Wednesday, 13 January 2016: 9:30 AM
Room 350/351 ( New Orleans Ernest N. Morial Convention Center)
Satellite data play an important role in monitoring and predicting tropical cyclones (TCs) as a result of lack of in-situ data over the ocean. However, due to the exact same reason, satellite data over the ocean are not well calibrated and validated. GPS dropsondes have been routinely deployed during hurricane reconnaissance and surveillance flights to help predict hurricane tracks and intensity. A long-term (1996-2012), high-quality, high vertical resolution (~5-15 m) GPS dropsonde dataset was created from NOAA Hurricane flights and consists of 13,681 atmospheric profiles for 120 TCs. In this study, the newest version of the Atmospheric Infrared Sounder (AIRS) data, Version 6, is evaluated against the dropsonde data for 2002-2012. The AIRS and dropsonde profiles were matched within two hours and 150 km of each other; 1538 pairs were found for 54 TCs. The AIRS temperature agrees well with the dropsonde with mean biases of <=.5°C from the surface to 200 hPa and ~1°C RMSE although it shows a statistically significant warm bias of ~0.5°C in the middle troposphere. The AIRS relative humidity (RH) shows dry and moist biases at RH above and below 50% RH, respectively; the dry bias at higher RHs increases with RHs. The dry bias is sometimes associated with the warm bias in temperature, and seems related to the cloud clearing scheme in the AIRS retrieval. The strength and weakness of AIRS data in the TC environment will be summarized.
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