地 址：北京市朝阳区德胜门外祁家豁子华严里40号 竺南中心
Developing a Climate Prediction System over Southwest China Using the 8-km Weather Research and Forecasting (WRF) Model: System Design, Model Calibration, and Performance Evaluation[2022-09-24]
A high-resolution, short-term climate prediction system for summer (June-July-August) climate over Southwest China has been developed using the Weather Research and Forecasting (WRF) model nested with a global climate prediction system (PCCSM4). The system includes 12 ensemble members generated by PCCSM4 with different initial conditions, and the finest horizontal resolution of WRF is 8 km. This study evaluates the ability of the WRF model to predict summer climate over Southwest China, focusing on the system design, model tuning and evaluation of baseline model performance. Sensitivity simulations are firstly conducted to provide the optimal model configuration, and the model performance is evaluated against available observational data using reforecast simulations for 1981-2020. When compared to PCCSM4, the WRF model shows major improvements in predicting the spatial distribution of major variables such as 2-m temperature, 10-m wind speed and precipitation. WRF also shows better skill in predicting inter-annual temperature variability and extreme temperature events, with higher anomaly correlation coefficients. However, large model biases remain in seasonal precipitation anomaly predictions. Overall, this study highlights the potential advantages of using the high-resolution WRF model to predict summer climate conditions over Southwest China.
Fig. 1. Spatial distribution of summer mean biases of PCCSM4 (a-c) and WRF (d-f) model for: 2-m temperature (a, d, units: ℃), 10-m wind speed (b, e, units: m/s), (c) precipitation (c, f, units: %) relative to CN05.1.
Yu, Entao, Jiehua Ma, and Jianqi Sun. Developing a Climate Prediction System over Southwest China Using the 8-km Weather Research and Forecasting (WRF) Model: System Design, Model Calibration, and Performance Evaluation, Weather and Forecasting. 37, 9 (2022): 1703-1719.