EDR Algorithms for the
Cross-track Infrared Sounder
Xu Liu
Atmospheric Environmental research, Inc.
131 HartwellAve, Lexington, Ma 02421
Contact: Xliu@aer.com
and
Ronald J. Glumb, Christopher E. Lietzke and Joseph P. Predina
ITT Industries, ITT Aerospace/Communications,
1919 West Cook Road, P.O. Box 3700, Fort Wayne, IN 46801, USA
Contact: joe.predina@itt.com
CrIS
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CrIMSS EDR Products
ATMS
CrIS
CMIS
Spacecraft
Navigation
Ground Calibration
(Generate SDRs)
Produce
ATMS SDRs
ATMS
Produce
CrIS SDRs
Calibrated and
Geolocated
Radiances
CrIS IR
(9 FOVs)
Produce
CMIS EDR
Climateology
(first guess)
s (NWP)
p
Surface
Map
Scene
Classification
Infrared and
Microwave
Retrieval
High Altitude
Temperature
CrIMSS
EDR
Products
Other NPOESS Elements
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Microwave
Retrieval
First Guess Profile
Produce
CMIS SDRs
CrIS Hardware & Software
CrIS
Ground Science Algorithms
(Generate EDRs)
Merge SDRs
Space Segment
(Generate RDRs)
S/C Store and Forward
Microwave
Scenes
IR
Scenes
Microwave
Scenes
CrIS EDR
Algorithm
2
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AMSU/MHS Channels Used
CrIS EDR
Algorithm
CrIS
(ATMS to replace AMSU/MHS)
Chan
#
1
2
Central
Freq.(GHz)
23.800
31.400
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
50.300
52.800
53.596
54.400
54.940
55.500
57.290
57.290
57.290
57.290
57.290
57.290
89.000
89.000
150.000
183.310
183.310
183.310
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Side Band
(GHz)
0
0
0
0
0.115
0
0
0
0
0.217
0.322 0.048
0.322 0.022
0.322 0.010
0.322 0.0045
0
0.9
0.9
1
3
7
3
Bandwidth
(MHz)
270
180
180
400
170
400
400
330
330
78
36
16
8
3
6000
1000
1000
500
1000
2000
Channel
Function
Water Vapor Burden
Surface Temperature
Surface Temperature
Surface Temperature
Tropospheric Temp.
Tropospheric Temp.
Tropospheric Temp.
Tropospheric Temp.
Stratospheric Temp.
Stratospheric Temp.
Stratospheric Temp.
Stratospheric Temp.
Stratospheric Temp.
Stratospheric Temp.
Cloud Top and Snow
Precipitation
Water Vapor
Water Vapor
Water Vapor
Water Vapor
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CrIS EDR
Algorithm
CrIS Channels Used
Band
LWIR
MWIR
SWIR
Total
Frequency Range
650-1095 cm-1
1210-1750 cm-1
2155-2550 cm-1
Resolution (1/2L)
0.625 cm-1
1.25 cm-1
2.5 cm-1
# Channels
713
433
159
1305
• Channels Excluded During MW/IR Retrieval
– Ozone Band from 950 cm-1 to 1095 cm-1
– Trace gas channels
– Low information content channels (channel selection)
– Good results using only 400, 300 and 150 channels
• Special High Information Content Channels Used
– 709.5 cm-1 to 746 cm-1 for cloud parameter h estimation and
Principle Component Analysis (PCA) for estimating number of
cloud formations
– 2190 cm-1 to 2250 cm-1 for cloud parameter h estimation
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CrIS EDR
Algorithm
Fast Forward Model
• Optimal Spectral Sampling (OSS)
Benchmarked
against AIRS fast
forward model in
1999………
OSS > 20 times faster
OSS > 40 times faster
when including
Jacobians
–
–
–
–
–
–
Developed at Atmospheric Environmental Research (AER)
Fast and accurate (validated against Line-by-line models)
Can model non-localized Instrument Line Shape (ILS)
Computes Jacobian efficiently
Accurate treatment of reflective radiation from surface
Both MW and IR versions developed
Only 20% Speed
Penalty when
Modeling sinc vs.
Blackman-Harris
Instrument ILS
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CrIS EDR
Algorithm
Retrieval Methodology (Rogers, 1976)
Error Covariance
Matrix of Background
General
Form Used
Observed Radiance
Error Covariance
Matrix of Measurement

xi 1  xa  S x K Ki S x K  S y
T
i
T
i
Matrix of Partial Derivatives
of yi With Respect to x
EOF Form
Used

1
y
xi 1  xa  K S Ki  S
T
i
 y
1
o
Calculated Radiance
 yi  Ki ( xi  xa )
Retrieved Variable

