Variability of passive microwave radiometric signatures at different spatial resolutions and its implication for rainfall estimation

Dong Bin Shin, Kenneth P. Bowman, Jung Moon Yoo, Long S. Chiu

Research output: Contribution to journalArticlepeer-review


Analysis of precipitation radar (PR) and Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI) data collected from the TRMM satellite shows that rainfall in-homogeneity, as represented by the coefficient of variation (CV), depends on a spatial scale, i.e., the CV appears to be nearly constant at all rain rates within the field of view (FOV) of the TMI 37-GHz channel, while it decreases with rain rate at lower spatial resolutions, such as the FOV sizes of the low-frequency TMI channels (10.7 and 19.4 GHz). It is known that the brightness temperature (Tb) for a low-frequency channel decreases with increasing rainfall inhomogeneity for a given rain rate. As such, more inhomogeneous rainfall at low rain rates leads to a lower Tb compared with that of a FOV with homogeneous rainfall; however, less inhomogeneous rainfall at high rain rates tends to produce a Tb similar to that of homogeneous rainfalls. These results indicate that the observed radiometric signatures of low-frequency channels at low spatial resolutions are characterized by a larger response range and smaller variability than those at a higher spatial resolution. Based on the observational characteristics of the TMI and PR data sets, we performed synthetic retrievals of rainfalls, employing a Bayesian retrieval methodology at different retrieval resolutions corresponding to the FOV sizes of the TMI channels at 10.7, 19.4, and 37 GHz. Comparisons of the rainfalls retrieved at the different resolutions and their temporal and regional averages show that the systematic bias resulting from the rainfall inhomogeneity is smaller in the lower resolution data than in their higher resolution counterparts. We note that such low-resolution rainfall retrievals are not expected to describe the instantaneous features of rain fields; however, they could be useful for climatological estimates at large temporal and spatial scales.

Original languageEnglish
Article number4694130
Pages (from-to)1575-1584
Number of pages10
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number6
Publication statusPublished - 2009 Jun

Bibliographical note

Funding Information:
Manuscript received April 4, 2008; revised July 30, 2008. First published December 2, 2008; current version published May 22, 2009. This work was supported in part by the Korea Research Foundation program under Grant KRF-2007-314-C00306 and in part by Yonsei University under Grant 2007-7-0179. D.-B. Shin is with the Department of Atmospheric Sciences, Yonsei University, Seoul 120-749, Korea (e-mail: K. P. Bowman is with the Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843 USA. J.-M. Yoo is with the Department of Science Education, Ewha Womans University, Seoul 120-750, Korea. L. S. Chiu is with the Institute of Space and Earth Information Science, Chinese University of Hong Kong, Shatin, Hong Kong. Color versions of one or more of the figures in this paper are available online at Digital Object Identifier 10.1109/TGRS.2008.2007740

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)


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