3.1
Comparison of Column Integrated Water Vapor Measurements from Atmospheric InfraRed Sounder (AIRS) and Surface-based Global Positioning System Receivers

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Tuesday, 31 January 2006: 8:30 AM
Comparison of Column Integrated Water Vapor Measurements from Atmospheric InfraRed Sounder (AIRS) and Surface-based Global Positioning System Receivers
A405 (Georgia World Congress Center)
M. K. Rama Varma Raja, I. M. Systems Group, Inc., Kensington, MD; and S. I. Gutman, J. G. Yoe, L. M. McMillin, and J. Zhao

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Integrated Precipitable Water (IPW) vapor estimates derived from a network of ground-based GPS receivers provide an accurate, convenient, and statistically robust means to assess the quality of AIRS water vapor retrievals over the contiguous United States (CONUS). For a period from April to October 2004, GPS IPW estimates were paired with AIRS data nearly coincident in time and space. The matched data pairs exhibit small monthly mean and rms differences, giving confidence in both the AIRS observations and the humidity retrieval. Monthly rms differences were reduced using stricter horizontal matching, indicating that part of the observed differences are attributable to sampling. IPW biases were found to be proportional to surface pressure differences reported for the GPS and AIRS retrievals. IPW match-up pairs for which the surface pressure differences are small (less than 0.5 mb) show smaller biases. Moreover, adjusting the AIRS IPW values to account for the reported surface pressure differences resulted in significant reductions of both bias and rms differences. The AIRS IPW estimates tend to be relatively dry in moist atmospheres (IPW values > 40 mm) and wet in dry cases (IPW values < 10 mm). This is consistent with previously documented tendency of satellite retrievals to be biased towards initial guess used for retrievals. Additional investigation is necessary to verify and quantify the effect of the bias of AIRS water vapor retrievals towards initial guess on AIRS IPW estimates and their validation. Finally, it is shown that the IPW bias and rms differences appear to have a seasonal dependency.