基于机器学习方法的气溶胶对西藏高原地区雨季降水的影响
Impact of aerosol on rainy season precipitation in Xizang Plateau based on machine learning method
达瓦次仁 1落追 1洪一航 2次仁卓嘎1
作者信息
- 1. 拉孜县气象局,西藏日喀则 858100
- 2. 南京信息工程大学,江苏南京 210044
- 折叠
摘要
利用2001-2021 年年降水量资料,2021 年雨季6-9 月和非雨季露点温度、降水量等资料,PM2.5、硫酸盐、硝酸盐等大气污染物资料,基于机器学习方法对西藏高海拔地区拉孜降水量进行建模,并量化了影响拉孜地区降水量的气象因素和气溶胶粒子.结果表明:露点温度是影响拉孜地区降水量的关键变量,其对雨季和非雨季降水量的贡献分别为 74%和 66%.硝酸盐是气溶胶组分中对降水量影响最大的变量,其在雨季和非雨季占气溶胶总贡献的61%和71%,表明硝酸盐气溶胶对降水有重要作用.
Abstract
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.
关键词
高海拔地区/降水成因/机器学习Key words
High altitude region/Precipitation mechanism/Machine learning algorithm引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据