Seasonal Forecast Method Research Of Accumulated Cyclone Energy For Tropical Cyclone Landfalling Over China Mainland From 1979 To 2019

Accumulated cyclone energy(ACE)is an indicator which characterizes the overall intensity of the tropical cyclones(TC)activity in a specific period of time.Moreover,it is often used to characterize the energy characteristics of TC in seasonal forecasting.At present,in the research of TC seasonal forecasting,domestic and foreign meteorological agencies mainly conduct operational forecast based on basinwide ACE.The natural disaster caused by TC are often closely related to their activities on land after landfall.China is one of the countries which most severely affected by TC in the world,so it is necessary to forecast the overland ACE in China mainland.Based on CMA-STI best track dataset,calculating the temporal and spatial distribution characteristics of overland ACE in China mainland,which is conducive to have a better understanding of the activity characteristics of TC in China mainland.It was found that the landfall frequency and mean duration of TC has significant influence on overland ACE.On the other hand,based on the reanalysis data,the main climate modes which affecting the change of overland ACE are found through the atmospheric and sea-air environmental conditions.Statistically,it is found that the El Ni(?)o-Southern Oscillation(ENSO)and Pacific-North American Pattern(PNA)are significantly correlated with overland ACE.The correlation between ENSO and PNA with overland ACE is analyzed from the two dimensions of time and space,and physical mechanism is analyzed based on large-scale environmental conditions.Based on ENSO and PNA,the multiple linear equation model of overland ACE in China mainland was constructed.The prediction results of overland ACE during the past 40 years were tested by using the CMA-STI best track dataset as a control.The results shows that the consistency of overland ACE trend prediction results based on PNA index,Ni(?)o-1+2 index,Ni(?)o-3 index,Ni(?)o-3.4 index and Ni(?)o-4 index can reaches 83%.In conclusion,ENSO and PNA can better predict the overall TC intensity in China mainland during TC season.