IMAPP - International MODIS and AIRS Processing Package
H.-L. Allen Huang, Liam Gumley, Thomas Rink, Jun Li, Elisabeth Weisz, Kevin Baggett, Xiangqian Wu, Kathy Strabala, Chris Moeller
Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison
and William L. Smith Langley Research Center, NASA
2. IMAPP Software
1. IMAPP Revision History
May 12th, 2000 (v1.0) Initial release for Terra MODIS
SSEC is funded by NASA to develop the
International MODIS/AIRS Processing Package
(IMAPP). The goals of the IMAPP project include:
November 1st, 2000 (v1.1)
Calibration algorithm updated to version 2.4.3.
i. To release a freely available package for processing
MODIS and AIRS/AMSU/HSB data,
April 13th, 2001 (v1.2)
Calibration algorithm updated to version 2.5.5.
ii. To promote and support the worldwide use of EOS
data, and to involve the international community in
EOS validation efforts.
December 3rd, 2001 (v1.3)
Level-1A: fixed problems arising from bad Level-0 input
Geolocation: fixed interpolation problems at pass boundaries
Calibration: Algorithm updated to 3.0.0
For this purpose, SSEC has adapted the
operational Level-0 to Level-1 MODIS geolocation
and calibration software developed by NASA. The
main differences are that IMAPP:
ScanEX (Moscow) has ported IMAPP to Windows
http://cimss.ssec.wisc.edu/~gumley/IMAPP/
MODIS & AIRS Cloud Clearing Demonstration
Lower spectral resolution MODIS
data can provide high spatial
information to AIRS to improve
cloud clearing performance:
MODIS N*/MODIS Filter
Average CCR Yields:
2x2 = 10.8
3x3 = 4.5
4x4 = 2.4
6x6 = 0.9
1. Using N* windows to produce
a spectrum of N*
2. Using MODIS radiance to filter
N* results
11µm N*/MODIS Filter
3. Single 11 micron channel N*
(No MODIS data)
3.
Average CCR Yields:
2x2 = 12.9
3x3 = 5.5
4x4 = 3.0
6x6 = 1.2
Clear Column Radiance Results
With and without MODIS
2x2 ~ 4 Km Resolution
3x3 ~ 6 Km Resolution
4x4 ~ 8 Km Resolution
6x6 ~ 12 Km Resolution
11 µm Only
Average CCR Yields:
2x2 = 13.1
3x3 = 5.6
4x4 = 3.1
6x6 = 1.2
AIRS Algorithm Development
b. Compute linear regression RTV coefficients using noisy data
PCR applied to noisy independent testing data
Physical Retrieval:
a.
PCR-profiles (1c) used as initial (‘a priori’) data
b.
Channel selection using average Jacobian K
c.
PCC applied to PCR (1c) retrieved spectra (20 T, 15 Q , 5 O3, 1 Ts)
Simulated AIRS Data (From JPL & NOAA)
d. Optimal estimation retrieval:
X = Xa +
SKTSe-1(y-ya)
S = (KTSe-1K + Sa-1)-1
x, xa
rtv profile, initial (‘a priori’) profile
y, ya
measurements, measurements associated with xa
K
Jacobian (or weighting function matrix)
Se, Sa, and S
measurement, ‘a priori’ and rtv error covariance
Cloud Detection:
Eastern Europe Oct. 3, 2001: MODIS scene acquired
at the University of Dundee and processed by IMAPP.
3 color-composite Image
(Band 1- R; Band 6 - G; Band 7 -B)
Red-Snow; White-Clouds; Aqua-Clear Ground
12 Feb., 2002 17:23 UTC
IMAPP may be downloaded at no cost, and is
licensed under the terms of the GNU General Public
License (GPL). IMAPP is now used in USA, UK,
Germany, Russia, Japan, China, Korea, Singapore,
and Australia to process Terra MODIS data. The latest
release (v 1.3) was in December 2001,
Blue - Clear (probably)
Green - clear (confident)
Red - Uncertain
White - clouds
5.2 Water Vapor Product: June 2, 2001
Science algorithms currently under
development for release as part of IMAPP include:
• MODIS Cloud Mask
• MODIS Temperature and Moisture Profiles
• MODIS Cloud Top height, temperature, phase
• Fire Detection (courtesy of MODIS Land Team)
•AIRS/AMSU/HSB Level 0 to level 1 S/W
•AIRS Temperature and moisture Profiles
Barents Sea Mar. 1, 2001: MODIS scene acquired
by ScanEx Moscow and processed by IMAPP.
