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Probabilistic medium-range forecasts of extreme heat events over East Asia based on a global ensemble forecasting system Sunlae Tak, Nakbin Choi, Joon...
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LATEST RESEARCH

Probabilistic medium-range forecasts of extreme heat events over East Asia based on a global ensemble forecasting system

 

Probabilistic medium-range forecasts of extreme heat events over East Asia based on a global ensemble forecasting system

 

Sunlae Tak, Nakbin Choi, Joonlee Lee, Myong-In Lee*
Department of Civil Urban Earth and Environmental Engineering, Ulsan National Institute of Science & Technology (UNIST), 50 UNIST-gil, Ulju-gun, Ulsan, 44919, South Korea 
Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, VA, 22030, United States

 

This study suggests a methodology for probabilistic forecasts of the extreme heat events in East Asia based on an operational global ensemble prediction used by the Korea Meteorological Administration (KMA). It focuses on the medium range of up to 11 days, providing probabilities of heatwave and tropical night occurrence each day. Forecast validation in the summer from 2016 to 2021 shows that the deterministic heatwave forecast provides 5 days of optimal forecast range, while the probabilistic forecast can extend the practically predictable range up to 10 days in the Korean Peninsula and 7 days in Japan, respectively. Comparing prediction skills for heatwave and tropical night, the skills for tropical night tend to be inferior, presumably due to complex mechanisms of the tropical night and large uncertainty in the numerical model, such as microphysics and radiation. In addition, the coarse resolution of the operational system does not seem to resolve temperature variability at night. As a case study, this study also examines the forecast of the onset and offset of the 2018 South Korean heatwave event. The temporal evolution of the heatwave matches well with the changes in the upper-level atmospheric circulation pattern, which can be used for useful forecast guidance. This probabilistic forecast based on the global ensemble forecasting system is expected to provide reliable prediction information for heatwaves in advance, reducing exposure to extreme events.