Starting in 2002 with the summer's IHOP exercise to study H2O processes over the high plains, a project centered over OK, the GPS (signal delay) and GOES-measured total water vapor just  didn't match well. The ensuing investigation as to why, lead to adaptive methods to assimilate the data, a correction algorithm for the bias, and ultimately to a premise as to why the satellite moist bias existed. Provoked by the initial evidence of asynoptic bias effects in the GOES, the attention of CIMSS retrieval scientists was brought to bear on the problem, which ultimately lead to an improved algorithm for moisture retrievals beginning tests this past; spring, and now slated for operational implementation in FY09 at NESDIS. The new CIMSS algorithm has been now validated by GPS. As will be shown, the new algorithm removes most all of the bias in GOES to the level that we can now safely use the data without imposing a bias correction.

GOES-R will come to us with reduced retrieval capability since the initial planned HES instrument was removed from the suite of satellite sensors due to funding constraints. The ABI retrieval system will be under-determined; similar to the current GOES, all the more reason to pay attention to what we see on the current GOES. Lessons we have learned and those still being researched in the current GOES are therefore directly applicable to the future GOES-R product generation. We now are assessing model forecasts by applying GPS comparisons to insure the best first guess for the sounding retrieval algorithm. The independent measure of total moisture from GPS signal delay has proven to be a very useful independent data set for asynoptic assessment of GOES moisture retrieval science. A review of the work comprising GPS and GOES satellite data comparisons to date will be shown, along with current activities and future plans for satellite research in GSD.

Contact Information: http://laps.fsl.noaa.gov/cgi/birk.homepage.cgi