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Joonlee Lee

As seen in: Nature
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Articles

Atlantic SST as a key source of subseasonal predictability in the April 2020 Siberian heatwave

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By Joonlee Lee, Myong-In Lee, Jihae Kim, Nakbin Choi, JOHAN LEE, Kyung-On Boo, Yu-Kyung Hyun, Geonhee Bak, Beomcheol Shin
| Nature Verified
Abstract The April 2020 Siberian heatwave was among the most extreme early-spring warming events on record, with widespread environmental and societal impacts, yet it was missed by most subseasonal-to-seasonal (S2S) forecast systems. Understanding the sources of predictability and their limitations remains a key challenge in extended-range forecasting of land heat extremes.
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Unveiling teleconnection drivers for heatwave prediction in South Korea using explainable artificial intelligence - npj Climate and Atmospheric Science

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By Yeonsu Lee, Dongjin Cho, Jungho Im, Cheolhee Yoo, Joonlee Lee
| Nature Verified
Abstract Increasing heatwave intensity and mortality demand timely and accurate heatwave prediction. The present study focused on teleconnection, the influence of distant land and ocean variability on local weather events, to drive long-term heatwave predictions. The complexity of teleconnection poses challenges for physical-based prediction models.
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