 8-2: Location of the stations sampled on 7-11 July 2006 (from Loisel et al., 2009).
8.3.1 Key references
Loisel, H., Mériaux, X., Poteau, A., Artigas, L. F., Lubac, B., Gardel, A., Caillaud, J. &Lesourd, S.
(2009). Analyze of the inherent optical properties of French Guiana coastal waters for remote
sensing applications. Journal of Coastal Research ICS Proceedings.
Lubac, B. &Loisel, H. (2007). Variability and classification of remote sensing reflectance spectra in the
eastern English Channel and southern North Sea. Remote Sensing of the Environment 110: 45-58.
8.4 Helgoland/Cuxhaven Transect. PI: R. Doerffer
8.4.1 Introduction
This protocol (Doerffer and Schönfeld, 2009) describes data from the ferry cruises between Cuxhaven
and Helgoland, which are carried out for the validation of MERIS data (Figure 8-3). These matchups are
not yet in the MERMAID database, but are the subject of investigation into matchups over transects.
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Figure 8-3: Route and stations of the MERIS validation campaign "c30" on 13. July 2006
The basic idea is to sample data along a transect with a strong gradient of the concentration of water
constituents, in particular of yellow substance and suspended matter. Such a gradient can then be
compared with the corresponding transect extracted from MERIS data. The main problem of the
validation of case 2 waters is the strong patchiness and dynamics of case 2 coastal waters due to tidal
currents. A direct comparison between a water sample and a pixel is not possible because of the different
spatial and temporal relationships between these two measurements. When using a transect one can
compare at least the shape as well as the concentration range along the transect, although details may also
differ. Also the comparison between path radiance and water leaving radiance indicate if the atmospheric
correction over turbid water was successful. During the summer month there is a daily ferry connection
between Cuxhaven at the mouth of the Elbe River and the island of Helgoland (Figure 8-3). Shortly
before arriving Helgoland the overpass of MERIS happens. A further advantage is that it can be decided
to carry out a validation cruise on the basis of the weather forecast on short notice.
8.4.2 Measuring system and measurement protocol
During the entire cruise we operate a TRIOS RAMSES radiometer system to determine the water
reflectance spectrum (Figure 8-4). The instruments are mounted at the bow of the ship to avoid the ship
induced foam and to minimize shading / reflections by the ship‟s hull. One radiometer points to the sea
surface under an angle of 45 degrees with an azimuth angle of about 130-140 degrees with respect to the
sun. The second radiometer point to the sky under the same angles. The third radiometer measures the
downwelling irradiance. The water reflectance ρw (λ) is then computed according to:
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 w ( )  
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Lt ( , , )   f Lsky ( , , )
(37)
E s ( )
With Lt (λ) the total upward directed radiance from the water, Lsky (λ) the sky radiance, Es (λ) the
downwelling irradiance (above surface) and ρf the Fresnel reflection of water surface, computed according
to the Snell laws using a wavelength dependent on the refractive index for the mean salinity along the
transect.
Note: For our purpose we compute the directional water leaving radiance reflectance, RLw, without the PI
factor, then the unit is [sr-1], but in the delivered files the PI-factor is included for comparison with MERIS
data. Furthermore, water is sampled along each transect from the surface at about 6 stations, with the last
station (close to Helgoland) at the time of ENVISAT overpass. Water samples are processed at the end of
the cruise in the laboratory of the Biologische Anstalt on Helgoland.
Table 8-1 lists the transect dates for which data was provided to MERMAID, and the following variables
are determined:
1) phytoplankton pigment,
2) dry weight of total suspended matter,
3) dry weight of the inorganic and organic fraction of TSM,
4) absorption spectrum of the water after filtration with a pore size of 0.2 μm,
5) absorption spectrum of the filter pad before and after bleaching.
6) Furthermore, water temperature and salinity are recorded.
b)
a)
Figure 8-4: a) TRIOS-Spectrometer for measuring upward directed radiance from water and sky radiance,
and b) TRIOS Spectrometer for measuring downwelling irradiance
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Table 8-1: Number and dates of transect campaigns
Station
Ship
Date
Station
Ship
Date
C01
Wappen Von Hamburg
29/07/2002
C18
Südfall
20/04/2005
C02
Wappen Von Hamburg
30/07/2002
C19
Wappen Von Hamburg
21/04/2005
C03
Wappen Von Hamburg
14/08/2002
C20
Wappen Von Hamburg
23/06/2005
C04
Wappen Von Hamburg
15/08/2002
C21
Wappen Von Hamburg
13/07/2005
C07
Wappen Von Hamburg
03/09/2002
C22
Wappen Von Hamburg
17/08/2005
C08
Wappen Von Hamburg
17/07/2003
C23
Wappen Von Hamburg
01/09/2005
C09
Wappen Von Hamburg
05/08/2003
C24
Funny girl
06/10/2005
C10
Wappen Von Hamburg
06/08/2003
C25
Wappen Von Hamburg
13/10/2005
C11
Wappen Von Hamburg
17/09/2003
C26
Wappen Von Hamburg
08/05/2006
C12
Wappen Von Hamburg
28/07/2004
C27
Wappen Von Hamburg
11/05/2006
C13
Wappen Von Hamburg
03/08/2004
C28
Wappen Von Hamburg
12/06/2006
C14
Wappen Von Hamburg
05/08/2004
C29
Wappen Von Hamburg
04/07/2006
C15
Wappen Von Hamburg
06/08/2004
C30
Wappen Von Hamburg
13/07/2006
C16
Ludwig Prandtl
03-06/08/2004
C31
Wappen Von Hamburg
25/07/2006
C17
Wappen Von Hamburg
04/09/2004
C32
Wappen Von Hamburg
26/07/2006
8.4.3 Uncertainties
TBD
8.4.4 Key References
Doerffer, R. & Schönfeld, W. (2009).Validation Transect between Cuxhaven and Helgoland: GKSS
Technical Note (18th February 2009). GKSS, Germany.
