Enhancing seasonal predictability of the East Asian summer monsoon via optimized multi-model ensembles
Abstract The East Asian summer monsoon (EASM) exhibits complex and variable behavior that challenges the reliability of seasonal forecasts. In this study, we develop an optimized multi-model ensemble (MME) framework to enhance both the skill and confidence of EASM precipitation predictions. Unlike c...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-08794-6 |
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| author | OkYeon Kim Woo-Seop Lee |
| author_facet | OkYeon Kim Woo-Seop Lee |
| author_sort | OkYeon Kim |
| collection | DOAJ |
| description | Abstract The East Asian summer monsoon (EASM) exhibits complex and variable behavior that challenges the reliability of seasonal forecasts. In this study, we develop an optimized multi-model ensemble (MME) framework to enhance both the skill and confidence of EASM precipitation predictions. Unlike conventional MMEs that include all available models without performance filtering, the optimized MMEs are constructed by selecting only those models that demonstrate both high temporal correlation with observed principal components and a sufficiently large signal-to-total variance ratio. These criteria are quantified using the ratio of predictability components (RPC), which jointly captures real-world and model-based predictability. Results show that the optimized MMEs significantly outperform conventional MMEs in forecasting EASM rainfall: prediction skill improves by up to 13.4% and signal variance increases by up to 22.6%, particularly over East Asia. These improvements indicate not only higher forecast accuracy but also greater confidence in seasonal predictions. Our findings demonstrate that applying an RPC-based model selection method provides a robust strategy for improving seasonal climate forecasts in monsoon-affected regions. |
| format | Article |
| id | doaj-art-e6f5487b6eb744618f8c5452cade35b8 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-e6f5487b6eb744618f8c5452cade35b82025-08-20T03:45:56ZengNature PortfolioScientific Reports2045-23222025-07-0115111310.1038/s41598-025-08794-6Enhancing seasonal predictability of the East Asian summer monsoon via optimized multi-model ensemblesOkYeon Kim0Woo-Seop Lee1Climate Services and Research Department, APEC Climate CenterClimate Services and Research Department, APEC Climate CenterAbstract The East Asian summer monsoon (EASM) exhibits complex and variable behavior that challenges the reliability of seasonal forecasts. In this study, we develop an optimized multi-model ensemble (MME) framework to enhance both the skill and confidence of EASM precipitation predictions. Unlike conventional MMEs that include all available models without performance filtering, the optimized MMEs are constructed by selecting only those models that demonstrate both high temporal correlation with observed principal components and a sufficiently large signal-to-total variance ratio. These criteria are quantified using the ratio of predictability components (RPC), which jointly captures real-world and model-based predictability. Results show that the optimized MMEs significantly outperform conventional MMEs in forecasting EASM rainfall: prediction skill improves by up to 13.4% and signal variance increases by up to 22.6%, particularly over East Asia. These improvements indicate not only higher forecast accuracy but also greater confidence in seasonal predictions. Our findings demonstrate that applying an RPC-based model selection method provides a robust strategy for improving seasonal climate forecasts in monsoon-affected regions.https://doi.org/10.1038/s41598-025-08794-6 |
| spellingShingle | OkYeon Kim Woo-Seop Lee Enhancing seasonal predictability of the East Asian summer monsoon via optimized multi-model ensembles Scientific Reports |
| title | Enhancing seasonal predictability of the East Asian summer monsoon via optimized multi-model ensembles |
| title_full | Enhancing seasonal predictability of the East Asian summer monsoon via optimized multi-model ensembles |
| title_fullStr | Enhancing seasonal predictability of the East Asian summer monsoon via optimized multi-model ensembles |
| title_full_unstemmed | Enhancing seasonal predictability of the East Asian summer monsoon via optimized multi-model ensembles |
| title_short | Enhancing seasonal predictability of the East Asian summer monsoon via optimized multi-model ensembles |
| title_sort | enhancing seasonal predictability of the east asian summer monsoon via optimized multi model ensembles |
| url | https://doi.org/10.1038/s41598-025-08794-6 |
| work_keys_str_mv | AT okyeonkim enhancingseasonalpredictabilityoftheeastasiansummermonsoonviaoptimizedmultimodelensembles AT wooseoplee enhancingseasonalpredictabilityoftheeastasiansummermonsoonviaoptimizedmultimodelensembles |