Evaluation of the regional climate model for the forest area of Yunnan in China - Deng, Xiaofan; Zhang, Zhe; Zhao, Fan; Zhu, Zheng; Wang, Qiuhua (Frontiers in Forests and Global Change, 2023)
Climate change is becoming increasingly severe to the point that climate events have become one of the main factors causing forest fire. Regional climate models (RCMs), which are used to forecast climate, are a vital tool in the research on how to combat forest fires. As the main forest fire area in China, the forest area of Yunnan has frequent forest fires that generate significant losses, so it is a key area for forest fire prevention in China. Therefore, this study uses meteorological observational data from 25 meteorological stations in the forest area of Yunnan over the period 2004–2018 and compares and evaluates the regional climate forecast model (RegCM) and weather research and forecasting (WRF) model in multiple dimensions. Next, the optimal RCM is determined for the forest area of Yunnan. The results show that the deviations of RegCM predictions from the spatial mean of the real temperature are less than 3 ℃, whereas the deviations of the WRF model are all greater than 3 ℃. In addition, the RegCM correlation coefficient exceeds 0.8, whereas the WRF correlation coefficient exceeds 0.75. In terms of precipitation, the deviation of RegCM predictions for the whole territory is less than 2 mm, whereas the overall deviation of WRF predictions is large; the correlation coefficient for RegCM and WRF are both less than 0.5, but the RegCM correlation coefficient is greater than that of the WRF model. We thus conclude that the RegCM is more suitable for predicting the climate of the forest area of Yunnan. This study also provides references for related climate forecasting and for forest fire dynamics research in general.