Download A practical guide to IR and MW radiative transfer using the

A practical guide to IR and MW
radiative transfer using the
RTTOV model
What is atmospheric radiative transfer?
• Study of the of the propagation of electromagnetic
radiation through the atmosphere which involves
interactions with atmospheric constituents (gas
molecules, aerosols, clouds, hydrometeors) and the
surface.
• From a data assimilation perspective an RT model is the
observation operator for assimilating passive visible/nearinfrared, infrared and microwave satellite radiances into
NWP models.
• RT models take NWP fields (p, T, q, trace gas profiles
and surface variables) as input and calculate TOA
satellite-seen radiances.
Radiation-particle interactions
(1) Absorption: radiation attenuation of by
energetic modification (heat or chemical
reaction)
(2) Emission: isotropic increase in radiation by
molecular excitation due to absorption
(Kirchhoff’s law: emissivity = absorptivity)
(3) Scattering: radiation attenuation by deviation
of radiation from original direction; also increase
in radiation by deviation of radiation into
direction under consideration
(3)
(1)
(3)
(2)
What is RTTOV?
RTTOV = Radiative Transfer for TOVS
TOVS = TIROS Operational Vertical Sounder
TIROS = Television Infrared Observation Satellite
(RTTOV has been around for ~25 years)
What is RTTOV?
• A fast radiative transfer model for passive
VIS, IR and MW nadir-viewing instruments.
• Funded by EUMETSAT through the
NWP SAF, developed by Met Office,
Météo-France and ECMWF.
• Direct, TL, AD, K models.
• Applications: data assimilation, reanalysis,
simulated imagery, 1D-VAR, ...
RTTOV v11: >500 users
RTTOV v10: >600 users
RTTOV inputs
• Vertical profiles of p, T, q
• Other optional trace gases:
O3, CO2, CO, N2O, CH4
• Viewing geometry (zenith and azimuth
angles)
• Surface variables:
skin T, surface pressure, 10m wind u/v
• Surface emissivity (optional)
Transmittance
L
L
  [0,1]
extinction
(absorption)
  1  transparent
  0  opaque
Transmittance is related to optical depth by  = e-(optical depth)
Clear-sky RT equation

L
frequency

transmittance from TOA*
s
transmittance from TOA* to surface
radiance
T
temperature
Ts
surface skin temperature
B
Planck function
s
surface emissivity
L( ) 
1
1
s
s
2


(

)

(

)
B
(

,
T
)
B
(

,
T
)
d


(1


(

))

s
s
s
s
s ( ) 

upwelling
atmospheric
emission
surface
emission
B ( , T )
d
2

downwelling
atmospheric emission
reflected by surface
The computationally challenging term to calculate accurately is the
transmittance  or equivalently the optical depth where  = e-(optical depth)
*TOA = top of atmosphere
Weighting functions
Transmittance  varies monotonically with height z.
We can write the upwelling emission term as:
1

L( )   B( , T )d   B( , T )
s
Weighting function:
0
w( z ) 

dz
z

z
14
13
The upwelling emission is an integral of the
Planck function weighted by w(z).
12
11
The largest contribution comes from the region
where w(z) is largest i.e. where  changes
most rapidly with height.
AMSU-A:
50-57 GHz
channels
10
9
8
7
6
5
4
Polychromatic channels
Passive IR/MW sensor channels are not monochromatic.
Ideally we would solve the RT equation at many
wavelengths and integrate the resulting radiances over the
channel spectral response function (SRF).
In practice we integrate transmittances over the SRF and
solve the RT equation once per channel.
Line-by-line (LBL) models
LBL models embody the physics behind the
absorption processes
=> accurate, but slow.
Line-by-line (LBL) models
LBL models embody the physics behind the
absorption processes
=> accurate, but slow.
Key idea:
RTTOV parameterises off-line LBL
calculations of optical depths to enable very
rapid optical depth calculations for each
instrument channel.
RTTOV optical depth calculation
• 83 diverse atmospheric profiles each at 6
zenith angles => 498 training profiles.
RTTOV optical depth calculation
• 83 diverse atmospheric profiles each at 6
zenith angles => 498 training profiles.
• Divide atmosphere into 53* layers defined
by 54 fixed pressure levels.
*For hi-res sounders we also produce coefficients for 100 layers/101 levels.
RTTOV optical depth calculation
• 83 diverse atmospheric profiles each at 6
zenith angles => 498 training profiles.
• Divide atmosphere into 53* layers defined
by 54 fixed pressure levels.
• Calculate database of LBL optical depths
for each layer at high spectral resolution
for each training profile.
*For hi-res sounders we also produce coefficients for 100 layers/101 levels.
RTTOV optical depth calculation
Define a set of atmospheric “predictors”
derived from input profile variables
=> there are separate sets of predictors for
the optical depth due to mixed gases, water
vapour and each additional trace gas.
RTTOV optical depth calculation
Define a set of atmospheric “predictors”
derived from input profile variables
=> there are separate sets of predictors for
the optical depth due to mixed gases, water
vapour and each additional trace gas.
Integrate the LBL optical depths in each layer
over each instrument channel SRF for every
training profile.
RTTOV optical depth calculation
Regress layer optical depths onto predictors (pi)
for each channel
=> coefficients (ci) which are stored in a file for
each instrument
Optical depth calculation:
Optical depth due to
mixed gases*
Total layer =
optical depth
n mg
c
i 1
mg
i
pimg
Optical depth due to
water vapour*

