Typhoons, with their severe winds, rain, storm surges, and secondary disasters, have long been a key focus for local governments, meteorological departments, and research institutions, with all parties applying maximum effort in exploring more efficient ways to ensure public safety.
By every mid-May, the research team led by Prof. Kelvin Chan from the School of Atmospheric Sciences at Sun Yat-sen University (SYSU) provides meteorological services to China and neighboring areas, forecasting the number of typhoons for different regions in each year. Recently, the team developed a statistical seasonal forecasting model (SYSU Model) to forecast the number of typhoon landfalls on Taiwan Island. The related article was published recently in Atmospheric and Oceanic Science Letters .
"This concise, open-source, and effective model utilizes four pre-typhoon-season environmental predictors to forecast the number of typhoons that will land on Taiwan Island by every mid-May. Benefiting from the comprehensive predictor selection method, the hit rate of the model reaches 98% for the period 1979–2022," says Ms. Ziqing Chen, first author of the article.
Research suggests that large-scale climate phenomena, such as the Antarctic Oscillation, along with the variations of the western Pacific subtropical high, play an important role in steering typhoons towards Taiwan Island. In addition, the Asian summer monsoon and the oceanic tunnel connecting different sea basins are potential factors that affect the formation and tracks of typhoons.
"Being able to forecast typhoon landfall months ahead is of benefit to the relevant regions in making adequate preparations for disaster prevention and mitigation. Furthermore, the open-source model offers an additional reference for operational forecasting, facilitating collaboration between scientific research and meteorological operations. With the continuous improvement and promotion of the SYSU model by the research team, the expectation is that it will serve more regions in the future", says Prof. Kelvin Chan, corresponding author of the study.
