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CESAR Science day, 19 June, 2013
Application of Cloudnet
data in the validation of
SCIAMACHY cloud height
products
Ping Wang
Piet Stammes
KNMI, De Bilt, The Netherlands
Overview
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SCIAMACHY cloud products
Cloud retrieval algorithms from O2 A band
Validation data sets
Results
Summary
SCIAMACHY cloud products
• ESA L2 (v5.02)
Cloud top height and Cloud optical thickness
are retrieved from SACURA. Cloud optical
thickness is only retrieved for thick clouds,  > 5.
Cloud fraction is retrieved from PMDs (OCRA).
• FRESCO (v6)
Effective cloud fraction and cloud height are
retrieved from FRESCO. The cloud height is close
to the middle of the cloud.
FRESCO: Fast Retrieval Scheme for Clouds from the
Oxygen A band
FRESCO cloud algorithms
Lambertian cloud model
Cloud data sets of SCIAMACHY
Data: ESA level-2, version 5.02,
FRESCO, version 6
• Intercomparison data set
- one orbit per month from 2002 to 2012,
including 4 full day of data (~160 orbits).
• Validation data set
- SCIAMACHY overpass pixels at Cabauw (20032005) and Lindenberg (2005-2012).
(~700 measurements)
Distributions of the differences
(L2 –FRESCO)
Cloud fraction
Cloud height
Mean difference -0.0225
Standard deviation 0.100
Mean difference 0.609 km
Standard deviation 2.16 km
Cloudnet data
Instruments:
Radar :
large particles such as rain and drizzle drops,
ice particles, and insects
Lidar : higher concentrations of smaller particles, such as
cloud droplets, aerosol, supercooled liquid layers
Microwave radiometer: liquid water path
Rain gauge: precipitation
Cloudnet cloud top height, cloud base height and target
categorization data are selected for one hour, centered at
SCIAMACHY overpass time.
Illingworth et al., BAMS, 2007.
http://www.cloud-net.org
Cloudnet categorization product
Ice cloud
Cloud top
Water cloud
Cloud base
height
Cabauw:
0.253-11.5km,
Lindenberg: 0.355-15.2km,
grid
time resolution
90m (126 levels),
30m (495 levels),
15s (240 /hr)
30s (120 /hr)
Cloudnet categorization product
Ice cloud
Cloud top
Water cloud
Cloud base
height
Cabauw:
0.253-11.5km,
Lindenberg: 0.355-15.2km,
grid
time resolution
90m (126 levels),
30m (495 levels),
15s (240 /hr)
30s (120 /hr)
Cloud top of ESA L2 vs. Cloudnet:
single layer clouds
All
clouds
water
clouds
Color scale: ESA L2 cloud fraction
ice
clouds
Cloud height of FRESCO vs. Cloudnet
cloud top: single layer clouds
All
clouds
water
clouds
ice
clouds
Color scale: FRESCO effective cloud fraction
SCIA cloud heights and Cloudnet cloud
boundaries: single layer clouds, ceff>0.1
SCIAMACHY and Cloudnet cloud heights: single
layer clouds, ceff>0.1
SCIAMACHY cloud height vs. Cloudnet
cloud top: multi-layer clouds
ESA L2 cloud
top height
FRESCO
cloud height
SCIAMACHY and Cloudnet cloud heights:
Multi-layer clouds
Summary (1)
SCIAMACHY ESA L2 v5.02 cloud fractions are similar to
FRESCO v6 effective cloud fractions. For the selected data
from 200210 to 201204, the mean difference is -0.0225 and
the standard deviation is 0.10.
SCIAMACHY ESA L2 v5.02 cloud top height is higher than
FRESCO cloud height. The mean difference of cloud heights is
0.609 km with a standard deviation of 2.16 km for pixels
without snow/ice.
Summary (2)
We compared ESA L2 and FRESCO cloud heights with
Cloudnet products for 220 single layer cloud cases in 20032011.
For single layer clouds,
ESA L2 cloud top height is close to lidar/radar cloud top
height for clouds at 3-7 km.
FRESCO cloud height is close to lidar/radar cloud middle
height for clouds below 5 km.
Acknowledgment
We would like to thank Henk Klein-Baltink (KMNI) for helpful
discussions.
We acknowledge the Cloudnet project (European Union contract
EVK2-2000-00611) for providing the target classification and
cloud boundaries, which was produced by the University of
Reading using measurements from Cabauw and Lindenberg.