Rain rate estimation from nadir-looking TOPEX/POSEIDON microwave radiometer (TMR) for correction of radar altimetric measurements

Varma, A. K. ; Gairola, R. M. ; Kishtawal, C. M. ; Pandey, P. C. ; Singh, K. P. (1999) Rain rate estimation from nadir-looking TOPEX/POSEIDON microwave radiometer (TMR) for correction of radar altimetric measurements IEEE Transactions on Geoscience and Remote Sensing, 37 (5). pp. 2556-2568. ISSN 0196-2892

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Related URL: http://dx.doi.org/10.1109/36.789650

Abstract

Atmospheric liquid water, particularly in the form of rain, produces anomalies in the radar altimetric range measurements. Such features are observed as sudden large changes in radar backscatter as a means of identification. To quantify the rain that radar altimetric pulses encounter, the instantaneous rain estimation capability of the nadir looking multichannel microwave radiometer onboard the TOPEX/POSEIDON satellite is explored. The three frequency (18, 21, and 37 GHz) nadir looking TOPEX microwave radiometer (TMR) brightness temperature data are colocated with the special sensor microwave/imager (SSM/I) rain rates to find a new rain rate algorithm by regression over the Indian Sea. Among the colocated data on different spatial and temporal scales, the most restrictive criteria (<0.1°, <1 h apart) produce the best correlations between the SSM/I estimated rain rates and the TMR brightness temperatures. The TMR measurements, colocated with SSM/I, thus presents a nontraditional usage of nadir viewing microwave radiometer data for estimation of instantaneous rainfall for correction of the radar altimetric measurements over the oceans. This equation is further used to generate monthwise-averaged global rain rate maps for the year 1993. Typical rain rate maps for two contrasting seasons for the months of January and July 1993, during the northeast and southwest monsoon, respectively, are compared with similar maps of the SSM/I rain rate. It is found that all the major features of global rainfall are picked up accurately and reproduced by the TMR-based algorithm. The mean rainfall rate thus derived (totaling a month) also is analyzed with some simultaneous atmospheric and oceanic processes in mind, which couple each other through rainfall.

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