不同水平分辨率区域气候模式对青藏高原气候特征模拟

he Tibetan Plateau has a unique climate, complex topography, and few meteorological observation stations, which makes it difficult to observe and simulate its regional climate and water cycle processes. Using the regional climate models RegCM and WRF, the spatial and temporal distribution of the climate in this region from 1989 to 2008 was systematically analyzed, and the simulation capability of the RegCM and WRF models was investigated at 10, 25, and 50 km horizontal resolutions in the Tibetan Plateau. Results show that the trend of annual average temperature simulated by both models at 10 km horizontal resolution is 1.60-2.122 lower than the multiyear average temperature simulation at 25 and 50 km horizontal resolution. With increasing horizontal resolution, the simulation biases of annual and seasonal temperatures simulated by the WRF model decrease, and the cold bias of temperature in the central and western parts of the Tibetan Plateau improves. The simulated temperature in the RegCM model at a 10 km horizontal resolution has the lowest error, and it is significantly better for simulating the spatial distribution of temperature in the Tibetan Plateau. The correlation between the simulated temperature of both models in different seasons and the observation data has been improved. In the precipitation simulation, the WRF model at a horizontal resolution of 25 km has the best correlation with the observed data but has the largest error. With the increase of horizontal resolution, the overestimation of precipitation in the southeastern and southern Tibetan Plateau by the WRF model has been significantly improved, and the annual precipitation simulated by the RegCM model gradually approaches the measured values (the overestimation decreases from about 2.73 times to 1.77 times). However, the overall overestimation of precipitation by both models still exists. In the simulation of the five major river sources on the Tibetan Plateau, with increasing horizontal spatial resolution, the WRF model reduces the biases of the air temperature in the source region of the Mekong river and Salween River, whereas the RegCM model reduces the biases of the air temperature in the source region of the Brahmaputra River and Mekong river. The largest reduction in precipitation bias was achieved in the Brahmaputra River source region at 10 km horizontal resolution by the WRF and RegCM models. This study can lay the foundation for understanding the impact of climate change on the water cycle process in the Tibetan Plateau.