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This paper introduces the Method of Microwave Rainfall Normalization (MMN) for the Global Satellite Mapping of Precipitation (GSMaP) algorithm in its latest version (V05, algorithm version 8), released in December 2021. The method aims to mitigate the discrepancy of GSMaP rainfall estimates among passive microwave (PMW) imagers/sounders (MWIs/MWSs) due to differences in sensor specifications and retrieval algorithms. The basic idea of the MMN module is to calibrate target PMW sensors with reference sensors (the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI)) using the cumulative distribution function (CDF) of the rain rate. Differences between the CDF and normalization table for MWSs are greater than MWIs due to different rain retrieval algorithms. More (less) MWS rainfall is detected over the ocean (land) than GMI rainfall. Matchup rainfall data between GMI and a target PMW sensor are compared to evaluate MMN performance. The monthly mean rainfall and mean bias error were improved for almost all PMW sensors. This study leaves open the possibility for further inter-calibration and improvement of rain detection and heavy rainfall retrievals. [ABSTRACT FROM AUTHOR]

In this study, the spatial variability in precipitation at a 0.1° scale is investigated using long-term data from the Tropical Rainfall Measuring Mission Precipitation Radar. Marked regional heterogeneities emerged for orographic rainfall on characteristic scales of tens of kilometers, high concentrations of small-scale systems (<10 km) over alpine areas, and sharp declines around mountain summits. In detecting microclimates, an additional concern is suspicious echoes observed around certain geographical areas with relatively low rainfall. A finescale land-river contrast can be extracted in the diurnal behavior of rainfall in medium-scale systems (10-100 km), corresponding to the course of the Amazon River. In addition, rainfall enhancement over small islands (0.1°-1°) was identified in terms of the storm scale. Even 0.1°-scale flat islands experience more rainfall than the adjacent ocean, primarily as a result of localized small or moderate systems. By contrast, compared with small islands, high-impact large-scale systems (>100 km) result in more rainfall over the adjacent ocean. Finescale hourly data represented the abrupt asymmetric fluctuation in rainfall across the coastline in the tropics and subtropics (30°S-30°N). Significant diurnal modulations in the rainfall due to large-scale systems are found over tropical offshore regions of vast landmasses but not over small islands or in the midlatitudes between 30° and 36°. Rainfall enhancement over small tropical islands is generated by abundant afternoon rainfall, which results from medium-scale storms that are regulated by the island size and inactivity of rainfall over coastal waters. [ABSTRACT FROM AUTHOR]

This letter identifies causes of the deterioration of the Global Satellite Mapping of Precipitation rain detection over the Tibetan Plateau during the summer monsoon season. Using the rain/no-rain classification (RNC) method over the Plateau, observed brightness temperature (Tb) at 21 (23) GHz from the Tropical Rainfall Measuring Mission Microwave Imager (the Defense Meteorological Satellite Program Special Sensor Microwave Imager) [Tb(21 V) and Tb(23 V)], and surface emissivity ( $\varepsilon )$ was substituted for surface temperatures (Ts) to exclude areas of low Ts as snow cover because it is difficult to distinguish between the scattering signals of precipitation and snow cover. A case study demonstrates that rain systems are excluded because Ts is often below the threshold for snow cover due to the use of an inadequate value for $\varepsilon $ (constant value throughout the year), even though a rain scattering signal at high-frequency channels under no snow cover is evident. After $\varepsilon $ is replaced with values from a monthly mean satellite observation-based land surface emissivity database, rainfall detection is improved. In addition, it is suggested that a database of RNCs should also consider diurnal variations in Tb(21 V) and Tb(23 V) due to large diurnal differences over the Plateau. [ABSTRACT FROM PUBLISHER]