8.5 MUMMTriOS. PI: K. Ruddick
The following protocol is extracted from Ruddick (2006), wherein further details can be found.
Measurements were performed with three TriOS-RAMSES hyperspectral spectroradiometers, two
measuring radiance, L, and one measuring downwelling surface irradiance Es. The instruments were
mounted on a steel frame as shown in Figure 8-5. Zenith angles of the sea- and sky-viewing radiance
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sensors were 40o. The frame was fixed to the prow of the ship, facing forward to minimize ship shadow
and reflection. The ship was maneuvered on station to point the radiance sensors at a relative azimuth
angle of 135o away from the sun. Lenses were checked and, if necessary, cleaned prior to each
measurement. Measurements were made for 10 min, taking a scan of the three instruments every 10 s.
The sensors measured over the wavelength range of 350–950 nm with a sampling interval of
approximately 3.3 nm and a spectral width of about 10 nm. Position was measured simultaneously by
global positioning system (GPS). Data were acquired with the TriOS GmbH MSDA software using the
file recorder function and radiometrically calibrated using nominal calibration constants. Calibrated data
for downwelling irradiance, Ed0+ (hereafter termed Es, by the definition provided in Section 1.4), sea
radiance, Lsea0+, and sky radiance, Lsky0+, were interpolated to 2.5 nm intervals. The sensors were
calibrated in a MERIS Validation Team laboratory every year, after which the definitive spectra were
obtained.
Water reflectance, ρw, is calculated from simultaneous above-water measurements of Es, total upwelling
radiance (i.e., from the water and from the air-sea interface) at a zenith angle of 40o, Lsea0+; and sky
radiance, Lsky0+, sea sky in the direction of the region of sky that reflects into the seaviewing sensor, by:
w  


L0sea
  f L0sky
(38)
Es
where ρf is the air-water interface reflection coefficient for radiance equal to the Fresnel reflection
coefficient in the case of a flat sea surface. This corresponds to „„Method 1‟‟ of the NASA protocols
(Mueller et al., 2000).
Figure 8-5 Frame with three TriOS-RAMSES hyperspectral radiometers as installed on the research vessel
Belgica (Ruddick, 2006).
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ρf is expected to vary strongly with wind speed for clear sky conditions because of reflection of brighter
parts of the sky in the case of higher waves (Mobley, 1999), but is approximately independent of wind
speed for cloudy conditions. This can be accounted for by switching between clear sky (Equation 39) and
cloudy sky (Equation 40) models for ρf, according to the ratio Lsky0+/Es at 750 nm, which takes a value of
about 0.02 in the clear sky simulations of Mobley (1999) but can reach much higher values (e.g., of order
0.3 for fully overcast conditions):
 f  0.0256  0.00039W  0.000034W
 f  0.256
2
for
for

L0sky
(750)
Es (750)

L0sky
(750)
Es (750)
 0.05
 0.05
(39)
(40)
The sunny sky formula of Equation 39 is derived as a function of wind speed, W, in meters per second at
height 10 m from the model simulations of Mobley (1999) based on the wave slope statistics of Cox and
Munk (1954). Although Mobley (1999) reports a slight sun zenith angle dependency for ρf, Equation 39
fits all simulations for the range 30o ≤ θ0 ≤ 70o to within 1% for W 5 m-s and to within 3% for W 10 m-s.
For the intermediate case of partially cloudy skies, whether obscuring the sun or patchy near the skyviewing direction, neither of these formulations is entirely appropriate. Although problematic for many
above-water reflectance measurements, this intermediate case is not relevant because such data are
removed from the analysis, as are the fully cloudy data where measurement uncertainties are more
significant.
