** Progress in Earth and Planetary Science is the official journal of the Japan Geoscience Union, published in collaboration with its 50 society members.

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    • Progress in Earth and Planetary Science
    • Progress in Earth and Planetary Science
    • Progress in Earth and Planetary Science
    • Progress in Earth and Planetary Science
    Progress in Earth and Planetary Science

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    Atmospheric and hydrospheric sciences

    201908201908

    Precipitation estimation performance by Global Satellite Mapping and its dependence on wind over northern Vietnam

    Nodzu M I,Matsumoto J,Trinh-Tuan L, Ngo-Duc T

    Precipitation, Satellite observation, GSMaP, Asian summer monsoon, Orographic convection.

    The performance of the Global Satellite Mapping of Precipitation data Microwave-Infrared Combined Reanalysis Product (GSMaP RNL), version 6, was evaluated, using northern Vietnam as the test area. The Vietnam Gridded Precipitation (VnGP) Dataset was used for comparison purposes. Particular emphasis was placed on the investigation of heavy-rain days (precipitation over 50 mm day −1). Wind data from operational radiosonde observations at Hanoi were also used to examine the effect of interaction between wind and topography, on the GSMaP performance, and the basic relationship between the VnGP precipitation and lower tropospheric wind. Results showed that heavy-rain days generally occurred during May–August. Regions with higher and lower precipitation in the GSMaP, compared to the VnGP, were found to be distributed in a complex manner, at a scale similar to that of tributary basins. The GSMaP and the VnGP showed similar precipitation values when associated with westerly wind in the lower troposphere at Hanoi. Positive influences of westerly wind on estimated precipitation were observed along the northeastern foot of the mountain ranges, whereas negative influences were found along the southeastern foot. The results implied that the GSMaP rainfall estimation algorithm, taking account of orographic effects, may improve the accuracy of rainfall reproducibility, by using a more appropriate wind dataset to evaluate orographic convection.