Research on short-term ozone forecasting model based on WRF and random forest——A case study of Qingdao
This study takes Qingdao as an example,based on the WRF model forecast and the random forest method,the forecast and the real data of 9 stations in September 2022 are used to revise the meteorological element forecast,and the short-term forecast model of O3 concentration is established by substituting the revised data of meteorological elements and adding the static data to realize the forecast with the time resolution of 1 hour for 7 days at each station,and the effect of the revision of the meteorological elements and the O3 prediction is evaluated and analyzed.The results show that the meteorological elements 2 m air temperature,surface pressure,2 m relative humidity,and 10 m wind speed are all revised to different degrees,especially the surface pressure and 10 m wind speed are revised with obvious effects;the O3 concentration prediction model has a good prediction effect,the RMSE is reduced by 22.1%compared with the WRF prediction,and the station prediction errors are improved and most of the effects are obvious.
Ozone(O3)random forestrevision of forecastsQingdao
NETL
NSTL
万方数据
