Caroline Poulsen
ATSR

2 Group
Cloud parameters estimated by
variational analysis of visible and
infrared measurements from ATSR

2
Caroline Poulsen, Richard Siddans, Barry Latter and
Brian Kerridge, Chris Mutlow, Sam Dean
2
, Don
Grainger
2
, Gareth Thomas
2
, Graham Ewen
2
and
Phil Watts
1
Space Science and Technology Department
Rutherford Appleton Laboratory
UK
1.
Now at EUMETSAT
2.
Oxford University
Outline
Why use ATSR?
Why Variational Analysis?
Forward Model
Examples
Validation
Level 3 products
Future
ATSR Channels
ATSR2/AATSR
•
0.55um
•
0.67um
•
0.87um
•
1.6um
•
3.7um
•
11um
•
12um
Cloud Parameters Retrieved
•
Cloud top pressure/height
•
Cloud fraction
•
Cloud optical depth
•
Cloud effective radius
•
Cloud phase
Auxillary information
•
ECMWF T and q profiles
•
MODIS surface albedo
Aerosol Parameters Retrieved
•
Aerosol optical depth
•
Aerosol effective radius
Comparing measurements with
calculations: Ice, water and mixed
phase
water
ice
Why use Optimal Estimation?
•
Basic principle is to maximise the accuracy the retrieved cloud
parameters based on the measurements and any ‘apriori’
•
Allows us to characterise the error in each cloud parameter
under the assumption of a reasonably plane parallel cloud model
•
It’s a very flexible approach that enables us to utilise any prior
information, for example on cloud fraction. All the clear sky
atmospheric effects can be derived from NWP profiles.
•
Allows us to utilise ALL the information in the measurements for
each channel contributes to a greater or lesser extent to the
retrieval of individual cloud parameters.
Forward Model
Ice clouds: complex particles
Currently uses a combination of geometric optics (ray tracing); for large ice crystals and a T

matrix (ray tracing); method for small crystals.
Plates
Columns
Rosettes
Aggregates
Water clouds: spherical drops
Mie theory: solution of electromagnetic equations on dielectric sphere
Size distribution
10
m
m drop, 0.87
m
m wavelength
Since real time calculations of cloud radiative properties are too slow calculations are
made once DISORT (plane

parallel) model and incorporating rayleigh scattering and
stored in easily accessible Look up Tables.
Look up Tables
T
bc
T
ac
(e.g. MODTRAN)
Cloud + Atmosphere/surface
•
Separate solar and ‘thermal’ models
•
Both embed cloud with precalculated radiative
properties (LUTs) in clear atmosphere
t
r
e
p
c
(f)
Solar model
R
s
T
ac
From e.g. RTTOV
t
r
e
p
c
(f)
Thermal model
Transmitted
R
bc
Cloud emitted
B(T(p
c
))
e
Reflected
R
down
Atmosphere
emitted
R
up
Inversion: Optimal estimation
Guess
x
o
Calculate measurements
y(x
n
)
Adjust
(minimise J)
d
x =

J’/J’’
(Newton’s Method)
Stop!
d
J < 0.1 or n>10
Compare
J = [y
m

y(x
n
)] S
y

1
[y
m

y(x
n
)]
T
a priori
x
b
+ [x
n

x
b
] S
x

1
[x
n

x
b
]
T
= 1D

Variational analysis. Same principles > 3D, 4D Var (assimilation)
Cost Function
Compare
J = [y
m

y(x
n
)] S
y

1
[y
m

y(x
n
)]
T
+ [x
n

x
b
] S
x

1
[x
n

x
b
]
T
J = [y
m

y(x
n
)] S
y

1
[y
m

y(x
n
)]
T
Where y
m
are the radiances, S
y
the measurement error
covariance and y(x
n
) the cloud parameters modelled into
radiance space.
+ [x
n

x
b
] S
x

1
[x
n

x
b
]
T
Where X
b
is the apriori and S
x
the apriori covariance.
Inversion: Optimal estimation
Guess
x
o
Calculate measurements
y(x
n
)
Adjust
(minimise J)
d
x =

