Validation of Satellite-Derived Near-Surface Air Temperature and Humidity using Dropsondes

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Wednesday, 7 January 2015
Darren L. Jackson, CIRES/Univ. of Colorado, Boulder, CO; and G. A. Wick

Satellite-derived estimates of air-sea heat fluxes depend significantly on accurate retrievals of near surface air temperature (Ta) and specific humidity (Qa). Our efforts toward a global retrieval of these observations has been ongoing for over 10 years, and this study will provide recent updates to the retrieval and recent validation efforts with observations from dropsondes taken near tropical cyclones and Pacific winter storms. These measurements are particularly important near extreme weather events, such as tropical cyclones, where validation of Ta, Qa, and heat fluxes is generally unknown. This type of validation can better characterize uncertainties in this environment. The unique aspect of our retrieval is combining microwave observations from SSM/I and SSMIS instruments with microwave sounder observations from AMSU-A instruments to retrieve Ta and Qa. Recent refinements to our products have included regional correction based on anomalous stability conditions, use of independent sea surface temperature data, and the use intercalibrated satellite data. The initial comparison between satellite-derived and dropsonde observations indicated the greatest biases in the most warm and moist regions and in the most cold and dry regions. Biases are generally too wet and warm in warm, moist regions and too dry and cold in the in the cold, dry regions. Qa biases were found to be generally larger than those for Ta, and biases were found to correlate the highest with integrated water vapor. Other potential dependencies such as cloud liquid water and wind speed were found to have no significant correlation with these biases. The biases characterized from the dropsonde data generally agree with separate studies using buoy and ICOADS ship comparisons. This study will provide explanation for these biases and the steps taken to improve and mitigate the bias in the satellite retrieval. Such improvements will ultimately improve satellite-derived air-sea heat flux estimates and provide better error characteristics for these retrievals near extreme weather events.