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arXiv · 2609.03364

Added value of dynamical downscaling in sub-seasonal tropical cyclone forecast

Abstract

Improving the sub-seasonal forecast of tropical cyclones (TCs) remains a significant challenge for climate models. This study evaluated the characteristics of tropical cyclones (TCs) in sub-seasonal forecasts using the Global Seasonal Forecast System 6 (GloSea6), an operational seasonal-to-sub-seasonal forecasting model operated by the Korea Meteorological Administration (KMA) during June-September (JJAS) from 1993 to 2016 over the western North Pacific (WNP). GloSea6 was found to underestimate TC frequency, tracks, particularly in mid-latitudes, lifetime, and intensity across all months, with the most significant errors occurring in August. To address these deficiencies, we examined whether applying dynamical downscaling to GloSea6 during August 2016, a period characterized by the lowest TC forecast skill in GloSea6, could improve sub-seasonal TC forecasts. The application of dynamical downscaling demonstrated added value by directly improving the simulation of TCs in terms of frequency, structure, intensity, and lifetime, although slight overestimations were observed. Furthermore, improved reproductions of the Indian monsoon and circumglobal teleconnection (CGT), both of which strongly influence the western North Pacific subtropical high (WNPSH), contributed to more accurate forecasts of WNPSH variability and, consequently, better predictions of TC activity in the mid-latitudes and East Asia. Therefore, dynamical downscaling can significantly advance sub-seasonal TC forecasts by not only directly improving TC characteristics but also indirectly enhancing the environmental fields (e.g., WNPSH, Indian monsoon, and CGT) that are critical to TC activity.

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Taehyung Kim, Eunji Kim, Haerin Park, Dong-Hyun Cha, Johan Lee. 2026-09-03. Added value of dynamical downscaling in sub-seasonal tropical cyclone forecast. https://doi.org/10.1016/j.atmosres.2026.108988

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