Journal of the Meteorological Society of Japan. Ser. II
Online ISSN : 2186-9057
Print ISSN : 0026-1165
ISSN-L : 0026-1165
Articles
Estimation of Tropical Cyclone's Intensity Using TRMM/TMI Brightness Temperature Data
Shunsuke HOSHINOTetsuo NAKAZAWA
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2007 Volume 85 Issue 4 Pages 437-454

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Abstract
A new method for the estimation of tropical cyclone (TC) intensity utilizing 10, 19, 21, 37 and 85 GHz channel TRMM Microwave Imager (TMI) data from 1999 to 2003 is developed. As a first step, we investigated the relationship between the TRMM/TMI brightness temperature (TB) parameters, which are computed in concentric circles, or annuli of different radius in different TMI frequencies, and the TC maximum wind speed from the TC best track data, and/or observed by microwave scatterometers (QuikSCAT and SeaWinds).
In contrast to the previous studies, we found that the parameters with lower frequency channels of 10 or 19 GHz give higher correlation. This would be because that TBs of lower frequencies, that have less sensitivity to rain than those of higher frequencies, reflect the speed ofsea surface wind more directly in the TC case. The highest correlation coefficient obtained is 0.7, and the root mean square error (RMSE) of the regression between a parameter of highest correlation case is found to be 6 ms−1.
We developed a TC intensity estimation method, based on the multiple regression equations using a few parameters. After choosing 3 parameters out of all possible combinations, we computed the regression coefficients and chose 10 regression equations, sorted by the lower RMSEs.
Finally, we evaluated our estimation method using independent verification data during 2004. The RMSEs are found to be about 8 ms−1 in the entire basin for the best track data, and about 6 ms−1 for the best track data in the northwestern Pacific. Whereas, for the microwave scatterometer data in all basins RMSE is found to be about 7 ms−1. We also found that the temporal TC intensity change in our method shows good agreement with the TC best track data.
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© 2007 by Meteorological Society of Japan
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