image: (a) Precipitation time series from GPM satellite product (GPM) and sensitivity experiments; (b)–(d) probability density distribution functions of daily total precipitation for GPM (green), CTRL experiment (CTRL; blue), and other sensitivity experiments (orange). In the legends of panels b–d, the values in the first column represent the overall mean daily total precipitation, and the values in the second column represent the root mean square error (RMSE) of daily total precipitation between the sensitivity experiments and GPM.
Credit: ©Science China Press
This study is led by Dr. Junjun Li from Nanjing University of Information Science and Technology and Nanyang Technological University; Dr. Chunsong Lu and Dr. Jinghua Chen from Nanjing University of Information Science and Technology; Dr. Xu Zhou from the Institute of Tibetan Plateau Research, Chinese Academy of Sciences; Dr. Kun Yang from Tsinghua University; Dr. Xiaoqi Xu from the Nanjing Joint Institute for Atmospheric Sciences; and Dr. Xianghua Wu and Dr. Lei Zhu from Nanjing University of Information Science and Technology.
This study utilized the Weather Research and Forecasting WRF model to simulate precipitation over the Tibetan Plateau and adjacent areas during June and July 2019. The aim was to evaluate the combined impact of an optimized Grell-Freitas cumulus scheme with improved entrainment process and a Turbulent Orographic Form Drag scheme on cloud and precipitation representation. The control experiment tended to overestimate precipitation across the TP and surrounding regions. The introduction of the improved Grell-Freitas cumulus scheme significantly reduced this overestimation. The simulated precipitation better matched observations in terms of spatial patterns, temporal evolution, and statistical distribution. The experiment applying the Turbulent Orographic Form Drag scheme alone had a limited effect on the domain-averaged precipitation amount but improved the spatial distribution of simulated precipitation over the TP. When both the improved Grell-Freitas cumulus scheme and the Turbulent Orographic Form Drag scheme were combined, the simulation showed the greatest reduction in precipitation bias. This combined approach aligned more closely with observations in both mean precipitation and temporal variation, achieving the highest precipitation skill scores among all experiments.
Overall, this study demonstrates that the combined use of optimized convective entrainment processes and turbulent orographic drag parameterization substantially enhances the WRF model’s ability to simulate precipitation over the Tibetan Plateau, providing valuable insights for improving weather forecasting and climate research in mountainous regions.
See the article:
Li J, Lu C, Chen J, Zhou X, Yang K, Xu X, Wu X, Zhu L, He X, Wu S, Lin P. 2025. The combined effects of convective entrainment and orographic drag on precipitation over the Tibetan Plateau. Science China Earth Sciences, 68(8): 2615–2630, https://doi.org/10.1007/s11430-024-1619-5
Journal
Science China Earth Sciences