1 1
x
Background
Temp/moisture/
Emissivity/
Reflectivity/
etc.
KiT S y1yo  yi  Ki xi  xa 
EOF Form Has Much Smaller Dimension & Is
Modified to Handle Nonlinear Case
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CrIS EDR
Algorithm
Retrieved Parameters
Parameter
Temperature
Water vapor
Ozone
Other trace gases
Skin Temperature
MW Surface Emissivity
MW Cloud Liquid Water
MW Cloud Top Pressure
IR Surface Emissivity
IR Surface Reflectivity
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# of elements
20 EOFs
10 EOFs
1 (column correction)*
Column correction only
1
5 EOFs
1
1
6 hinge points
6 hinge points
7
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CrIS EDR
Algorithm
CrIMSS Retrieval Process (1 of 6)
• Initialization
Used for First
Guess
Fast Forward
Model Parameters
Indexed Every 10
Degree of
Temperature
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– Load instrument specifications (AMSU, MHS, CrIS
frequencies, Noise, etc.)
– Load climatoligical atmospheric data base
– Load surface background data base (Mean profiles, error
covariance matrices)
– Load OSS parameters (Optical depth tables)
– Load solar spectrum
– Load topography & land/ocean mask
GTOPO30 Digital
Elevation Map,
land/ocean mask
8
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CrIS EDR
Algorithm
CrIMSS Retrieval Process (2 of 6)
• Preprocessing
Interpolated in
Time and Space
Land/ocean maps
& MW Brightness
Temperature tests
@ 31, 50, 89 & 23
GHz
– Test for precipitation
– Compute surface pressure from NWP data
– Test for surface type
• Land
• Ocean
• Ice
• Snow
• Coast: ocean/land
• Coast: ice/snow
– Choose Background by Surface type & mix with emissivity
information
MW Ocean
Emissivity per
Wilheit model
(Wilheit, 1979)
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MW Land
Emissivity per
Grody model
(Grody, 1988)
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CrIS EDR
Algorithm
CrIMSS Retrieval Process (3 of 6)
• Microwave Only Retrieval
– Average radiances from 9 MHS
FOVs
– Execute OSS fast forward model
based upon climatology first
guess
– Perform inversion & update first
guess profile
– Calculate new radiances using
OSS
– Test for convergence
– Continue iteration if convergence
criteria not met
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CrIS EDR
Algorithm
CrIMSS Retrieval Process (4 of 6)
• Scene Classification
– Purpose
• Maximize # of good retrievals
within a field of regard (FOR)
• Optimize an FOV clustering
strategy for treatment of clouds
and use of cloud clearing
algorithm
– Method
• Form matrix of 9 FOVs by 62 IR
channels in the spectral region
from 709 to 748 cm-1
• Analyze for up to 9 principle
components
• Determine number of cloud
formations present from PCA
analysis & 2 statistical tests
• Cluster minimum number of
FOVs needed to perform cloud
clearing
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3
2
1
6
5
4
9
8
7
Example of PCA Analysis
3 principle components
indicating 2 cloud
formations
11
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CrIS EDR
Algorithm
CrIMSS Retrieval Process (5 of 6)
• Combined MW/IR Retrieval
– Uses MW retrieval as first
guess (profiles, surface, cloud
parameters)
– Modified Maximum Likelihood
Method for nonlinear retrieval
– Dynamically adjust channel
weights to improve
convergence and stability
– Cloud clearing parameter h
estimated each iteration
– FOVs averaged above 80 mbar
– Test for convergence
– Continue iterations if
convergence criteria not met
Next
Cluster
Calculate Clear Radiance estimate
from MW Retrieval or NWP Profile
CCflag
False
True
Calculate CC Radiance
Average FOV's within
cluster
Perform Physical Inversion
Update geophysical parameters
Calculate new Radiance
No
Convergence?
Max Iterations?
Yes
No
All Clusters
Processed?
Yes
Quality Control
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CrIS EDR
Algorithm
CrIMSS Retrieval Process (6 of 6)
• Quality Control
– If normalized c2 > 1.0 for
the retrieval, then
retrieval is not reported
– If MW radiances after
MW/IR retrieval differ by
more than 3 K from
observed radiances,
then entire retrieval
rejected
– If MW retrieval and
MW/IR retrieval differ by
more than 3 K, then the
MW/IR retrieval is
rejected
– If difference between
cloud cleared CrIMSS
radiances and VIIRS
cloud free radiance is
greater than 2 k, then
retrieval is suspect
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Retrieved Brightness
Temperature in
ith Channel
Observed Brightness
Temperature in
ith Channel
nchan
( iretr   iobser ) 2
i 1
Ni

c 
2
Stop If
• c < 0.7
• <10% change
between iterations
• # iterations = 4
nchan
Number of Spectral Channels
(or super channels)
Used in Retrieval
Noise Variance
for i th Channel
Microwave Retrieved
Brightness
Temperature @ Level i
Combined Microwave/IR
Retrieved Brightness
Temperature @ Level i
nlev

If  > 3 K
Reject
MW/IR Retrieval
13
 (T (MW )  T (MW / IR))
i 1
i
2
i
nlev
Number of Retrieved
Levels Below
3 km Altitude
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CrIS EDR
Algorithm
CrIS
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Performance for Various Levels of Channel Selection
14
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CrIS EDR
Algorithm
CrIMSS Projected Performance
1
30
100
100
25
Altitude (km)
10
Altitude (mbar)
Altitude (mbar)
“Threshold”
Performance
500
20
15
10
5
1000
1000
0
0.5
1
1.5
Retrieved Temperature
Error (K, rms)
0
0
5
10
15
20
25
Retrieved Moisture
Error (%, rms)
0.0
0.5
1.0
Retrieved Pressure
Accuracy (%)
Based on Global Average
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Expected Improvement Over HIRS
CrIS EDR
Algorithm
(RMS Uncertainty, Global Average Basis)
CrIS
CrIS
HIRS
HIRS
CrIS
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