Processing Architecture
MODIS direct broadcast data are processed at
SSEC using an automated data-driven architecture.
The SeaSpace TeraScan system is responsible for
acquiring Level-0 (reconstructed time-ordered
instrument packets) for every overpass. When a new
Level-0 pass file is created, it is sent to a separate
computer for IMAPP Level-1 processing, which
involves unpacking, geolocation, and calibration of
the MODIS image data at all spatial resolutions.
PCC (EOF) applied to training data
c.
Has been ported to major UNIX platforms,
Requires only the NCSA HDF 4.1r3 toolkit,
Runs in a much simpler processing environment,
Can use downlink or definitive ephemeris/attitude,
Can process satellite overpasses of arbitrary size.
4.
Initial Retrieval:
a.
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•
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5.1 Cloud Mask Product: February 12, 2002 (Real time Product)
When a new Level-1B file is created, browse
images are created for a variety of predetermined
scenes in the continental US, Canada, and Northern
Mexico. The browse images and pass information are
then sent to a third computer that maintains a
database-backed website for all passes and images.
Level-0
Data
Level-0 Ingestor
(SeaSpace TeraScan)
Tape archive
Exabyte 8mm
Level-0 Data
Level-1 Processor
Level-1B
Data
(IBM Netfinity, Solaris)
Online Level-1B
(Anonymous FTP)
Browse Images
Web Server
(IBM Netfinity, Solaris)
Browse
Images
Database
0.87 m reflectance
Total Precipitable Water Vapor
This pass over the US east coast and Gulf of Mexico ranges from a dry atmosphere north of the
Great Lakes to a moist atmosphere over the Yucatan peninsula. Note the high density of TPW retrievals
in clear skies. A retrieval is made for every 5 x 5 box of 1000 meter pixels if 5 or more pixels are clear.
5.3 Sea Surface Temperature Product: May 2, 2001
(MySQL, PHP)
Front
Web Pages
http://eosdb.ssec.wisc.edu/modisdirect/
SSEC is adapting the following MODIS science
algorithms for IMAPP release by the end of 2001:
Dramatic structure in the Gulf Stream is
revealed in this daytime sea surface temperature
retrieval from the combination of the MODIS 11 m
and 12 m channels. Note the temperature front
where a gradient of almost 20C is observed over a
few kilometers.
Cloud Mask: For every 1000 m MODIS pixel,
determines whether the field of view is obstructed
(usually by cloud). Uses a combination of fuzzy
spectral tests using visible and infrared bands.
Simulated AIRS Spectrum & Noise
Ice and Water Cloudy Signature Approach
Simultaneous Cloud Height and Cloud Emissivity:
Minimum Local Emissivity Variance Approach
SSEC is also developing MODIS in-house science
MLEV
Cloud Height
Retrieval
Sensitivity
algorithms for future IMAPP release:
Sea Surface Temperature: GOES like retrieval.
Simulated AIRS Retrieval & Residual
Striping & Out of Band Correction: Detector
dependent ratio technique (determination of
correction coefficients is under investigation)
Temperature and Moisture Profiles: Retrieves profiles
of atmospheric temperature and water vapor for every 5
x 5 box of 1000 m MODIS pixels. Uses a statistical
regression for efficiency.
Cloud Top Properties: Retrieves cloud top properties
(including height, effective emissivity, phase) for every
5 x 5 box of 1000 m MODIS pixels. Uses longwave
infrared CO2 slicing and tri-spectral thresholds.
5.4 Striping & Out
of Band Influence
Correction:
Dec. 8, 2000
MODIS 1.38 m band image
before and after correction
0215 UTC Dec. 8, 2000