2. User’s Expectations of GSICS
Lars Peter Riishojgaard
Fuzhong Weng
(JCSDA)

3. JCSDA Partners
Pending
In 2001 the Joint Center was established2 by NASA and NOAA and in 2002, the JCSDA expanded its partnerships to include the U.S. Navy and Air Force weather agencies.
2 Joint Center for Satellite Data Assimilation: Luis Uccellini, Franco Einaudi, James F. W. Purdom, David Rogers: April 2000.

4. JCSDA Expectations
GSICS should consider the cross-calibration of US operational & research missions (e.g. DoD, NASA, and NOAA/NASA joint programs) that are relative to NWP community
GSICS is recommended to establish a website for monitoring of sensor performance with information of sensor noises and biases relative to NWP backgrounds and analysis fields
GSICS partner agencies can offer some insights on O-A and O-B from NWP systems thru xcalibration capabilities
GSICS can help facilitate the common practices of instrument calibration (e.g. SSMIS UPP )
GSICS should develop routine calibration of geostationary satellite data to correct bias at IR channels to improve GOES data assimilation

5. SSMIS Anomaly Distribution
Shown is the difference between simulated and observed SSMIS 54.4 GHz. The SSMIS is the first conical microwave sounding instrument, precursor of NPOESS MIS. The outstanding anomalies have been identified from three processes: 1) antenna emission after satellite out of the earth eclipse which contaminates the measurements in ascending node and small part in descending node, 2) solar heating to the warm calibration target and 3) solar reflection from canister tip, both of which affect most of parts of descending node.

6. Impact of SSMIS on Forecast Scores
For northern hemispheric forecasts, impacts from both data sets are similar
For southern hemispheric forecasts, the score from UPP data is much lower compared to that from NESDIS data
SSMIS Exp. (F16 NESDIS)
NESDIS
data
UPP
data
More
negative
More
positive
SSMIS Exp. (F16 NESDIS)

7. Cross Calibration of GOES-12 Imager
The GSICS studies have found that there are large biases of the GOES-12 Imager at 13.3 µm (Ch6) because of contamination issue and Spectral Response Function Shift
GSICS Xcalibration Algorithm is developed using AIRS/IASI as a standard
Rad(c) = (Rad(o) – b ) / a, where a and b are regression coefficients from
matched monthly GOES and Hyperspectral data sets
Before Xcalibration
bias= K
After Xcalibration
bias= K
A and B are derived from collocated data from IASI and GOES.