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

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.

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

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.

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)

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= -2.55 K After Xcalibration bias= -0.11 K A and B are derived from collocated data from IASI and GOES.