Prediction of duration of high temperature heat wave in the Dongting Lake Basin
At present,heat waves(HWs)are gradually becoming the norm from extreme events.HWs have serious adverse effects on human health,natural ecological environment,and socio-economic systems.So,ac-curately predicting the duration of heatwaves is an urgent problem to be solved.The middle and lower reaches of the Yangtze River and the Huaihe River Basin are one of the three major frequent HWs areas in the world.Our study based on both the observed meteorological data from 1984 to 2020 in the Dongting Lake Basin,which located in the middle reaches of the Yangtze River,and four types of HWs influencing factors data(i.e.,global warming,large scale atmospheric circulation,human activity and land-atmosphere coupling),the signi-ficant factors affecting the duration of HWs in the Dongting Lake Basin were screened by full subset regres-sion,and then the duration model of HWs in the Dongting Lake Basin was established by full subset regres-sion and BP neural network algorithm.The results show that:1)The duration of HWs had a decreasing trend from 1960s to early 1970s,and remained stable from early 1970s to the mid-1990s,then shown a significant in-crease since the mid-1990s.2)The duration of HWs is positively correlated with air temperature,surface solar radiation,east extension ridge of South Asian High,vegetation growth,aerosol,ground hardening and urbaniz-ation,and negatively correlated with precipitation,relative humidity,west Pacific subtropical high west exten-sion ridge and ENSO.The west Pacific subtropical high ridge,ENSO change,aerosol,ground hardening and urbanization were identified as the significant factors of the duration of HWs with the full subset regression model.3)A prediction model for the duration of HWs is established based on the observed data of significant factors during the same period.BP neural network model has better performance than the whole subset model.Thus it could be used as the model for the duration of HWs in the Dongting Lake Basin from 1984 to 2020.
high temperature heat waveduration daysinfluence factorfull subset analysisBP neural net-work algorithm
万方数据
维普