8.5.1 Data Processing
Ruddick et al. (2006a) describe data processing procedures for MUMM optical measurements. The
measurement sequence of scanning every 10 s for 10 min produces a time series of 60 scans. ρw calculated
from these 60 scans will vary in time for a number of reasons such as wave and sunglint, bidirectionality,
water optical properties, tilt, floating material, clouds and skyglint, solar zenith angle. After inspection
and analysis of the time series recorded for stations in a wide variety of atmospheric and marine
conditions, the following approach for calculation of the ρw was adopted. Scans are flagged for rejection if
any of the following cases occurred:

Inclination from the vertical exceeded 5%;

Es, Lsea0+, Lsky0+ at 550 nm differs by more than 25% from either neighbouring scan; or

Incomplete or discontinuous spectra (occasional instrument malfunction).
In practice, scan rejection is low or zero for calm sea and clear sky conditions, but increases rapidly with
wind speed and/or if cloud cover is scattered and may reach 80% or more in the worst conditions. Next,
the ρw measured from the first five scans passing these tests are mean-averaged to yield the ρw and its
standard deviation for each station.
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Only stations meeting the following quality requirements were used:

Clear, sunny skies as denoted by the relation Lsky0+/Es (750) < 0.05,

Standard deviation of the five scans of reflectance was,10% of the mean average at 780 nm,

Wind speed, 10 m-s
8.5.2 Uncertainty Estimates for the NIR
Ruddick et al. (2006b) describe measurement uncertainty analyses and estimates. The uncertainty of
measurements of ρw(λ) and of the derived similarity spectrum  wn780 ( ) arising from the method
described in the main text is considered to arise from three main sources (Zibordi et al., 2002; Zibordi et
al., 1999): Instrument calibration and performance, correction for air-sea interface reflection, and optical
changes of the water induced by the measurement platform.
8.5.3 Key references
Cox, C. &Munk, W. (1954). Measurements of the Roughness of the Sea Surface from Photographs of the
Sun's Glitter. Journal of the Optical Society of America 44: 834-850.
Mueller, J. L., Davies, C., Arnone, R., Frouin, R., Carder, K. L., Lee, J. P., Steward, R. G., Hooker, S. B.,
Mobley, C. D. &McLean, S. (2000).Above-water Radiance and Remote Sensing Reflectance
Measurements and Analysis Protocols. In Ocean Optics Protocols for Satellite Ocean Cor Sensor
Validation. Rev 2.(Eds G. Fargion and J. L. Mueller). NASA.
Mobley, C. D. (1999). Estimation of the remote-sensing reflectance from above-surface measurements.
Applied Optics 38: 7442-7455.
Ruddick, K. (2006). Seaborne measurements of near infrared water-leaving reflectance: The similarity
spectrum for turbid waters. Limnology and Oceanography 51(2): 1167-1179.
Ruddick, K., De Cauwer, V., Park, Y. &Moore, G. F. (2006a). Web Appendix 1. Data Processing: Scan
Selection and Averaging. Limnology and Oceanography 51(2): 1167-1179.
Ruddick, K., De Cauwer, V., Park, Y. &Moore, G. F. (2006b). Web Appendix 2. Measurement
Uncertainty Analysis. Limnology and Oceanography 51(2): 1167-1179.
Zibordi, G., Doyle, J. P. &Hooker, S. B. (1999). Offshore Tower Shading Effects on In-water Optical
Measurements. Journal of Atmospheric and Oceanic Technology 16: 1767-1779.
Zibordi, G., Hooker, S. B., Berthon, J.-F. &D'Alimonte, D. (2002). Autonomous above water radiance
measurements from stable platforms. Journal of Atmospheric and Oceanic Technology 19: 808819.
8.6 Wadden Sea. PI: A. Hommersom
8.6.1 Introduction
The Wadden Sea, a shallow coastal area bordering the North Sea, is optically a complex area due to its
shallowness, high turbidity and fast changes in concentrations of optically active substances. Hommersom
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et al. (2009) describe the site and methodologies in detail, but here provide a summary of the
measurements contributed to MERMAID.
8.6.2 Measurement protocol and data processing
Reflectance
Reflectance, ρw (λ), spectra were calculated from measurements with three multi-spectral radiometric
sensors (TriOS). Two radiance sensors (RAMSES ARC; field of view of 7 o) were employed at the front
of the ship in azimuth ~135 º away from the sun. One sensor measured light that entered the water at an
angle of 41 º in zenith direction (sky radiance, Lsky). The other sensor measured at angle of 41º from nadir
direction, the light escaping the water (surface radiance, Lt). Foam, shadow and reflectance from the ship
were avoided; if necessary the 135 º azimuth angle was adjusted in an angle between > 90 ° and < 180 °.
The third sensor (RAMSES ACC, cosine) was employed on top of the ship and was used to measure
downwelling irradiance (Es). Measurements were carried out according to the Ocean Optics protocols
(Mueller et al., 2003a). The water-leaving radiance (Lw) was calculated as:
Lw ( )  Lt ( )   f Lsky ( )
(41)
Where: ρf is the surface reflectance, estimated with the information from Mobley (1999).
