5.5 Estimation of Tropical Cyclone Intensity Using the CIMSS ATMS Tropical Cyclone Intensity Algorithm

Tuesday, 16 August 2016: 11:30 AM
Madison Ballroom CD (Monona Terrace Community and Convention Center)
Derrick Herndon, CIMSS, Madison, WI; and C. S. Velden

Accurate estimation of Tropical Cyclone (TC) intensity is a critical part of the TC analysis and forecast process. Over the last 20 years a number of advanced satellite tools have been made available to forecasters to enable them to more accurately assess TC current intensity. The Advanced Technology Microwave Sounder (ATMS) flown aboard the Suomi-NPP satellite is the latest addition to the suite of satellites capable of providing TC intensity estimates through observations of the TC warm temperature anomaly. CIMSS ATMS estimates of maximum sustained winds (MSW) and minimum sea level pressure (MSLP) are validated using ground truth data consisting of aircraft reconnaissance observations from 2012-2015 in the Atlantic and Eastern/Central Pacific. A small number of pressure observations from surface observations outside of the aircraft reconnaissance domain during this period are also used to validate the MSLP estimates. While accurate observations of MSW are more difficult to obtain from surface observations the pressure observations can be converted to a MSW using a pressure-wind relationship such as that developed by Knaff and Zehr with associated error bounds. Pressure-wind based estimates of MSW can be used to validate the ATMS estimates of MSW using the surface observations. Algorithm performance is similar in skill to the CIMSS AMSU and SSMIS sounder intensity algorithms with an RMSE of 7.4 hPa for MSLP and 10.7 knots for MSW. This makes ATMS an important addition to the sounder-based TC intensity suite. The addition of ATMS is especially important considering the recent loss of SSMIS sounders on F-16, F-18 and F-19. In addition the ATMS algorithm is tested as an input into the CIMSS SATellite CONsensus (SATCON) algorithm as a potential member of the objective consensus method.
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