The evaluation and downscaling‐calibration of IMERG precipitation products at sub‐daily scales over a metropolitan region
Abstract The Global Precipitation Measurement (GPM) Integrated Multi‐satellitE Retrievals for GPM products (i.e., IMERG) provide new‐generation satellite precipitation measurements. For urban contexts, however, the issues of its bias and insufficient resolutions still exist. This study aims to devel...
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Format: | Article |
Language: | English |
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Wiley
2023-09-01
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Series: | Journal of Flood Risk Management |
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Online Access: | https://doi.org/10.1111/jfr3.12902 |
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author | Qi Zhuang Zhengzheng Zhou Shuguang Liu Daniel B. Wright Lisha Gao |
author_facet | Qi Zhuang Zhengzheng Zhou Shuguang Liu Daniel B. Wright Lisha Gao |
author_sort | Qi Zhuang |
collection | DOAJ |
description | Abstract The Global Precipitation Measurement (GPM) Integrated Multi‐satellitE Retrievals for GPM products (i.e., IMERG) provide new‐generation satellite precipitation measurements. For urban contexts, however, the issues of its bias and insufficient resolutions still exist. This study aims to develop high‐precision and high‐resolution (e.g., 0.01°/1 h) data for a metropolitan region based on IMERG and gauge precipitations. The original IMERG product is evaluated using hourly in situ precipitations from 47 gauges. A spatial downscaling‐calibration (DC) technique is then developed to enhance the IMERG using the Normalized Difference Vegetation Index. The results show the limited capability of IMERG to capture sub‐daily precipitation and high‐intensity precipitation. The proposed DC method significantly improves IMERG performance, with correlation coefficient (CC) increasing from 0.07 to 0.75, and probability of detection improving from 0.34 to 0.90 at the hourly scale. In terms of spatial rainfall distribution, 86% of mean absolute error and 80% of RMSE are improved with CC increasing from 0.07 to 0.91 on average. Additionally, the calibrated downscaled product provides finer information in local areas, capturing three times more spatial variabilities of urban precipitation against the original IMERG input data. The results highlight the necessity of improving urban observations for flood risk management at fine spatiotemporal resolutions. |
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format | Article |
id | doaj.art-9d97b05c3642499d896e349d241aa084 |
institution | Directory Open Access Journal |
issn | 1753-318X |
language | English |
last_indexed | 2024-03-12T12:16:53Z |
publishDate | 2023-09-01 |
publisher | Wiley |
record_format | Article |
series | Journal of Flood Risk Management |
spelling | doaj.art-9d97b05c3642499d896e349d241aa0842023-08-30T10:00:52ZengWileyJournal of Flood Risk Management1753-318X2023-09-01163n/an/a10.1111/jfr3.12902The evaluation and downscaling‐calibration of IMERG precipitation products at sub‐daily scales over a metropolitan regionQi Zhuang0Zhengzheng Zhou1Shuguang Liu2Daniel B. Wright3Lisha Gao4Department of Hydraulic Engineering Tongji University Shanghai ChinaDepartment of Hydraulic Engineering Tongji University Shanghai ChinaDepartment of Hydraulic Engineering Tongji University Shanghai ChinaDepartment of Civil and Environmental Engineering University of Wisconsin‐Madison Madison Wisconsin USAShanghai Water Planning and Design Research Institute (Shanghai Ocean Planning and Design Research Institute) Shanghai ChinaAbstract The Global Precipitation Measurement (GPM) Integrated Multi‐satellitE Retrievals for GPM products (i.e., IMERG) provide new‐generation satellite precipitation measurements. For urban contexts, however, the issues of its bias and insufficient resolutions still exist. This study aims to develop high‐precision and high‐resolution (e.g., 0.01°/1 h) data for a metropolitan region based on IMERG and gauge precipitations. The original IMERG product is evaluated using hourly in situ precipitations from 47 gauges. A spatial downscaling‐calibration (DC) technique is then developed to enhance the IMERG using the Normalized Difference Vegetation Index. The results show the limited capability of IMERG to capture sub‐daily precipitation and high‐intensity precipitation. The proposed DC method significantly improves IMERG performance, with correlation coefficient (CC) increasing from 0.07 to 0.75, and probability of detection improving from 0.34 to 0.90 at the hourly scale. In terms of spatial rainfall distribution, 86% of mean absolute error and 80% of RMSE are improved with CC increasing from 0.07 to 0.91 on average. Additionally, the calibrated downscaled product provides finer information in local areas, capturing three times more spatial variabilities of urban precipitation against the original IMERG input data. The results highlight the necessity of improving urban observations for flood risk management at fine spatiotemporal resolutions.https://doi.org/10.1111/jfr3.12902calibrationdownscalingIMERGNDVIprecipitationsub‐daily |
spellingShingle | Qi Zhuang Zhengzheng Zhou Shuguang Liu Daniel B. Wright Lisha Gao The evaluation and downscaling‐calibration of IMERG precipitation products at sub‐daily scales over a metropolitan region Journal of Flood Risk Management calibration downscaling IMERG NDVI precipitation sub‐daily |
title | The evaluation and downscaling‐calibration of IMERG precipitation products at sub‐daily scales over a metropolitan region |
title_full | The evaluation and downscaling‐calibration of IMERG precipitation products at sub‐daily scales over a metropolitan region |
title_fullStr | The evaluation and downscaling‐calibration of IMERG precipitation products at sub‐daily scales over a metropolitan region |
title_full_unstemmed | The evaluation and downscaling‐calibration of IMERG precipitation products at sub‐daily scales over a metropolitan region |
title_short | The evaluation and downscaling‐calibration of IMERG precipitation products at sub‐daily scales over a metropolitan region |
title_sort | evaluation and downscaling calibration of imerg precipitation products at sub daily scales over a metropolitan region |
topic | calibration downscaling IMERG NDVI precipitation sub‐daily |
url | https://doi.org/10.1111/jfr3.12902 |
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