ρw (λ) was calculated according to Equation (3).
Chl
All samples were taken with a bucket. For Chl concentration measurements GF/F filters were used. After
filtration the filters were frozen at -20 °C and transferred to -80 °C in the lab within two weeks of taking
the first sample. Chl samples were analysed on HPLC, mainly according to the Ocean Optics protocol
(Mueller et al., 2003b), except for the solvent gradient program, which was modified to improve
separation. Peak areas were measured relative to the peak areas of a Chl standard in fresh water.
Concentrations of the standard were determined in acetone with a spectrophotometer. A correction is
applied for the amount of water that remains in a filter following Mueller et al. (2003b). In an experiment
the amount of water retained in a 47 mm GF/F filter was found to be 0.58 ml.
8.6.3 Uncertainties
Not yet available
8.6.4 Key References
Mobley, C. D. (1999). Estimation of the remote-sensing reflectance from above-surface measurements.
Applied Optics 38: 7442-7455.
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Muller, J. L., Morel, A., Frouin, R., Davies, C., Arnone, R. & Carder, K. L. (2003).Ocean Optics
Protocols for Satellite Ocean Color Sensor Validation, Revision 4, Volume III: Radiometric
Measurements and Data Analysis Protocols., 78 Greenbelt, MD: NASA/GSFC.
Tilstone, G. H., Moore, G. F., Sørensen, K., Doerffer, R., Røttgers, R., Ruddick, K., Pasterkamp, R. &
Jørgensen, P. V. (2002).REVAMP Regional Validation of MERIS Chlorophyll products in North Sea
coastal waters., 78 Plymouth: Plymouth Marine Laboratory.
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9. MERMAID PROTOCOLS VII: Miscellaneous datasets
9.1 NASA bio-Optical Marine Algorithm Data set (NOMAD). PI: Jeremy Werdell
9.1.1 Introduction
The NASA bio-Optical Marine Algorithm Data set (NOMAD) is a compilation of data provided to the
NASA SeaWiFS Bio-optical Archive and Storage System (SeaBASS), a repository for in-situ radiometric
and phytoplankton pigment data used by the NASA Ocean Biology Processing Group (OBPG). The data
is used in the satellite validation activities of the OBPG (Werdell and Bailey, 2002; Werdell et al., 2003),
and in particular for remote sensing studies. The NOMAD dataset is made available on the SeaBASS
website, and version 2.0 of the dataset is that included in the MERMAID database. Werdell and Bailey
(2005) describe in detail the NOMAD database, but here the information pertinent to MERMAID is
presented.
For NOMAD, the relevant parameters for MERMAID are Lw (λ) and Es (λ), from which ρw (λ) is
computed.
9.1.2 Measuring systems and protocols
Approximately 15,000 radiometric observations were acquired from SeaBASS for NOMAD. The
radiometric data sources include in-water profiling instruments and handheld or platform mounted abovewater instrumentation. Measurements from both multi- and hyperspectral resolution instruments are
included; see Werdell and Bailey (2005) and Werdell (2005) and references therein for details.
Consistency in the data was facilitated by a requirement to adhere to pre-specified in-situ data
requirements and sampling strategies (Mueller et al., 2003a), namely the NASA Ocean Optics Protocols,
or similarly appropriate methods documented by the provider.
The data received by the OPBG is fully processed to depth-registered, calibrated geophysical values by
the data contributor prior to inclusion in SeaBASS and, apart from outliers (queried of the contributor) or
uncertain methods, were considered accurate (Werdell and Bailey, 2005).
9.1.3 Data processing to Lwn (λ)
NOMAD consists of radiometric profiles limited to those with coincident observations of upwelling
radiance, Lu (λ, z) and downwelling irradiance, Ed (λ, z), and if available measurements of surface
irradiance, Es (λ,0+), usually collected near-simultaneously either on the deck of the vessel or nearby
buoy.
The OBPG use especially-designed software (Werdell and Bailey, 2002) to visualise and process the data.
Measurements without near-surface profiler data (less than 5m) or without significant overall stability in
the reference surface irradiance were excluded. All remaining measurements of radiance and irradiance
were corrected for variations in solar irradiance using a surface reference value if available and not
performed prior to data submission. Contaminated observations, for example those resulting from wave
focusing near the surface or high tilt, were removed from the profiles. Werdell and Bailey (2005) provide
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no further detail regarding exclusion of tilt-affected data. Data collected under non-ideal, or cloudy, sky
conditions are not excluded from NOMAD.
Near-surface diffuse attenuation coefficients were calculated by the OBPG from the radiance and
irradiance profiles via a linear exponential fit to the corrected data. These coefficients were used to
propagate the radiances and irradiances to just beneath the surface, Lu(0-) and Ed(0-), respectively.
Water leaving radiances were then determined using Equation (11), and using a value of 0.975 for the
Fresnel transmittance term and 1.34 for n.