n wv
c
i 1
wv
i
piwv
Optical depth due to
ozone*

* strictly speaking these are “pseudo” optical depths (RTTOV science and validation reports give more details)
no 3
c
i 1
o3
i
pio 3
RTTOV flow diagram
Input profile on N
levels and surface
parameters
Interpolate profile onto
54 fixed levels
Calculate predictors
on 53 layers
Instrument
coefficients
internal RTTOV
calculations
Multiply predictors by
coefficients for each channel
=> layer optical depths for
each channel
Interpolate optical depths
to N user levels
Optional surface
emissivity calculation
Integrate RT equation
for each channel
Output radiances
and BTs
Implications for accuracy
Sources of error:
• Use of polychromatic optical depths
Implications for accuracy
Sources of error:
• Use of polychromatic optical depths
• Optical depth parameterisation (regression)
Implications for accuracy
Comparison of TOA BTs from a simple forward RT model (upwelling emission
plus surface term with unit emissivity) run with:
• LBL channel-integrated optical depths
• RTTOV optical depths (from predictor regression)
Implications for accuracy
Sources of error:
• Use of polychromatic optical depths
• Optical depth parameterisation (regression)
• Discretisation of atmosphere into homogenous
layers and associated interpolation
Implications for accuracy
Sources of error:
• Use of polychromatic optical depths
• Optical depth parameterisation (regression)
• Discretisation of atmosphere into homogenous
layers and associated interpolation
• Input profiles values (including zenith angle) lying
beyond the limits of the training set
Jacobian (K) model
This calculates the derivatives of the simulated radiances or
BTs with respect to each profile variable. For example:
profile variables:
L L L
,
,
,...
Ti qi O3i
and surface parameters:
for 1 <= i <= nlevels
L L
,
,...
Ts  s
It tells us how sensitive the satellite-seen radiance is to each
individual profile variable.
Use of Jacobian
Satellite observations in a number of channels
Use of Jacobian
Satellite observations in a number of channels
Assume a priori (background) atmospheric
state
Use of Jacobian
Satellite observations in a number of channels
Assume a priori (background) atmospheric
state
Run direct RT model to get simulated
observations using background
Use of Jacobian
Satellite observations in a number of channels
Assume a priori (background) atmospheric
state
Run direct RT model to get simulated
observations using background
Jacobians are then used to modify the
background in such a way as to make the
simulations match the obs more closely
RTTOV capabilities
• Clear-sky visible/near-IR, IR and MW radiances
• Internal sea surface emissivity and reflectance
models
• Land surface emissivity and reflectance atlases
• Aerosol- and cloud-affected IR radiances
• Cloud- and precipitation-affected MW radiances
• Simulated Principal Components for hi-res IR
sounders
• and more...
How to get RTTOV
Freely available, simply register here:
http://nwpsaf.eu/deliverables/rtm/index.htm
Coefficient files are available here:
http://nwpsaf.eu/deliverables/rtm/rttov11_coefficients.html
RTTOV forum:
http://www.nwpsaf.eu/forum/
Questions?
Practical
Start up the RTTOV GUI with
Click on green creature (bottom left of
screen then open up a terminal window).
On the command line type:
rttovgui
GUI Example 1 – AMSU-A
•
•
•
•
•
Loading coefficients
Loading a profile
Running the direct model
Modifying a profile
Comparing output from multiple runs
AMSU-A weighting functions
Channels sensitive to the surface
AMSU-A weighting functions
Channels insensitive to the surface
GUI Example 2 - IASI
• Running the direct model for a hi-res IR
sounder
• Running the K model
• Interpreting the output
• Look at ozone Jacobian in ch1640
• Look at water vapour Jacobian in ch3450