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首页> 外文期刊>International Journal of Climatology: A Journal of the Royal Meteorological Society >Quantifying the reliability of precipitation datasets for monitoring large-scale East Asian precipitation variations
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Quantifying the reliability of precipitation datasets for monitoring large-scale East Asian precipitation variations

机译:量化降水数据集的可靠性,以监测大规模东亚降水变化

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摘要

Early detection of extreme drought and flood events either over the whole globe or a broad geographical region, and timely dissemination of this information, is indispensable for mitigation and disaster preparedness. Recently, the APEC Climate Center (APCC) has launched a global precipitation variation monitoring product based on the Climate Anomaly Monitoring System-Outgoing Longwave Radiation Precipitation Index (CAMS-OPI) data. Here we quantify the reliability of CAMS-OPI, as well as other gauge-satellite-merged and reanalysis precipitation datasets, for the purpose of monitoring large-scale precipitation variability in East Asia. The ground truth is the newly available gauge-based data from the project titled 'Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) of the Water Resources'. It is found that the seasonal-to-interannual rainfall deficit and surplus given by various reanalysis systems sometimes do not match the spatial patterns seen in the APHRODITE data. Moreover, maps showing the Standardized Precipitation Index (SPI) become less and less reliable as the time scale based on which values are calculated increases. In contrast, the performance of gauge-satellite-based rainfall datasets is satisfactory and the quality of SPI maps does not decay as the time scale increases. Overall, CAMS-OPI is found to be reliable for monitoring large-scale precipitation variations over the East Asian sector.
机译:尽早发现全球或整个地理区域的极端干旱和洪灾事件,并及时传播这些信息,对于减灾和备灾是必不可少的。最近,APEC气候中心(APCC)根据气候异常监测系统的长波辐射降水指数(CAMS-OPI)数据推出了全球降水变化监测产品。在这里,我们量化CAMS-OPI以及其他轨距合并和再分析降水数据集的可靠性,目的是监测东亚的大规模降水变化。基本事实是题为“亚洲降水-高度分辨的观测数据集成以评估水资源(APHRODITE)”项目中新获得的基于量规的数据。结果发现,各种再分析系统给出的季节间至年度间的降雨赤字和盈余有时与APHRODITE数据中看到的空间格局不匹配。此外,随着计算值所基于的时标的增加,显示标准化降水指数(SPI)的地图变得越来越不可靠。相反,基于轨距的降雨数据集的性能令人满意,并且SPI图的质量不会随时间尺度的增加而衰减。总体而言,发现CAMS-OPI对于监测东亚地区的大规模降水变化是可靠的。

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