Abstract

Over the years, blended methods that use multi-satellites and multi-sensors have been developed for estimating global precipitation and resulting products are widely used in applications. An example is the 3-hourly TRMM (Tropical Rainfall Measuring Mission) Multi-Satellite Precipitation Analysis (TMPA) that consists of two products: near-real-time (3B42RT) and research-grade (3B42). The former provides quick, less accurate estimates suitable for monitoring activities; the latter provides more accurate estimates more suitable for research. Both products have been widely used in research and applications. Nonetheless, to improve near-real-time applications, it is important to understand their difference. In this study, seasonal mean difference (MD), mean absolute difference (MAD), root mean square difference (RMSD), and their inter-annual variations in boreal (June, July and August or JJA) and austral (December, January and February or DJF) summers and in different rain regimes over two surface types are investigated on a large scale (50°N–50°S) from 2000 and 2012. Over land, positive MD values (3B42RT>3B42) dominate, especially in western China, western United States, northwest Asia and over some oceanic regions of light rain in both JJA and DJF. Over ocean, negative MD values (3B42RT<3B42) prevail, except over regions of light rain. In general, relative (to 3B42) MD values increase with rain rate. Variation of the individual differences between the two products is small (large) over regions of heavy (light) rain. There is no significant inter-annual variation in the seasonal mean statistics. The difference between the two products is likely due to the algorithms and further investigations are needed.

Full Text
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