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
