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印度半干旱地区高分辨率多卫星和再分析降水产品的时空性能评估。

Spatiotemporal performance evaluation of high-resolution multiple satellite and reanalysis precipitation products over the semiarid region of India.

机构信息

Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore, India.

Centre for Agricultural and Rural Development Studies, Tamil Nadu Agricultural University, Coimbatore, India.

出版信息

Environ Monit Assess. 2024 Oct 3;196(11):1006. doi: 10.1007/s10661-024-13152-6.

Abstract

The present investigation evaluates three satellite precipitation products (SPPs), Multi-Source Weighted-Ensemble Precipitation (MSWEP), Global Precipitation Climatology Centre (GPCC), Climate Hazard Infrared Precipitation with Station Data (CHIRPS), and two reanalysis datasets, namely, the ERA5 atmosphere reanalysis dataset (ERA5) and Indian Monsoon Data Assimilation and Analysis (IMDAA), against the good quality gridded reference dataset (1991-2022) developed by the India Meteorological Department (IMD). The evaluation was carried out in terms of the rainfall detection ability and estimation accuracy of the products using metrics such as the false alarm ratio (FAR), probability of detection (POD), misses, root mean square error (RMSE), and percent bias (PBIAS). Among all the rainfall products, ERA5 had the best ability to capture rainfall events with a higher POD, followed by MSWEP. Both MSWEP and ERA5 had PODs of 70-100% in more than 90% of the grids and less than 35% of missing rainfall events in the entire Tamil Nadu. In the case of the rainfall estimation accuracy evaluation, the MSWEP exhibited superior performance, with lower RMSEs and biases ranging from - 25 to 25% at the annual and seasonal scales. In northeast monsoon (NEM), CHIRPS demonstrated a comparable performance to that of MSWEP in terms of the RMSE and PBIAS. These findings will help product users select the best reliable rainfall dataset for improved research, diversified applications in various sectors, and policy-making decisions.

摘要

本研究评估了三种卫星降水产品(SPP),即多源加权集合降水(MSWEP)、全球降水气候中心(GPCC)、气候危险红外降水与站数据(CHIRPS),以及两个再分析数据集,即欧洲中期天气预报中心大气再分析数据集(ERA5)和印度季风数据同化与分析(IMDAA),与印度气象局(IMD)开发的高质量格网参考数据集(1991-2022 年)进行对比。评估使用了错误警报率(FAR)、探测概率(POD)、漏报、均方根误差(RMSE)和偏度百分比(PBIAS)等指标,评估了产品的降水检测能力和估计精度。在所有降水产品中,ERA5 具有最高的捕捉降水事件的能力,POD 较高,其次是 MSWEP。MSWEP 和 ERA5 在超过 90%的格网中 POD 达到 70-100%,在整个泰米尔纳德邦中漏报降水事件不到 35%。在降水估计精度评估方面,MSWEP 表现出卓越的性能,其 RMSE 和偏度在年度和季节尺度上的范围为-25%至 25%。在东北季风(NEM)期间,CHIRPS 在 RMSE 和 PBIAS 方面与 MSWEP 具有可比的性能。这些发现将帮助产品用户选择最佳可靠的降水数据集,以改进研究、在各个领域多样化应用和决策制定。

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