Convective-scale forecast errors over Taiwan: an ensemble analysis of error covariances and their influences
Abstract This study investigates the characteristics of ensemble-based forecast errors at the convective scale over the land of Taiwan and the adjacent sea. A case study during the Southwest Monsoon Experiment/Terrain-influenced Monsoon Rainfall Experiment (SoWMEX/TiMREX) intensive observation perio...
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| Format: | Article |
| Language: | English |
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Springer
2025-03-01
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| Series: | Terrestrial, Atmospheric and Oceanic Sciences |
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| Online Access: | https://doi.org/10.1007/s44195-025-00092-y |
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| author | Kao-Shen Chung Chih-Chien Tsai Li-Hsin Chen Shu-Chih Yang |
| author_facet | Kao-Shen Chung Chih-Chien Tsai Li-Hsin Chen Shu-Chih Yang |
| author_sort | Kao-Shen Chung |
| collection | DOAJ |
| description | Abstract This study investigates the characteristics of ensemble-based forecast errors at the convective scale over the land of Taiwan and the adjacent sea. A case study during the Southwest Monsoon Experiment/Terrain-influenced Monsoon Rainfall Experiment (SoWMEX/TiMREX) intensive observation period 8 (IOP 8) in 2008 is selected. Using a set of 72-member ensemble forecasts generated by the Weather Research and Forecasting (WRF) model, the structures of error variance and error correlation are examined. It is found that the coverage of the cold pool significantly influences the error variances of wind and temperature near the surface. Additionally, a comparison of the horizontal wind error variance between 9 and 3-km ensembles reveals that higher-resolution (3-km) ensemble forecasts not only better capture the uncertainties of severe weather but also display the features of multi-scale interactions within the southwesterly flow. The error variances of state variables are closely associated with the development of the weather system, including factors such as divergence and latent heating. The spatial and temporal error covariances of dynamic and thermodynamic variables under different conditions imply a potential disparity in the impact on high-resolution data assimilation. This information could provide valuable guidance for further studies on the ensemble data assimilation system over the island of Taiwan. |
| format | Article |
| id | doaj-art-eea28ed1da9f4e27920777a9c22ca759 |
| institution | DOAJ |
| issn | 1017-0839 2311-7680 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Springer |
| record_format | Article |
| series | Terrestrial, Atmospheric and Oceanic Sciences |
| spelling | doaj-art-eea28ed1da9f4e27920777a9c22ca7592025-08-20T02:49:32ZengSpringerTerrestrial, Atmospheric and Oceanic Sciences1017-08392311-76802025-03-0136112010.1007/s44195-025-00092-yConvective-scale forecast errors over Taiwan: an ensemble analysis of error covariances and their influencesKao-Shen Chung0Chih-Chien Tsai1Li-Hsin Chen2Shu-Chih Yang3Department of Atmospheric Sciences, National Central UniversityNational Science and Technology Center for Disaster ReductionDepartment of Atmospheric Sciences, National Central UniversityDepartment of Atmospheric Sciences, National Central UniversityAbstract This study investigates the characteristics of ensemble-based forecast errors at the convective scale over the land of Taiwan and the adjacent sea. A case study during the Southwest Monsoon Experiment/Terrain-influenced Monsoon Rainfall Experiment (SoWMEX/TiMREX) intensive observation period 8 (IOP 8) in 2008 is selected. Using a set of 72-member ensemble forecasts generated by the Weather Research and Forecasting (WRF) model, the structures of error variance and error correlation are examined. It is found that the coverage of the cold pool significantly influences the error variances of wind and temperature near the surface. Additionally, a comparison of the horizontal wind error variance between 9 and 3-km ensembles reveals that higher-resolution (3-km) ensemble forecasts not only better capture the uncertainties of severe weather but also display the features of multi-scale interactions within the southwesterly flow. The error variances of state variables are closely associated with the development of the weather system, including factors such as divergence and latent heating. The spatial and temporal error covariances of dynamic and thermodynamic variables under different conditions imply a potential disparity in the impact on high-resolution data assimilation. This information could provide valuable guidance for further studies on the ensemble data assimilation system over the island of Taiwan.https://doi.org/10.1007/s44195-025-00092-yConvective scaleEnsemble forecastsError varianceError correlationData assimilation |
| spellingShingle | Kao-Shen Chung Chih-Chien Tsai Li-Hsin Chen Shu-Chih Yang Convective-scale forecast errors over Taiwan: an ensemble analysis of error covariances and their influences Terrestrial, Atmospheric and Oceanic Sciences Convective scale Ensemble forecasts Error variance Error correlation Data assimilation |
| title | Convective-scale forecast errors over Taiwan: an ensemble analysis of error covariances and their influences |
| title_full | Convective-scale forecast errors over Taiwan: an ensemble analysis of error covariances and their influences |
| title_fullStr | Convective-scale forecast errors over Taiwan: an ensemble analysis of error covariances and their influences |
| title_full_unstemmed | Convective-scale forecast errors over Taiwan: an ensemble analysis of error covariances and their influences |
| title_short | Convective-scale forecast errors over Taiwan: an ensemble analysis of error covariances and their influences |
| title_sort | convective scale forecast errors over taiwan an ensemble analysis of error covariances and their influences |
| topic | Convective scale Ensemble forecasts Error variance Error correlation Data assimilation |
| url | https://doi.org/10.1007/s44195-025-00092-y |
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