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DOI10.1016/j.atmosres.2020.105119
Expanding contingency table for intensity and frequency based “true” detection of rainy events in precipitation datasets
Chaudhary S.; Dhanya C.T.
发表日期2020
ISSN0169-8095
卷号244
英文摘要Conventional Contingency Table (CT) compares the simulated/remotely-sensed dataset with observed dataset based on the frequency of rainfall events detected. However, while drawing comparison, it overlooks the variability in the rainfall intensity of Hit events (rainy events detected by both simulated and observed dataset). We propose to expand the conventional CT by segregating the Hit events into Over-hit (OH), True-hit (TH) and Under-hit (UH) events. While, TH represents those hit events with exactly same magnitude in simulated and observed dataset, OH (UH) represents over-estimation (under-estimation) by the simulated dataset. The efficacy of modified CT is demonstrated by initially using synthetic precipitation time series and later by using real gauge-based and satellite-derived dataset over India. The results show that modified CT provides additional information about the similarity in frequency as well as intensity of rainy events, which is extremely useful in quantifying the “true accuracy” (in form of TH) of the simulated/remotely-sensed dataset. © 2020 Elsevier B.V.
关键词Earth atmosphereMeteorologyContingency tableOver-estimationPrecipitation time seriesRainfall eventRainfall intensityRaincontingent valuationdetection methodprecipitation (climatology)precipitation assessmentprecipitation intensitytime seriesIndia
语种英语
来源机构Atmospheric Research
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/132390
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Chaudhary S.,Dhanya C.T.. Expanding contingency table for intensity and frequency based “true” detection of rainy events in precipitation datasets[J]. Atmospheric Research,2020,244.
APA Chaudhary S.,&Dhanya C.T..(2020).Expanding contingency table for intensity and frequency based “true” detection of rainy events in precipitation datasets.,244.
MLA Chaudhary S.,et al."Expanding contingency table for intensity and frequency based “true” detection of rainy events in precipitation datasets".244(2020).
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