Ma J.-H.,Shanghai Pudong Meteorological Service |
Zhou G.-Q.,Shanghai Pudong Meteorological Service |
Zhou G.-Q.,Shanghai Typhoon Institute |
Zhou J.,Shanghai Pudong Meteorological Service |
And 4 more authors.
Zhongguo Huanjing Kexue/China Environmental Science | Year: 2014
A fully coupled atmospheric chemistry model, weather research and forecasting (WRF) with dust component (WRF-Dust) was applied to investigate a dust event occurring over Shanghai and surrounding regions during May 1-4, 2011. Through the comparisons with observations, the model was able to capture main features of the event fairlywell. Overall, the simulations showed good agreement with the observations for the starting time (~11:00 on May 1), the ending time (~02:00 on May 2), and dust peak values of the event around Shanghai. However, some simulation biases were found for several meteorological factors and dust concentrations over several sub-regions during the event. In addition, the model did not reproduce dust backflow over the coastal regions of the Yangtze River Delta. Finally, the possible reasons causing the simulation biases were discussed and methods to improve simulations of dust events were proposed.
Zhou G.-Q.,Yangtze River Delta Center for Prediction and Warning of Environmental Meteorology |
Zhou G.-Q.,Shanghai Key Laboratory of Meteorology and Health |
Geng F.-H.,Yangtze River Delta Center for Prediction and Warning of Environmental Meteorology |
Geng F.-H.,Shanghai Key Laboratory of Meteorology and Health |
And 10 more authors.
Zhongguo Huanjing Kexue/China Environmental Science | Year: 2015
A numerical chemical weather forecasting system was established and operationally implemented based on the WRF-Chem Model, an online coupled regional chemical transport model. Performance of the modeling system on daily maximum 1-hour and 8-hour ozone (1 h and 8 h O3) concentrations was evaluated between May 1st and September 30th, 2013. The results showed that the numerical forecasting has generally good performance. There is no substantial systematic bias in 1h and 8h O3 concentrations and correspondent IAQI in forecasts of 24 h, 48 h, and 72 h. The correlation coefficients (R) are ~0.8, and the mean and median biases are around 1×10-9~2×10-9. The forecasted O3 attainment vs. pollution days as well as primary pollutants are also in good agreement with observations. The performance of 48 h forecast is slightly better than that of 24 h and 72 h forecast, and these of the later two are generally close to each other. Meanwhile, further improvement is still needed. For example, model shows substantial biases in O3 concentrations or IAQI forecasts in some cases, and the accuracy of O3 IAQI level forecast is substantially lower than that of concentration and IAQI value forecast. In general, the numerical forecasting system shows relatively good performance in O3 forecasts during May to September, 2013, and it has the capability to support the air quality forecast over Shanghai. ©, 2015, Chinese Society for Environmental Sciences. All right reserved.