Superior Representation of Summer Precipitation Frequency and Intensity over the Tibetan Plateau by Physically-Refined Regional Climate Model

Accurate simulation of precipitation frequency and intensity over the Tibetan Plateau (TP) is crucial for elucidating regional precipitation patterns and mitigating water-related hazards under climate change, yet remains a long-standing challenge. This study evaluates the physically-refined Tibetan Plateau Climate System Model (TPCSM) in simulating precipitation amount and frequency across different intensity categories. High-resolution simulations for summer 2019 were compared against daily precipitation observations from 112 rain-gauge stations, ERA5 reanalysis, standard WRF simulations, and three satellite products (GSMaP, IMERG, and MSWEP). Quantitative evaluations show that ERA5 exhibits a substantial overestimation of total precipitation, with a bias of 3.51 mm/d and a frequency error of 31.32 d; whereas kilometer-scale WRF simulations mitigate these biases to 1.95 mm/d and 10.2 d, respectively. The refined TPCSM further enhances performance, yielding the lowest mean bias of 0.53 mm/d and a frequency error of only ∼3 d. Specifically, the refinements of physical schemes in TPCSM remarkably improve the representation of mid-heavy precipitation (>10 mm/d), demonstrating superior fidelity in capturing the precipitation frequency-intensity relationship and achieving the highest Equitable Threat Score across all intensity categories. Sensitivity experiments identify the sub-grid statistical cloud scheme as the primary contributor to these improvements; its implementation leads to a substantial 119.66 mm reduction in cumulative moisture flux convergence, corresponding to a 64.4% decrease in mid-heavy precipitation frequency. Additionally, incorporating soil organic matter and turbulent orographic form drag helps rectify the wet bias by modulating evapotranspiration and limiting moisture transport. Notably, TPCSM also corrects the prevalent overestimation of light precipitation frequency in satellite retrievals over the TP, demonstrating predictive skill comparable to or exceeding that of mainstream satellite products. These findings underscore the potential of TPCSM as an effective tool for studying precipitation variability under future climate change, thereby supporting risk assessment and water-related hazards mitigation in data-scarce regions of the TP.