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仅利用红外和经过雨量计校准的多卫星降水产品在估算印度西南季风降水方面的准确性如何?

How accurate are infrared-only and rain gauge-adjusted multi-satellite precipitation products in the southwest monsoon precipitation estimation across India?

作者信息

Prakash Satya, Bhan S C

机构信息

India Meteorological Department, Ministry of Earth Sciences, New Delhi-110 003, India.

出版信息

Environ Monit Assess. 2023 Mar 28;195(4):515. doi: 10.1007/s10661-023-11148-2.

Abstract

A dense network of rain gauges and considerably large variability of the southwest monsoon precipitation across the country make India a suitable test-bed to evaluate any satellite-based precipitation product. In this paper, three real-time infrared-only precipitation products derived from the INSAT-3D satellite namely, INSAT Multispectral Rainfall (IMR), Corrected IMR (IMC) and Hydro-Estimator (HEM) and three rain gauge-adjusted Global Precipitation Measurement (GPM)-based multi-satellite precipitation products namely, Integrated Multi-satellitE Retrievals for GPM (IMERG), Global Satellite Mapping of Precipitation (GSMaP) and an Indian merged satellite-gauge product (INMSG) have been evaluated over India at a daily timescale for the southwest monsoon seasons of 2020 and 2021. An evaluation against rain gauge-based gridded reference dataset shows noticeable reduction of bias in IMC product over IMR, primarily over the orographic regions. However, INSAT-3D infrared-only precipitation retrieval algorithms have limitations in shallow and convective precipitation estimation. Among rain gauge-adjusted multi-satellite products, INMSG is shown to be the best product in the monsoon precipitation estimation over India due to use of rather larger number of rain gauges than IMERG and GSMaP products. All satellite-derived precipitation products, i.e. infrared-only and gauge-adjusted multi-satellite products underestimate heavy monsoon precipitation by 50-70%. The bias decomposition analysis indicates that a simple statistical bias correction would considerably improve the performance of the INSAT-3D precipitation products over the central India, but the same might not work over the west coast due to rather larger contributions of both positive and negative hit bias components. Although rain gauge-adjusted multi-satellite precipitation products show very small or negligible total biases in the monsoon precipitation estimation, positive and negative hit bias components are considerable over the west coast and central India. Furthermore, rain gauge-adjusted multi-satellite precipitation products underestimate very heavy to extremely heavy precipitation with larger magnitudes than the INSAT-3D derived precipitation products over the central India. Among the rain gauge-adjusted multi-satellite precipitation products, INMSG has smaller bias and error than IMERG and GSMaP products for very heavy to extremely heavy monsoon precipitation over the west coast and central India. Preliminary results of this study would be useful for end users in choosing a better precipitation product for real-time and research applications as well as for algorithm developers in further improving these products.

摘要

密集的雨量计网络以及印度全国范围内西南季风降水的显著大变化,使印度成为评估任何基于卫星的降水产品的合适试验场。在本文中,对2020年和2021年西南季风季节期间,源自INSAT - 3D卫星的三种仅利用实时红外数据的降水产品,即INSAT多光谱降雨(IMR)、校正后的IMR(IMC)和水文估算器(HEM),以及三种经过雨量计校准的基于全球降水测量(GPM)的多卫星降水产品,即GPM的综合多卫星反演(IMERG)、全球降水卫星地图(GSMaP)和一种印度合并卫星 - 雨量计产品(INMSG),在印度进行了每日时间尺度的评估。与基于雨量计的网格化参考数据集进行的评估表明,IMC产品相对于IMR产品,偏差有显著降低,主要是在地形区域。然而,INSAT - 3D仅利用红外数据的降水反演算法在浅对流降水估计方面存在局限性。在经过雨量计校准的多卫星产品中,由于使用的雨量计数量比IMERG和GSMaP产品更多,INMSG在印度季风降水估计中被证明是最佳产品。所有基于卫星的降水产品,即仅利用红外数据的产品和经过雨量计校准的多卫星产品,都将强季风降水低估了50 - 70%。偏差分解分析表明,简单的统计偏差校正将显著提高INSAT - 3D降水产品在印度中部的性能,但由于正负命中偏差分量的贡献都较大,在西海岸可能不起作用。尽管经过雨量计校准的多卫星降水产品在季风降水估计中显示出非常小或可忽略不计的总偏差,但正负命中偏差分量在西海岸和印度中部相当可观。此外,经过雨量计校准的多卫星降水产品在印度中部对非常大到极其大的降水的低估幅度,比INSAT - 3D衍生的降水产品更大。在经过雨量计校准的多卫星降水产品中,对于西海岸和印度中部非常大到极其大的季风降水,INMSG的偏差和误差比IMERG和GSMaP产品更小。这项研究的初步结果将有助于终端用户选择更好的降水产品用于实时和研究应用,也有助于算法开发者进一步改进这些产品。

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