Convection-permitting modelling improves simulated precipitation over the central and eastern Tibetan Plateau

The Tibetan Plateau (TP) plays an essential role in influencing the global climate, and precipitation is one of its most important water-cycle components. However, accurately simulating precipitation over the TP is a long-standing challenge. In this study, a convection-permitting model (CPM; with 4 km grid spacing) that covers the entire TP was conducted and compared to two mesoscale models (MSMs; with model horizontal resolutions of 13 and 35 km) over the course of a summer. The results showed that the two MSMs have notable wet biases over the TP and can overestimate the summer precipitation by more than 4.0 mm center dot day(-1)in some parts of the Three Rivers Source region. Moreover, both MSMs have more frequent light rainfall; increasing horizontal resolution of the MSMs alone does not reduce the excessive precipitation. Further investigation reveals that the MSMs have a spurious early-afternoon rainfall peak, which can be linked to a strong dependence on convective available potential energy (CAPE) that dominates the wet biases. Herein, we highlight that the sensitivity of CAPE to surface temperatures may cause the MSMs to have a spurious hydrological response to surface warming. Users of climate projections should be aware of this potential model uncertainty when investigating future hydrological changes over the TP. In comparison, the CPM removes the spurious afternoon rainfall and thus significantly reduces the wet bias simulated by the MSMs. In addition, the CPM also better depicts the precipitation frequency and intensity, and is therefore a promising tool for dynamic downscaling over the TP.

Automated summary

This study compared the performance of a convection-permitting model with two mesoscale models in simulating precipitation over the Tibetan Plateau. The mesoscale models exhibited notable wet biases and a spurious early-afternoon rainfall peak, while the convection-permitting model significantly reduced the wet bias and spurious rainfall.