Thursday, 19 April 2018
Champions DEFGH (Sawgrass Marriott)
Tropical Cyclone (TC) intensity estimation is one of the first steps in the TC forecasting process. Current TC intensity along with the trend of the intensity are important predictors in both the subjective evaluation of the TC near term forecast and statistical models used to estimate intensity. The primary method for estimating TC current intensity is the subjective Dvorak Technique (DT) that uses geostationary infrared and visible satellite imagery. In addition a number of objective intensity methods are used routinely including the Advanced Dvorak Technique (ADT) which uses geostationary infrared imagery (ADT), polar orbiting passive microwave sounder-based methods (AMSU, SSMIS and ATMS) and to a more limited degree scatterometer data from ASCAT. Emerging methods that leverage CYGNSS and SMAP offer the potential to increase the number of intensity estimates available to the forecaster in the near future. With so many sensors and methods available the TC forecaster often has little time to interrogate the details and idiosyncrasies of all the available methods. The CIMSS SATCON algorithm can combine multiple intensity estimates into a single estimate that is more skillful than the individual components. This allows the forecaster to quickly assess the TC intensity without the need to subjectively weight each sensor’s contribution. Current members of SATCON include the CIMSS ADT, AMSU, SSMIS and ATMS methods along with the CIRA ATMS method. SATCON estimates have been run in near real-time at CIMSS and provided to worldwide TC warning agencies since 2008. Because these estimates are produced hourly they can alert the forecaster to rapid changes in intensity, in some cases before the DT is able to show these changes. In addition the multi-spectral algorithm can resolve intensity fluctuations such as eyewall replacement cycles that are generally missed by the DT. An update on the latest changes to the algorithm including the addition of the ATMS intensity method from the S-NPP and JPSS-1 satellites along with performance statistics will be presented.
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