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Pattern recognition analysis of satellite data for tropical cyclone motion and intensity forecastsAn objective empirical analysis technique is employed to investigate the extent to which satellite-obtained measurements (GOES IR and TOVS data) of a tropical cyclone and its environment can be used to predict cyclone motion. The paper describes the procedure used to process the satellite derived data in order to optimize their possible predictive value, the technique used in developing the regression algorithms, and the results of testing these algorithms using the Lachenbrach and Mickey (1968) procedure. The data were examined alone and in conjunction with available nonsatellite climatological and persistence variables for each storm. These predictors are similar to those used in the National Hurricane Center (NHC) CLIPPER model. The performances obtained using the Nichols Research Corporation CLIPPER model and the NHC CLIPPER model are compared, using homogeneous data sets for the comparisons. Major differences in results were found to be related to differences in the models.
Document ID
19870036119
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Hunter, Herbert
(Nichols Research Corp. Huntsville, AL, United States)
Nunez, Edwin
(Nichols Research Corp. Huntsville, AL, United States)
Barker, Llyle
(Nichols Research Corp. Huntsville, AL, United States)
Rodgers, ED
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
August 13, 2013
Publication Date
January 1, 1986
Subject Category
Meteorology And Climatology
Accession Number
87A23393
Distribution Limits
Public
Copyright
Other

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