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  4. Further improvement of the heavy orographic rainfall retrievals in the GSMaP algorithm for microwave radiometers
 
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Further improvement of the heavy orographic rainfall retrievals in the GSMaP algorithm for microwave radiometers

Journal
J. Appl. Meteorol. Climatol.
Journal Volume
56
Pages
2607-2619
Date Issued
2017
Author(s)
Yamamoto, M. K.
S. Shige
CHENG-KU YU  
L.- W. Cheng
DOI
10.1175/JAMC-D-16-0332.1
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/476524
Abstract
An orographic/nonorographic rainfall classification scheme has been introduced for the operational algorithm of the Global Satellite Mapping of Precipitation (GSMaP) for passive microwave radiometers. However, problems of overestimations and false alarms of heavy orographic rainfall remain unresolved. This is because the current scheme selected lower constant thresholds of orographic rainfall conditions for global application and used values of orographically forced upward motionw derived from near-surface atmospheric data. This study improves the conceptual model of the warm-rain process for considering the strength of the upstream flow of the low-level troposphere. Under a weak upstream current, rain reaches the foothills of the windward mountain slope because of sufficient time for condensation and precipitation enhancement by the topography. Conversely, under a strong upstream current, precipitation enhancement occurs nearer to the mountain peak. This is because the upstream current flows so quickly that there is insufficient time for enhancement of precipitation over the foothills of the windward mountain slope. After implementing a variable threshold for w that depends on the mean horizontal low-level wind, the area of orographic enhancement of rain was detected reasonably well in cases of both strong and weak winds. To improve the accuracy of estimates of orographic rainfall, an adjustment to the rain estimation was introduced using a lower-frequency channel. The biases of the rainfall estimate for the adjusted scheme from the Tropical Rainfall Measuring Mission Precipitation Radar were improved for the cases considered here as well as for the Asian region of heavy orographic rainfall over land. © 2017 American Meteorological Society.
Subjects
Algorithms; Microwave observations; Satellite observations
SDGs

[SDGs]SDG15

Other Subjects
Algorithms; Frequency estimation; Landforms; Microwave devices; Microwave measurement; Precipitation (meteorology); Radiometers; Classification scheme; Microwave observations; Microwave radiometers; Operational algorithms; Orographic enhancement; Precipitation enhancement; Satellite observations; Tropical rainfall measuring mission precipitation radars; Rain; algorithm; condensation; microwave radiometer; orography; precipitation intensity; satellite data; TRMM; troposphere

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