Multiscale Performance of Global Blended Satellite Precipitation Products Over Taiwan
Strong land–ocean interactions and complex terrain have been challenging the accuracy of satellite precipitation products (SPPs). To recognize the error patterns of the mainstream SPPs over Taiwan, this study evaluates the temporal and spatial performance of NOAA Climate Prediction Center...
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10756198/ |
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| author | Liping Wang Haonan Chen Zhe Li |
| author_facet | Liping Wang Haonan Chen Zhe Li |
| author_sort | Liping Wang |
| collection | DOAJ |
| description | Strong land–ocean interactions and complex terrain have been challenging the accuracy of satellite precipitation products (SPPs). To recognize the error patterns of the mainstream SPPs over Taiwan, this study evaluates the temporal and spatial performance of NOAA Climate Prediction Center (CPC) morphing technique (CMORPH V1) and NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG V07 Final) during 2019–2021, with an emphasis on exploring the multi-scale performance of CMORPH and IMERG and their dependence on precipitation intensity and season. The precipitation estimates produced from the operational Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system are employed as ground-based reference data, and various statistical metrics are calculated against this reference grid by grid to evaluate the performance of CMORPH and IMERG at yearly, seasonal and daily scales. A wide range of evaluation metrics such as the relative bias (RB), Pearson correlation coefficient (CC), mean error (ME), normalized mean error (NME), mean absolute error (MAE), normalized mean absolute error (NMAE) and root mean squared error (RMSE) are considered in the study. The verification skills of SPPs at different precipitation intensity thresholds is analyzed through the probability of detection (POD), false alarm ratio (FAR), frequency bias index (FBI) and Heidke skill score (HSS). It is universally observed that both products are prone to underestimate precipitation over Taiwan, especially over high-elevation locations. Overall, CMORPH shows a better capability of capturing the precipitation spatial patterns and IMERG has smaller estimation errors of rainfall intensity than CMORPH over Taiwan. |
| format | Article |
| id | doaj-art-f5caaa98199144b5b5dbac0961c97bcf |
| institution | Kabale University |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-f5caaa98199144b5b5dbac0961c97bcf2025-01-16T00:00:26ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-01182108212510.1109/JSTARS.2024.349991010756198Multiscale Performance of Global Blended Satellite Precipitation Products Over TaiwanLiping Wang0https://orcid.org/0000-0002-9594-026XHaonan Chen1https://orcid.org/0000-0002-9795-3064Zhe Li2https://orcid.org/0000-0003-3241-5641Colorado State University, Fort Collins, CO, USAColorado State University, Fort Collins, CO, USAColorado State University, Fort Collins, CO, USAStrong land–ocean interactions and complex terrain have been challenging the accuracy of satellite precipitation products (SPPs). To recognize the error patterns of the mainstream SPPs over Taiwan, this study evaluates the temporal and spatial performance of NOAA Climate Prediction Center (CPC) morphing technique (CMORPH V1) and NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG V07 Final) during 2019–2021, with an emphasis on exploring the multi-scale performance of CMORPH and IMERG and their dependence on precipitation intensity and season. The precipitation estimates produced from the operational Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system are employed as ground-based reference data, and various statistical metrics are calculated against this reference grid by grid to evaluate the performance of CMORPH and IMERG at yearly, seasonal and daily scales. A wide range of evaluation metrics such as the relative bias (RB), Pearson correlation coefficient (CC), mean error (ME), normalized mean error (NME), mean absolute error (MAE), normalized mean absolute error (NMAE) and root mean squared error (RMSE) are considered in the study. The verification skills of SPPs at different precipitation intensity thresholds is analyzed through the probability of detection (POD), false alarm ratio (FAR), frequency bias index (FBI) and Heidke skill score (HSS). It is universally observed that both products are prone to underestimate precipitation over Taiwan, especially over high-elevation locations. Overall, CMORPH shows a better capability of capturing the precipitation spatial patterns and IMERG has smaller estimation errors of rainfall intensity than CMORPH over Taiwan.https://ieeexplore.ieee.org/document/10756198/Climate Prediction Center morphing technique (CMORPH)error analysisIntegrated MultisatellitE Retrievals for the Global Precipitation Measurement mission (IMERG)satellite precipitation products (SPPs)Taiwan |
| spellingShingle | Liping Wang Haonan Chen Zhe Li Multiscale Performance of Global Blended Satellite Precipitation Products Over Taiwan IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Climate Prediction Center morphing technique (CMORPH) error analysis Integrated MultisatellitE Retrievals for the Global Precipitation Measurement mission (IMERG) satellite precipitation products (SPPs) Taiwan |
| title | Multiscale Performance of Global Blended Satellite Precipitation Products Over Taiwan |
| title_full | Multiscale Performance of Global Blended Satellite Precipitation Products Over Taiwan |
| title_fullStr | Multiscale Performance of Global Blended Satellite Precipitation Products Over Taiwan |
| title_full_unstemmed | Multiscale Performance of Global Blended Satellite Precipitation Products Over Taiwan |
| title_short | Multiscale Performance of Global Blended Satellite Precipitation Products Over Taiwan |
| title_sort | multiscale performance of global blended satellite precipitation products over taiwan |
| topic | Climate Prediction Center morphing technique (CMORPH) error analysis Integrated MultisatellitE Retrievals for the Global Precipitation Measurement mission (IMERG) satellite precipitation products (SPPs) Taiwan |
| url | https://ieeexplore.ieee.org/document/10756198/ |
| work_keys_str_mv | AT lipingwang multiscaleperformanceofglobalblendedsatelliteprecipitationproductsovertaiwan AT haonanchen multiscaleperformanceofglobalblendedsatelliteprecipitationproductsovertaiwan AT zheli multiscaleperformanceofglobalblendedsatelliteprecipitationproductsovertaiwan |