Towards Improved Satellite Data Utilization in China: Insights from an Integrated Evaluation of GSMaP-GNRT6 in Rainfall Patterns
To improve the utilization of satellite-based data and promote their development, this analysis comprehensively evaluates the performance of GSMaP Near-real-time Gauge-adjusted Rainfall Product version 6 (GSMaP_GNRT6) data in depicting precipitation over China from 2001 to 2020 by comparing four pre...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-02-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/16/5/755 |
| _version_ | 1797263984285450240 |
|---|---|
| author | Zunya Wang Qingquan Li |
| author_facet | Zunya Wang Qingquan Li |
| author_sort | Zunya Wang |
| collection | DOAJ |
| description | To improve the utilization of satellite-based data and promote their development, this analysis comprehensively evaluates the performance of GSMaP Near-real-time Gauge-adjusted Rainfall Product version 6 (GSMaP_GNRT6) data in depicting precipitation over China from 2001 to 2020 by comparing four precipitation indices—accumulated precipitation, number of rainy days and rainstorm days, and precipitation maxima—with daily precipitation data from 2419 stations across China on monthly and annual time scales. The results show that the GSMaP-GNRT6 data effectively capture the overall spatial pattern of the four precipitation indices, but biases in the spatial distribution of the number of rainy days from July to September and the precipitation maxima during the wintertime are evident. A general underestimation of GSMaP-GNRT6 data is observed in the average for China. The annual precipitation amount, the number of rainy days and rainstorm days, and the precipitation maxima based on the GSMaP-GNRT6 data are 17.6%, 35.5%, 31.6% and 11.8% below the station observations, respectively. The GSMaP-GNRT6 data better depict the precipitation in eastern China, with the errors almost halved. And obvious overestimation of the number of rainstorm days and precipitation maxima occurs in western China, reaching up to 60%. Regarding the accumulated precipitation, the number of rainstorm days and the precipitation maxima, the GSMaP-GNRT6 data show an almost consistent interannual variation and increasing trends that are consistent with the station observations. However, the magnitude of the increasing trend based on the GSMaP-GNRT6 data is larger, especially at the beginning of the 21st century. Conversely, a considerable discrepancy in the annual variation and an almost opposite trend can be observed in the number of rainy days between the GSMaP-GNRT6 data and the station observations. |
| first_indexed | 2024-04-25T00:21:41Z |
| format | Article |
| id | doaj.art-f7de424b70e64dd191a619f146ea4f7a |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-25T00:21:41Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-f7de424b70e64dd191a619f146ea4f7a2024-03-12T16:53:54ZengMDPI AGRemote Sensing2072-42922024-02-0116575510.3390/rs16050755Towards Improved Satellite Data Utilization in China: Insights from an Integrated Evaluation of GSMaP-GNRT6 in Rainfall PatternsZunya Wang0Qingquan Li1China Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Center, Beijing 100081, ChinaChina Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Center, Beijing 100081, ChinaTo improve the utilization of satellite-based data and promote their development, this analysis comprehensively evaluates the performance of GSMaP Near-real-time Gauge-adjusted Rainfall Product version 6 (GSMaP_GNRT6) data in depicting precipitation over China from 2001 to 2020 by comparing four precipitation indices—accumulated precipitation, number of rainy days and rainstorm days, and precipitation maxima—with daily precipitation data from 2419 stations across China on monthly and annual time scales. The results show that the GSMaP-GNRT6 data effectively capture the overall spatial pattern of the four precipitation indices, but biases in the spatial distribution of the number of rainy days from July to September and the precipitation maxima during the wintertime are evident. A general underestimation of GSMaP-GNRT6 data is observed in the average for China. The annual precipitation amount, the number of rainy days and rainstorm days, and the precipitation maxima based on the GSMaP-GNRT6 data are 17.6%, 35.5%, 31.6% and 11.8% below the station observations, respectively. The GSMaP-GNRT6 data better depict the precipitation in eastern China, with the errors almost halved. And obvious overestimation of the number of rainstorm days and precipitation maxima occurs in western China, reaching up to 60%. Regarding the accumulated precipitation, the number of rainstorm days and the precipitation maxima, the GSMaP-GNRT6 data show an almost consistent interannual variation and increasing trends that are consistent with the station observations. However, the magnitude of the increasing trend based on the GSMaP-GNRT6 data is larger, especially at the beginning of the 21st century. Conversely, a considerable discrepancy in the annual variation and an almost opposite trend can be observed in the number of rainy days between the GSMaP-GNRT6 data and the station observations.https://www.mdpi.com/2072-4292/16/5/755GSMaP-GNRT6station observationsvalidationprecipitationrainy daysrainstorm days |
| spellingShingle | Zunya Wang Qingquan Li Towards Improved Satellite Data Utilization in China: Insights from an Integrated Evaluation of GSMaP-GNRT6 in Rainfall Patterns Remote Sensing GSMaP-GNRT6 station observations validation precipitation rainy days rainstorm days |
| title | Towards Improved Satellite Data Utilization in China: Insights from an Integrated Evaluation of GSMaP-GNRT6 in Rainfall Patterns |
| title_full | Towards Improved Satellite Data Utilization in China: Insights from an Integrated Evaluation of GSMaP-GNRT6 in Rainfall Patterns |
| title_fullStr | Towards Improved Satellite Data Utilization in China: Insights from an Integrated Evaluation of GSMaP-GNRT6 in Rainfall Patterns |
| title_full_unstemmed | Towards Improved Satellite Data Utilization in China: Insights from an Integrated Evaluation of GSMaP-GNRT6 in Rainfall Patterns |
| title_short | Towards Improved Satellite Data Utilization in China: Insights from an Integrated Evaluation of GSMaP-GNRT6 in Rainfall Patterns |
| title_sort | towards improved satellite data utilization in china insights from an integrated evaluation of gsmap gnrt6 in rainfall patterns |
| topic | GSMaP-GNRT6 station observations validation precipitation rainy days rainstorm days |
| url | https://www.mdpi.com/2072-4292/16/5/755 |
| work_keys_str_mv | AT zunyawang towardsimprovedsatellitedatautilizationinchinainsightsfromanintegratedevaluationofgsmapgnrt6inrainfallpatterns AT qingquanli towardsimprovedsatellitedatautilizationinchinainsightsfromanintegratedevaluationofgsmapgnrt6inrainfallpatterns |