Assessment on IMERG V06 Precipitation Products Using Rain Gauge Data in Jinan City, Shandong Province, China
In this study, a comprehensive assessment on precipitation estimation from the latest Version 06 release of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) algorithm is conducted by using 24 rain gauge observations at daily scale from 2001 to 2016. The IMERG V0...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-03-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/7/1241 |
| _version_ | 1827696842387750912 |
|---|---|
| author | Peng Li Zongxue Xu Chenlei Ye Meifang Ren Hao Chen Jingjing Wang Sulin Song |
| author_facet | Peng Li Zongxue Xu Chenlei Ye Meifang Ren Hao Chen Jingjing Wang Sulin Song |
| author_sort | Peng Li |
| collection | DOAJ |
| description | In this study, a comprehensive assessment on precipitation estimation from the latest Version 06 release of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) algorithm is conducted by using 24 rain gauge observations at daily scale from 2001 to 2016. The IMERG V06 dataset fuses Tropical Rainfall Measuring Mission (TRMM) satellite data (2000–2015) and Global Precipitation Measurement (GPM) satellite data (2014–present), enabling the use of IMERG data for long-term study. Correlation coefficient (CC), root mean square error (RMSE), relative bias (RB), probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) were used to assess the accuracy of satellite-derived precipitation estimation and measure the correspondence between satellite-derived and observed occurrence of precipitation events. The probability density distributions of precipitation intensity and influence of elevation on precipitation estimation were also examined. Results showed that, with high CC and low RMSE and RB, the IMERG Final Run product (IMERG-F) performs better than two other IMERG products at daily, monthly, and yearly scales. At daily scale, the ability of satellite products to detect general precipitation is clearly superior to the ability to detect heavy and extreme precipitation. In addition, CC and RMSE of IMERG products are high in Southeastern Jinan City, while RMSE is relatively low in Southwestern Jinan City. Considering the fact that the IMERG estimation of extreme precipitation indices showed an acceptable level of accuracy, IMERG products can be used to derive extreme precipitation indices in areas without gauged data. At all elevations, IMERG-F exhibits a better performance than the other two IMERG products. However, POD and FAR decrease and CSI increase with the increase of elevation, indicating the need for improvement. This study will provide valuable information for the application of IMERG products at the scale of a large city. |
| first_indexed | 2024-03-10T12:56:00Z |
| format | Article |
| id | doaj.art-4cd98c0b8e5d46ee93c463a6d7b1bafd |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T12:56:00Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-4cd98c0b8e5d46ee93c463a6d7b1bafd2023-11-21T11:53:27ZengMDPI AGRemote Sensing2072-42922021-03-01137124110.3390/rs13071241Assessment on IMERG V06 Precipitation Products Using Rain Gauge Data in Jinan City, Shandong Province, ChinaPeng Li0Zongxue Xu1Chenlei Ye2Meifang Ren3Hao Chen4Jingjing Wang5Sulin Song6College of Water Sciences, Beijing Normal University, Beijing 100875, ChinaCollege of Water Sciences, Beijing Normal University, Beijing 100875, ChinaCollege of Water Sciences, Beijing Normal University, Beijing 100875, ChinaCollege of Water Sciences, Beijing Normal University, Beijing 100875, ChinaCollege of Water Sciences, Beijing Normal University, Beijing 100875, ChinaCollege of Water Sciences, Beijing Normal University, Beijing 100875, ChinaJinan Hydrology Bureau, Jinan 250014, ChinaIn this study, a comprehensive assessment on precipitation estimation from the latest Version 06 release of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) algorithm is conducted by using 24 rain gauge observations at daily scale from 2001 to 2016. The IMERG V06 dataset fuses Tropical Rainfall Measuring Mission (TRMM) satellite data (2000–2015) and Global Precipitation Measurement (GPM) satellite data (2014–present), enabling the use of IMERG data for long-term study. Correlation coefficient (CC), root mean square error (RMSE), relative bias (RB), probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) were used to assess the accuracy of satellite-derived precipitation estimation and measure the correspondence between satellite-derived and observed occurrence of precipitation events. The probability density distributions of precipitation intensity and influence of elevation on precipitation estimation were also examined. Results showed that, with high CC and low RMSE and RB, the IMERG Final Run product (IMERG-F) performs better than two other IMERG products at daily, monthly, and yearly scales. At daily scale, the ability of satellite products to detect general precipitation is clearly superior to the ability to detect heavy and extreme precipitation. In addition, CC and RMSE of IMERG products are high in Southeastern Jinan City, while RMSE is relatively low in Southwestern Jinan City. Considering the fact that the IMERG estimation of extreme precipitation indices showed an acceptable level of accuracy, IMERG products can be used to derive extreme precipitation indices in areas without gauged data. At all elevations, IMERG-F exhibits a better performance than the other two IMERG products. However, POD and FAR decrease and CSI increase with the increase of elevation, indicating the need for improvement. This study will provide valuable information for the application of IMERG products at the scale of a large city.https://www.mdpi.com/2072-4292/13/7/1241global precipitation measurementIMERGassessmentextreme precipitation |
| spellingShingle | Peng Li Zongxue Xu Chenlei Ye Meifang Ren Hao Chen Jingjing Wang Sulin Song Assessment on IMERG V06 Precipitation Products Using Rain Gauge Data in Jinan City, Shandong Province, China Remote Sensing global precipitation measurement IMERG assessment extreme precipitation |
| title | Assessment on IMERG V06 Precipitation Products Using Rain Gauge Data in Jinan City, Shandong Province, China |
| title_full | Assessment on IMERG V06 Precipitation Products Using Rain Gauge Data in Jinan City, Shandong Province, China |
| title_fullStr | Assessment on IMERG V06 Precipitation Products Using Rain Gauge Data in Jinan City, Shandong Province, China |
| title_full_unstemmed | Assessment on IMERG V06 Precipitation Products Using Rain Gauge Data in Jinan City, Shandong Province, China |
| title_short | Assessment on IMERG V06 Precipitation Products Using Rain Gauge Data in Jinan City, Shandong Province, China |
| title_sort | assessment on imerg v06 precipitation products using rain gauge data in jinan city shandong province china |
| topic | global precipitation measurement IMERG assessment extreme precipitation |
| url | https://www.mdpi.com/2072-4292/13/7/1241 |
| work_keys_str_mv | AT pengli assessmentonimergv06precipitationproductsusingraingaugedatainjinancityshandongprovincechina AT zongxuexu assessmentonimergv06precipitationproductsusingraingaugedatainjinancityshandongprovincechina AT chenleiye assessmentonimergv06precipitationproductsusingraingaugedatainjinancityshandongprovincechina AT meifangren assessmentonimergv06precipitationproductsusingraingaugedatainjinancityshandongprovincechina AT haochen assessmentonimergv06precipitationproductsusingraingaugedatainjinancityshandongprovincechina AT jingjingwang assessmentonimergv06precipitationproductsusingraingaugedatainjinancityshandongprovincechina AT sulinsong assessmentonimergv06precipitationproductsusingraingaugedatainjinancityshandongprovincechina |