Disclaimer: This material is being kept online for historical purposes. Though accurate at the time of publication, it is no longer being updated. The page may contain broken links or outdated information, and parts may not function in current web browsers. Visit https://espo.nasa.gov for information about our current projects.


Small-Scale Horizontal Rain-Rate Variability Observed by Satellite

Varma, A. K., and G. Liu (2006), Small-Scale Horizontal Rain-Rate Variability Observed by Satellite, Mon. Wea. Rev., 134, 2722-2733.

The horizontal distribution of rain rates within an area comparable to the pixel size of satellite microwave radiometers and the grid size of numerical weather prediction models has been studied over the global Tropics using three years of the Tropical Rainfall Measuring Mission satellite precipitation radar (PR) data. The global distribution of rain-rate standard deviation derived from the PR data suggests that the horizontal variability of rain rates is largely influenced by two factors: surface type (land or ocean) and latitudinal location (tropical or extratropical). Except for light stratiform rain, the land–ocean contrast seems to be the dominant feature for the differences in conditional probability density functions (PDFs) of rain rate. That is, oceanic rain-rate distribution is narrower when the rain rate is low, but becomes broader when the rain rate is high. For light stratiform rain, there is no clear difference among the rain-rate PDFs for rain events over land and ocean. The latitudinal variation of rain-rate PDFs seems to be greater for heavy rain than for light rain. In particular, there is no measurable difference in overland convective rain-rate PDFs between the Tropics and extratropics. Based on three years of observational data, two attributes, fractional rain cover and conditional rain-rate PDFs, are parameterized as a function of 0.25° ϫ 0.25° areal rain rate. These parameterizations are particularly useful in satellite microwave rainfall retrieval and assimilation of satellite microwave radiance data in numerical weather prediction models.