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Rainfall Monitoring for the Indian Monsoon Region from Merged Gauge, METEOSAT, INSAT and NWP Models

机译:利用合并仪表,METEOSAT,INSAT和NWP模型对印度季风地区的降雨进行监测

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摘要

For study of Asian monsoon, IR based estimates from Kalpana-1, Meteosat-5 and microwave based estimates from TRMM rainfall data are very useful, particularly for the oceanic regions. Satellite only estimates have biases, but are able to represent the large-scale monsoon rainfall features. IR estimates are unable to capture the heavy rain over the west coast of India. Even the TRMM values are underestimating the heavy rainfall over the west coast of India. Inclusion of gauge data (over land and island) improves the representation of daily rainfall. Gauge data corrects the biases in the satellite estimates. The number of gauge stations available in real time is less, and for a better analysis of the large-scale rainfall field at least the full set of 540 stations from India will be very useful. For meso-scale analysis a much denser network of gauge stations will be required. These gauge data will be very useful to correct the current biases in the satellite estimates.
机译:对于亚洲季风的研究,来自Kalpana-1,Meteosat-5的基于IR的估计以及来自TRMM降雨数据的基于微波的估计非常有用,特别是对于海洋区域。仅卫星估算有偏差,但能够代表大规模的季风降雨特征。 IR估计无法捕获印度西海岸的大雨。甚至TRMM值也低估了印度西海岸的强降雨。包含量表数据(陆地和岛屿上的数据)可以改善每日降雨量的表示方式。量表数据纠正了卫星估算中的偏差。实时可用的轨距站数量较少,为了更好地分析大规模降雨场,至少印度全套540个站将非常有用。对于中尺度分析,将需要更密集的仪表站网络。这些轨距数据对于校正卫星估算中的当前偏差将非常有用。

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