Kai Yang, Jinghua Chen, Tianliang Zhao, Chunsong Lu, Xiangde Xu, Yuehan Luo, Qingjian Yang, Chenghao Tan, Weikang Fu, Ziyue Wang
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引用次数: 0
Abstract
Inaccurate characterization of complex topography leads to the wet bias in climate models, particularly affecting terrain effects in regions like the Tibetan Plateau (TP). This study utilizes the Weather Research and Forecasting (WRF) model with multiple terrain datasets and introduces the terrain complexity index (TCI) to quantify the degree of terrain changes, aiming to evaluate how terrain complexity affects the cloud and precipitation processes over the TP. The results indicate that fine terrain complexity primarily causes earlier cloud formation and precipitation, resulting in more heavy precipitation on the southern slope of the TP (SSTP) and more light precipitation on the TP platform. The structure of moisture transport and microphysical processes further reveals that this promotes the formation of more medium and high clouds, increasing the proportion of solid precipitation over the SSTP. Over the TP platform, the restriction of medium and high cloud development with enhancing the proportion of low clouds for more liquid precipitation. These findings deepen the understanding of the TP’s complex terrain effect on cloud and precipitation changes in the Asian water cycle.
期刊介绍:
npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols.
The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.