Similarly, extrapolated surface irradiances were computed as
Es  t d
1
Ed (0  )
(42)
Where td is the downward Fresnel irradiance transmittance across the air-sea interface (0.96; Mueller et
al., 2003c).
Observations were considered questionable and discarded if extrapolated surface irradiances could not be
reconciled with reference surface irradiances (extrapolated Es). Intermediate processing details were
logged, including the extrapolation depth intervals, which were occasionally variable as a function of
wavelength, extrapolation statistics, cast direction, and processor-defined comments.
The remote sensing diffuse attenuation coefficient
Gordon and McCluney (1975) demonstrated that 90% of remotely sensed radiance originates in the upper
layer, defined by depth z90, corresponding to the first optical attenuation length as defined by Beer‟s Law.
Measurements of Ed (k, z) were smoothed using a weighted least-square polynomial fit. Using the
smoothed data and the previously calculated subsurface irradiance, values for z90(k) were identified as the
depth which satisfied the condition
Ed (k , z90 )  Ed (k ,0  ) e 1
(43)
Remote sensing diffuse attenuation coefficients, Krs(k), were calculated from the original irradiance
profiles by applying a linear exponential fit over the depth range from z = 0 - to z90(k). Radiometric
profiles with retrieved Krs(k) values less than the value for pure water (Kw(490)=0.016 m-1; Mueller,
2000) were considered questionable and discarded. Otherwise, both Krs(k) and z90(k) were recorded.
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Above-water radiometry
Above-water measurements of surface and sky radiance under known geometric conditions may be used
to derive water-leaving radiances (Deschamps et al., 2004; Mobley, 1999). Contributors of above-water
radiometric observations performed this derivation prior to submission to SeaBASS, thus eliminating the
need for additional data preparation. For 12% of these field campaigns (relating to 39% of all above-water
observations), the data contributor provided remote sensing reflectances, RRS (λ), in lieu of Lw (λ). In these
cases, water-leaving radiances were estimated from remote sensing reflectances via:
Lw ( )  Rrs ( ) Es ( )
(44)
If Es (λ) was not explicitly provided, they were derived using a clear sky model based on Frouin et al.
(1989); this is an operation requiring an assumption of ideal sky conditions at the time of data collection.
The uncertainty introduced by such an assumption will be minimal when developing algorithms using
radiance ratios, as the modeled Es (λ) are, in general, spectrally flat. That is, the ratio of any two discrete
modeled irradiance values is approximately unity, and, following, the errors associated with the
magnitude of the modeled irradiances are mathematically cancelled. Uncertainty will also be negligible
for satellite validation activities, where only the clearest days are considered (Werdell et al., 2003). While
uncertainties associated with above-water radiometry may be significant even under ideal conditions
(Hooker et al., 2002) data collected onboard underway research vessels are included in the dataset if
located in an otherwise under-sampled bio-regime (Werdell and Bailey, 2005).
To mimic the band passes inherent to most commercially available multispectral radiometers, data
collected with hyperspectral instruments were degraded to 11-nm averages centred on λc, as defined by:

)
 c 5
X ( c
i  5
X ( i )
(45)
n
where: X is some radiometric quantity, such as RRS, and n is the number of wavelengths considered (i.e.
11).
Radiometric data reduction
All replicate radiometric measurements were individually viewed and reduced via analysis of coincident
Lw (λ), Es (λ), and RRS (λ), the combined evaluation of which provides simultaneous insight into
processing artefacts, changing sky conditions, and water-mass variability that results from erroneous
replicate identification. For example, for a given station with multiple measurements, comparable surface
irradiance spectra indicate stable sky conditions and similar RRS (λ) implies a consistent water mass.
Under ideal circumstances, when the statistical variance of all three products was low, the geometric
mean was calculated. If only the RRS (λ) were stable, we retained the single observation with the highest
Es (λ), an indicator of the clearest sky conditions. Stable Es (λ) and highly variable Lw (λ) suggested errors
in data processing or replicate evaluation (e.g. insufficiently small spatial thresholds for frontal regions).
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Data with these symptoms were re-evaluated, and discarded upon unsuccessful reconciliation. For all of
the above, the average observation time, latitude, and longitude were recorded.
Exceptions
Naturally, the volume of data considered and the wide range of sources prompted several exceptions to be
made in how specific data were treated. SeaBASS data contributors occasionally provided Lw (λ) that
included a correction for instrument self-shading (Zibordi & Ferrari, 1995), either without providing the
radiance profiles, or with a documented perspective in favour of the correction for their particular field
campaign. NOMAD therefore excludes all radiometric data collected solely on tethered buoys (e.g., the
Satlantic, Inc. Tethered Spectral Radiometry Buoy) and moorings, as these data are predominantly scarce
in SeaBASS and, when available, rarely includes supporting radiometric information for use in the
extrapolation of Lu (k, z) to Lu (k, 0-).
