A Diachronic Assessment of Advances in Seasonal Forecasting: Evolution of the APCC Multi‐Model Ensemble Prediction System Over the Last Two Decades

Abstract Since its establishment in 2005, the APEC Climate Center (APCC) has pioneered advancements in seasonal climate prediction through its Multi‐Model Ensemble (MME) system, integrating the world's most diverse range of dynamical climate models. Over the past two decades, APCC has incorporated long‐range forecasts from more than 60 model versions, contributed by 21 institutions across 11 countries. This study presents the first diachronic assessment of the APCC MME system evolution, focusing on operational model transitions and associated substantial 34% improvement in global forecast skill. Despite these significant advances, challenges persist, particularly in predicting precipitation over land areas in the northern extratropics and in overcoming the spring predictability barriers. Our findings underscore the crucial role of model innovation, increased diversity, and international collaboration in advancing seasonal prediction. As the first study of its kind, this work provides key insights into the evolution of climate modeling, providing a foundation for future forecasting improvements.

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Publication Details

Journal
Geophysical Research Letters
Published
2025-09-03
DOI
https://doi.org/10.1029/2025gl116416
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.11

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article

A Diachronic Assessment of Advances in Seasonal Forecasting: Evolution of the APCC Multi‐Model Ensemble Prediction System Over the Last Two Decades

Sera Jo, Normand Gagnon, Young‐Mi Min, D. B. Kiktev et al.
1 citations
Geophysical Research Letters
Climate variability and models
1.11
article

A Diachronic Assessment of Advances in Seasonal Forecasting: Evolution of the APCC Multi‐Model Ensemble Prediction System Over the Last Two Decades

Sera Jo, Normand Gagnon, Young‐Mi Min, D. B. Kiktev, M. A. Tolstykh, Peter McLean, Apiradee Lim, Mingyue Chen, V. A. Matyugin, Andrea Molod, Suryun Ham, Andrea Borrelli, Chang‐Mook Lim, Vladimir N. Kryjov, Ryan Muncaster, Johan Lee, Pang‐Yen Liu, Hyung‐Jin Kim, Da-Eun Jeong, Yi Xiao, Jinho Yoo, Hee‐Sook Ji
article en
1 citations

Abstract

Abstract Since its establishment in 2005, the APEC Climate Center (APCC) has pioneered advancements in seasonal climate prediction through its Multi‐Model Ensemble (MME) system, integrating the world's most diverse range of dynamical climate models. Over the past two decades, APCC has incorporated long‐range forecasts from more than 60 model versions, contributed by 21 institutions across 11 countries. This study presents the first diachronic assessment of the APCC MME system evolution, focusing on operational model transitions and associated substantial 34% improvement in global forecast skill. Despite these significant advances, challenges persist, particularly in predicting precipitation over land areas in the northern extratropics and in overcoming the spring predictability barriers. Our findings underscore the crucial role of model innovation, increased diversity, and international collaboration in advancing seasonal prediction. As the first study of its kind, this work provides key insights into the evolution of climate modeling, providing a foundation for future forecasting improvements.

Geophysical Research LettersVol. 52(17)
Bureau of Meteorology (AU), Met Office (GB), Hydrometeorological Research Centre of Russian Federation (RU), Goddard Space Flight Center (US), National Oceanic and Atmospheric Administration (US), Korea Meteorological Administration (KR), Environment and Climate Change Canada (CA), Rural Development Administration (KR), CMCC Foundation - Euro-Mediterranean Center on Climate Change (IT), Voeikov Main Geophysical Observatory (RU), APEC Climate Center (KR), National Institute of Meteorological Sciences (KR), NOAA Climate Prediction Center, Independent University of Moscow (RU)
National Aeronautics and Space Administration, Rural Development Administration, Korea Meteorological Administration, Environment and Climate Change Canada
Openalex Percentile: Top 20%
Climate variability and models
1.11
DOIOpen Access PDFOpenAlex
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