Review of big-data and AI application in typhoon-related disaster risk early warning in Typhoon Committee region

Abstract

ESCAP/WMO Typhoon Committee Members are directly or indirectly affected by typhoons every year. Members have accumulated rich experiences dealing with typhoons' negative impact and developed the technologies and measures on typhoon-related disaster risk forecasting and early warning in various ways to reduce the damage caused by typhoon. However, it is still facing many difficulties and challenges to accurately forecast the occurrence of typhoons and warning the potential impacts in an early stage due to the continuously changing weather conditions. With the development of information technology (IT) and computing science, and increasing accumulated hydro-meteorological data in recent decades, scientists, researchers and operationers keep trying to improve forecasting models based on the application of big data and artificial intelligent (AI) technology to promote the capacity of typhoon-related disaster risk forecasting and early warning. This paper reviewed the current status of application of big data and AI technology in the aspect of typhoon-related disaster risk forecasting and early warning, and discussed the challenges and limitations that must be addressed to effectively harness the power of big data and AI technology application in typhoon-related disaster risk reduction in the future.

Keywords

• Typhoon-related disaster risk
• Forecasting and early warning
• Big data and artificial intelligence