Wavelength generalisation
Lw (λ), Es (λ) and Kd coefficients retain their native instrument-resolution in the RDBMS, for example,
Lw(411.8) is not rounded to Lw(412), yielding approximately 250 uniquely catalogued wavelengths. In
general, such exact radiometric precision is not required for algorithm development (O'Reilly et al., 2000;
O'Reilly et al., 1998) so to simplify the data for generalised and efficient use, wavelengths are rounded in
each data export process. A series of 21 nominal wavelengths are predefined after both reviewing the
spectral resolution of past, present, and future ocean colour satellites and considering the frequency of
occurrence of centre wavelengths in the merged data set. When exported from the database, radiometric
data are assigned the predefined wavelength, λpd, that satisfies the condition (λpd-2-nm)_kn_(λpd+2-nm),
where λn is the native instrument wavelength.
9.1.4 Quality assurance
The volume of data considered and the range of sources prohibit comprehensive description of data
sampling in this article. However, Werdell and Bailey (2005) provide the following description. Data are
fully processed to depth-registered, calibrated geophysical values by the data contributor prior to
inclusion in SeaBASS, thus eliminating the need for any additional calibration or normalisation efforts.
Data contributors were queried when outliers and questionable measurements were identified, or when
data processing methods or instrument calibrations were uncertain. Otherwise, the data were considered
accurate as is, following acquisition from SeaBASS. To facilitate the post-processing evaluation of
uncertainties resulting from varying observation types and measurement resolutions (such as in-water
versus above-water radiometry, or analysis of water samples collected via profiling rosettes versus
shipboard sea chests), the OBPG established a series of binary flags to record collection and processing
details for each measurement. As such, a flag field accompanies every measurement in the final compiled
data set.
9.1.5 Uncertainties
Upwelling radiances were not corrected for instrument self-shading (Gordon and Ding, 1992; Zibordi and
Ferrari, 1995), as the required supporting data were often inadequate (such as the absorption coefficient of
the water mass and the ratio between diffuse and direct sun irradiance). The uncertainty introduced by
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omitting this correction varies geographically and temporally and by instrument. Uncertainties are
generally between 5 and 9%.
9.1.6 Key References
Austin, R. W. (1974).The remote sensing of spectral radiance from below the ocean surface. In Optical
Aspects of Oceanography, 317-344 (Eds N. G. Jerlov and E. Steemann-Nielsen). New York: Academic
Press, London.
Deschamps, P.-Y., Fougnie, B., Frouin, R., Lecomte, P. & Verwaerde (2004). SIMBAD: A Field
Radiometer for Satellite Ocean-Color Validation. Applied Optics 43(20): 4055-4069.
Frouin, R., Longner, D. W., Gautier, C., Baker, K. S. & Smith, R. C. (1989). A simple analytical formula
to compute clear sky total and photosynthetically available solar irradiance at the ocean surface. Journal
of Geophysical Research 94: 9731-9742.
Gordon, H. R. & Ding, K. (1992). Self-shading of in-water optical instruments. Limnology and
Oceanography 37(3): 491-500.
Gordon, H. R. & McCluney, W. R. (1975). Estimation of depth of sunlight penetration in sea for remotesensing. Applied Optics 14: 413-416.
Hooker, S. B., Lazin, G., Zibordi, G. & McClean, S. (2002). An evaluation of above- and in-water
methods for determining water leaving radiances. Journal of Atmospheric and Oceanic Technology 19:
486-515.
Mobley, C. D. (1999). Estimation of the remote-sensing reflectance from above-surface measurements.
Applied Optics 38: 7442-7455.
Mueller, J. L. (2000).SeaWiFS algorithm for the diffuse attenuation coefficient, K(490), using waterleaving radiances at 490 and 555 nm In SeaWiFS postlaunch calibration and validation analyses: Part 3.
NASA Technical Memorandum, Vol. 11, 24-27 (Eds S. B. Hooker and E. R. Firestone). Greenbelt,
Maryland, USA.: NASA Goddard Space Flight Centre.
Mueller, J. L., Morel, A., Frouin, R., Davies, C., Arnone, R. & Carder, K. L. (2003c).Ocean Optics
Protocols for Satellite Ocean Color Sensor Validation, Revision 4, Volume III: Radiometric
Measurements and Data Analysis Protocols., 78 Greenbelt, MD: NASA/GSFC.
O'Reilley, J., Maritorena, S. A., O'Brien, M. C., Siegel, D. A., Toole, D. & Menzies, D. (2000).Ocean
Color Chlorophyll a algorithms for SeaWiFS, OC2 and OC4: Version 4. . In SeaWiFS Postlaunch
Calibration and Validation Analysis:, 9-23 (Eds S. B. Hooker and E. R. Firestone). Greenbelt, MD:
NASA.
O'Reilly, J. E., Maritorena, S., Mitchell, B. G., Siegel, D. A., Carder, K. L., Garver, S. A., Kahru, M. &
McClain, C. R. (1998). Ocean Color Algorithms for SeaWiFS. Journal of Geophysical Research 103:
24,937-924,953.
