Impact of aerosol on rainy season precipitation in Xizang Plateau based on machine learning method
Using the precipitation data from 2001 to 2021 and the data of atmospheric pollutants such as PM2.5,sul-fate and nitrate,we chose Lazi as the study area and use the machine learning(ML)method to decipher the com-plex relationship between precipitation and its influencing factors.After that,the contribution of each input variable to the precipitation in was is quantified by this ML method.The results indicate that the dew point temperature is the most crucial elements affecting the precipitation in Lazi,contributing 74%to precipitation in rainy season and 66%to precipitation in non-rainy season.Among aerosol components,nitrate shows the greatest influence on pre-cipitation,accounting for 61%and 71%to the precipitation in rainy and non-rainy seasons,respectively.This re-sult means that nitrate aerosols play an important role in precipitation.
High altitude regionPrecipitation mechanismMachine learning algorithm
国家科技期刊平台
NSTL
万方数据
