Ensemble numerical weather prediction model to improve the efficiency of Henan parameterization scheme

Abstract

China has highly emphasized the research and operational application of numerical weather prediction. This paper determines the objective function parameters, such as CAPE and SRH, to apply an ensemble numerical prediction model in weather forecasting. Preprocessing and evaluating rainfall data is necessary to construct the WRF-ARW numerical weather prediction model. The WRF-ARW model is applied to simulate the weather forecasts in Henan Province, and the difficulties and challenges faced in the efficient implementation of the parameterized scheme are outlined. The WRFARW model’s prediction errors for the maximum rainfall and total rainfall in Henan Province range from 1.78%-13.51% and 0.16%-3.78%, respectively, which are significantly less than 15%, and the model is more predictive than the others. The raw data test set’s credibility ranges from 0.957 to 0.997, which is close to 1, indicating that the raw data collected in this paper are highly credible. The WRF-ARW model’s qualification rates for forecasting maximum rainfall and total rainfall are 86.7% and 93.3%, respectively, and its overall accuracy is grade B and grade A, respectively. The pass rates for the peak occurrence time of maximum rainfall and total rainfall were 93.3% and 86.7%, respectively, and the overall prediction accuracy was Grade A and Grade B, respectively. The WRF-ARW model is effective in weather forecasting throughout Henan Province. In summary, the WRF-ARW model is very effective in improving the efficiency of ensemble numerical weather prediction and parameterization schemes in Henan Province.

Keywords

• wrf-arw model
• cape
• srh
• ensemble numerical
• weather prediction
• parameterized scheme
• 97p10