Werdell, P. J. &Bailey, S. W. (2002).The SeaWiFS Bio-optical Archive and Storage System (SeaBASS):
Current Architecture and Implementation. Greenbelt, Maryland.: NASA Goddard Space Flight Centre.
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Werdell, P. J. &Bailey, S. W. (2005). An Improved In situ Bio-Optical Data Set for Ocean Colour
Algorithm Development and Satellite Data Product Validation. Remote Sensing of Environment 98: 122140.
Werdell, P. J., Bailey, S. W., Fargion, G., Pietras, C. M., Knobelspiesse, K., Feldman, G. C. &al., e.
(2003). Unique data repository facilitates ocean color satellite validation. EOS Transactions 84(3): 379.
Zibordi, G. & Ferrari, G. M. (1995). Instrument self-shading in underwater optical measurements:
experimental data. Applied Optics 34: 2750-2754.
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10. Appendix 1: Values of the air-sea interface transmittance as function of
wind speed, ws, view angle, ', and salinity (salt and freshwater).
Table 10-1: Air-sea interface transmittance (35 psu).
Wind force
1
ms-1
0.25
'
0.534647
0
2
1.00
3
2.75
4
5.00
0.537108
0.532993
0.533324
15
0.534633
0.537071
0.532907
0.533184
30
0.534622
0.537041
0.532841
0.533079
45
0.534611
0.537012
0.532777
0.53298
60
0.534608
0.537004
0.532761
0.532955
0
0.534641
0.537093
0.53296
0.533274
15
0.534623
0.537045
0.532852
0.533098
30
0.53461
0.537009
0.532773
0.532974
45
0.534597
0.536975
0.532697
0.532857
60
0.534593
0.536965
0.532678
0.532827
0
0.540606
0.542336
0.541859
0.53747
15
0.540583
0.542275
0.541721
0.537255
30
0.540567
0.542233
0.541627
0.53711
45
0.540551
0.542193
0.541537
0.536974
60
0.540547
0.542182
0.541515
0.536941
0
0.540603
0.542328
0.54184
0.537441
15
0.540578
0.542262
0.541692
0.537211
30
0.540561
0.542218
0.541594
0.53706
45
0.540544
0.542175
0.5415
0.536918
60
0.54054
0.542164
0.541477
0.536884
0
0.540602
0.542326
0.541834
0.537431
Band 5
15
0.540575
0.542255
0.541677
0.537188
559.694
30
0.540557
0.542209
0.541575
0.537032
45
0.54054
0.542164
0.541478
0.536886
Band 1
412.691
Band 2
442.559
Band 3
489.882
Band 4
509.819
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60
0.540536
0.542153
0.541454
0.53685
0
0.544808
0.543715
0.542217
0.543843
15
0.544778
0.543641
0.542055
0.543587
30
0.54476
0.543596
0.541953
0.543426
45
0.544743
0.543551
0.541855
0.543276
60
0.544738
0.54354
0.541831
0.54324
0
0.544809
0.543716
0.542219
0.543846
15
0.544778
0.54364
0.542053
0.543584
30
0.54476
0.543594
0.54195
0.543422
45
0.544742
0.543549
0.541851
0.54327
60
0.544737
0.543537
0.541827
0.543234
0
0.544809
0.543717
0.54222
0.543847
15
0.544778
0.543639
0.542052
0.543583
30
0.54476
0.543594
0.541949
0.543421
45
0.544742
0.543548
0.54185
0.543269
60
0.544737
0.543537
0.541826
0.543233
0
0.549592
0.545889
0.546687
0.545824
15
0.549559
0.54581
0.546515
0.545561
30
0.54954
0.545764
0.546411
0.545399
45
0.549521
0.545718
0.54631
0.545248
60
0.549517
0.545706
0.546285
0.545211
0
0.549592
0.545889
0.546686
0.545823
15
0.549559
0.54581
0.546515
0.54556
30
0.54954
0.545764
0.54641
0.545399
45
0.549521
0.545717
0.54631
0.545247
60
0.549517
0.545706
0.546285
0.545211
0
0.549592
0.545889
0.546686
0.545823
Band 12
15
0.549559
0.54581
0.546515
0.54556
778.4091
30
0.54954
0.545764
0.54641
0.545399
45
0.549521
0.545717
0.54631
0.545247
Band 6
619.601
Band 7
664.5731
Band 8
680.821
Band 9
708.329
Band 10
753.371
All rights reserved, ARGANS Ltd
2011
MERIS
Optical
Measurement
Protocols
Band 13
864.876
Band 14
884.944
Doc
Name
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: July 2011
Issue
Date
PAGE : 91
60
0.549517
0.545706
0.546285
0.545211
0
0.549592
0.545889
0.546686
0.545823
15
0.549559
0.54581
0.546515
0.54556
30
0.54954
0.545764
0.54641
0.545399
45
0.549521
0.545717
0.54631
0.545247
60
0.549517
0.545706
0.546285
0.545211
0
0.549592
0.545889
0.546686
0.545823
15
0.549559
0.54581
0.546515
0.54556
30
0.54954
0.545764
0.54641
0.545399
45
0.549521
0.545717
0.54631
0.545247
60
0.549517
0.545706
0.546285
0.545211
Table 10-2: Air-sea interface transmittance (0 psu).