J’/J’’
(Newton’s Method)
Stop!
d
J < 0.1 or n>10
Compare
J = [y
m

y(x
n
)] S
y

1
[y
m

y(x
n
)]
T
a priori
x
b
+ [x
n

x
b
] S
x

1
[x
n

x
b
]
T
= 1D

Variational analysis. Same principles > 3D, 4D Var (assimilation)
Minimising J: optically thick
cloud
x
o
x
solution

No
a priori,

0.55, 1.6
m
m
channels

t
, R
e
only
Retrieved Cloud Parameters
Optical depth
Effective radius
Fraction
Cloud top pressure
False colour
Error Analysis and Quality Control
Cost
S
solution
= J’’
solution
= (S
x

1
+ K
T
.S
y

1
K)

1
Error Cloud top pressure
False colour
Validation Activities
R
e
validation against MRF FSSP probe
Optical depth (scaled to fit)
Effective radius
Hercules

ERS

2
Coincidence
FSSP
ATSR
Validation at SGP 20
th
Oct. 1997
AATSR overpass17:26
Microwave radiometer
SGP ARM data courtesy of Roger Marchand
.
Case study 20
th
October 1997
Parameter
ATSR

2
SGP
Optical depth
37.3
35.8
Effective radius
8.8
8.9
Liquid water path
244.0
209.8
Effective radius
LWP
Optical Depth
SGP validation
Mean:

0.08
Stdev: 1.21
Liquid water path is calculated using the
technique of Frisch et al, J. Atmos Sci.
1995, the technique is only valid for non

raining, water clouds.
Optical depth calculated using Han et al
J. Atmos Sci.,1995. Errors shown are the
standard deviation of the matches used.
Validation of CTH
Chilbolton
94GHz
Galileo Radar
Comparison with ISCCP data
ATSR

2 May 1999 Optical depth
ISCCP Optical depth May 1999
Level 3 products
Cloud top pressure
Cloud optical depth
Cloud effective radius
Cloud fraction
Summary and plans
•
6 years of ATSR

2 data
processed at 3x3km resolution
and a variety of level 3 products
•
Version 2 to begin soon with
many improvements
•
Potential is there to use
information from other satellites
•
Dual view tomographic cloud
retrieval
•
Extension to AATSR

long time
series
•
More validation, comparison with
met. Office models
The ATSR cloud and aerosol algorithm was developed
under funding from the following projects
The end
QC: Summary
•
Model
adequate
(J<1)
–
Expected errors, S
•
parameter dependent
•
state dependent
•
Information for
assimilation
•
(Discussed today
•
Not discussed)
•
Model
inadequate
(J>1)
–
A priori
out of range
•
rogue values
–
Measurements out of range
•
calibration errors
•
rogue values
–
Model out of range
•
multi

layer cloud
•
shadows
•
incorrect ice crystals
•
incorrect surface
reflectance
•
incorrect statistical
constraints
Retrieval (inversion): required
steps
•
“Forward modelling”:
–
Optical properties of
average particle in ‘single
scattering’ event
–
Optical properties of a
cloud of particles: multiple
scattering
–
Interaction of cloud
radiative processes with
atmosphere and surface
–
y = y(x)
•
“Inverse modelling”:
–
x = ? (y)
–
Guess cloud conditions (x)
–
Calculate radiances y(x)
–
Compare to measurements
–
Change cloud conditions
Stop!
R
e
validation against MRF FSSP probe
Optical depth (scaled to fit)
Effective radius
Hercules

ERS

2
Coincidence
FSSP
ATSR
Monthly Averaged Results
May 1999 log
10
Optical depth
May 1999 effective radius
Water clouds: spherical drops
Single particle
Mie theory: solution of electromagnetic equations on dielectric sphere
Size distribution
10
m
m drop, 0.87
m
m wavelength
Cloud top pressure
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