AbstractMany data-merging studies of the Tropical Rainfall Measuring Mission (TRMM) satellite involve the integration of high-resolution Visible and Infrared Scanner (VIRS) signals (~2 km) with low-resolution Precipitation Radar (PR) footprint (~5 km) to obtain comprehensive information from observations. Based on the merged dataset, “warm rain” is generally identified as having averaging 10.8-μm brightness temperatures (TB10.8) exceeding 273 K and the existence of surface rainfall. However, this integration may lead to the misidentification of warm rain because the beam-filling problem (nonuniform TB10.8 in PR pixels) is not fully considered through the method using high-resolution TB10.8 to match low-resolution rainfall. To assess the bias that is associated with identifying warm rain, a new dataset that includes all VIRS signals within the PR resolution is established, and the characteristics of this warm rain in the summers of 1998–2012 are analyzed. The results show that clear-sky pixels and “cold” pixels probably exist in some apparent warm-rain cases (60.5% and 11.2% of the time, respectively). According to this finding, warm-rain pixels are divided into pixels with and without clear sky. Statistical analysis shows that the existence of clear-sky pixels has a huge influence on the characteristics of the warm-rain pixels. The implications of this study are that many of the warm-rain cases are in fact not warm rain. When studying warm rain, the situation whereby the edges of pixels are clear sky should be fully considered. Also, when computing the weighted average brightness temperature and other characteristics of warm-rain pixels, parts that are clear-sky or cold pixels should be expelled to mitigate beam-filling problems.
Journal of Applied Meteorology and Climatology – American Meteorological Society
Published: Mar 3, 2017
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