Wind force
1
2
3
4
ms-1
0.25
1.00
2.75
5.00
0
0.540214
0.5427
0.538542
0.538877
15
0.5402
0.542663
0.538455
0.538735
30
0.540188
0.542632
0.538389
0.538629
45
0.540177
0.542603
0.538325
0.53853
60
0.540174
0.542595
0.538308
0.538504
0
0.540163
0.54264
0.538464
0.538781
15
0.540145
0.542591
0.538355
0.538604
30
0.540131
0.542555
0.538275
0.538478
45
0.540118
0.54252
0.538199
0.53836
60
0.540115
0.542511
0.538179
0.53833
'
Band 1
412.691
Band 2
442.559
All rights reserved, ARGANS Ltd
2011
MERIS
Optical
Measurement
Protocols
Band 3
489.882
Band 4
509.819
Band 5
559.694
Band 6
619.601
Band 7
664.5731
Band 8
680.821
Doc
Name
Issue
Date
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: July 2011
PAGE : 92
0
0.546129
0.547876
0.547394
0.542961
15
0.546105
0.547815
0.547255
0.542743
30
0.546089
0.547773
0.54716
0.542596
45
0.546073
0.547731
0.54707
0.54246
60
0.546069
0.547721
0.547047
0.542426
0
0.546103
0.547845
0.547352
0.542909
15
0.546077
0.547779
0.547204
0.542677
30
0.546061
0.547735
0.547104
0.542524
45
0.546044
0.547692
0.54701
0.542381
60
0.54604
0.54768
0.546986
0.542346
0
0.546054
0.547795
0.547298
0.54285
15
0.546026
0.547723
0.547139
0.542605
30
0.546008
0.547676
0.547036
0.542447
45
0.545991
0.547631
0.546938
0.5423
60
0.545986
0.54762
0.546914
0.542264
0
0.550253
0.549149
0.547636
0.549279
15
0.550223
0.549074
0.547472
0.54902
30
0.550205
0.549028
0.547369
0.548857
45
0.550187
0.548983
0.54727
0.548705
60
0.550182
0.548972
0.547246
0.548669
0
0.550222
0.549119
0.547608
0.54925
15
0.550191
0.549042
0.547439
0.548986
30
0.550173
0.548996
0.547335
0.548822
45
0.550155
0.54895
0.547236
0.548669
60
0.55015
0.548939
0.547211
0.548632
0
0.550212
0.54911
0.547598
0.549241
15
0.550181
0.549032
0.547429
0.548975
30
0.550163
0.548985
0.547325
0.548811
45
0.550145
0.548939
0.547224
0.548657
60
0.55014
0.548928
0.5472
0.548621
All rights reserved, ARGANS Ltd
2011
MERIS
Optical
Measurement
Protocols
Band 9
708.329
Band 10
753.371
Band 12
778.4091
Band 13
864.876
Band 14
884.944
Doc
Name
Issue
Date
: CO-SCI-ARG-TN-008
: MERIS Optical Measurement
Protocols. Part A: Reflectance
: 2.0
Rev.:
1.0
: July 2011
PAGE : 93
0
0.555027
0.551287
0.552093
0.551221
15
0.554994
0.551207
0.55192
0.550956
30
0.554975
0.551161
0.551814
0.550792
45
0.554956
0.551114
0.551712
0.550639
60
0.554951
0.551102
0.551687
0.550603
0
0.555003
0.551263
0.552068
0.551197
15
0.554969
0.551183
0.551895
0.550931
30
0.55495
0.551137
0.551789
0.550768
45
0.554931
0.55109
0.551688
0.550615
60
0.554926
0.551078
0.551663
0.550578
0
0.554991
0.551251
0.552056
0.551185
15
0.554957
0.551171
0.551883
0.550919
30
0.554938
0.551124
0.551777
0.550756
45
0.554919
0.551078
0.551676
0.550603
60
0.554914
0.551066
0.551651
0.550566
0
0.554954
0.551214
0.552019
0.551148
15
0.55492
0.551134
0.551846
0.550882
30
0.554901
0.551088
0.55174
0.550719
45
0.554882
0.551041
0.551639
0.550566
60
0.554877
0.551029
0.551614
0.55053
0
0.554946
0.551207
0.552012
0.55114
15
0.554913
0.551127
0.551839
0.550875
30
0.554894
0.55108
0.551733
0.550711
45
0.554874
0.551033
0.551631
0.550558
60
0.55487
0.551022
0.551606
0.550522
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