Linking the Pacific Meridional Mode to Decadal Heatwave Prediction in Taiwan and East Asia

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Authors: Chieh-Ting Tsai, Wan‐Ling Tseng, Yi‐Chi Wang, Yan-Lan Shen, Pao-Hsin Chu
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Abstract

Climate change is accelerating the frequency and intensity of heatwaves at an unprecedented rate, posing substantial threats to public health and socio-economic systems. To effectively mitigate future risks associated with extreme heat events, it is crucial to understand the decadal variability of heatwaves and to develop robust medium- to long-term adaptation strategies. However, owing to the complexity of internal climate variability, producing reliable, high-resolution decadal predictions of heatwaves over Taiwan and East Asia remains a major challenge.This study focuses on the Pacific Meridional Mode (PMM), a key mode of climate variability that influences heatwave activity in East Asia through its modulation of large-scale atmospheric circulation over the North Pacific. By examining the spatial characteristics of heatwaves in Taiwan and their linkage to PMM variability, we develop statistical models that relate PMM to decadal variations in heatwave frequency across East Asia. To further enhance predictive skill and reduce model uncertainty, we also apply a Bayesian ensemble approach, which optimally combines information from multiple models based on their historical performance.Our results demonstrate that incorporating PMM significantly improves the predictive skill of decadal heatwave forecasts, while the Bayesian ensemble method provides additional gains in forecast accuracy and robustness. These findings highlight the critical role of large-scale climate variability in governing extreme heat events and underscore the value of Bayesian ensemble techniques for advancing decadal climate prediction and supporting proactive climate risk management in Taiwan and East Asia.

Fields of Study & Subjects

Climate variability and models Meteorological Phenomena and Simulations Hydrology and Drought Analysis

Publication details

Journal / source
EGU General Assembly Conference Abstracts
Publication date
14 March 2026
Language
EN