Evaluating the climate projections for China through the lens of the simulations of planetary boundary layer height

Abstract

The planetary boundary layer height (PBLH) plays an essential role in affecting many meteorological parameters in climate change, and it is closely associated with the concentration of near surface air pollutants as well. Uncertainty of simulating PBLH is large partly due to the complexity in the modulation of surface energy, and the behaviors of the climate models in reproducing PBLH have not been fully evaluated, which also limits the understanding of future changes in PBLH. Here by utilizing a multi-model ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6), we first thoroughly evaluate the capability of CMIP6 models in reproducing the spatial distribution of PBLH over China during the period of 1995–2014, revealing large discrepancies among the CMIP6 models. Meanwhile, inaccuracy of simulated meteorological parameters can lead to large deviations of PBLH in models, among which sensible heat flux (SHFLX) and near surface relative humidity (RH) show stronger modulation effects. To enhance the confidence of future projections, we apply a method by selecting the five models with the smallest biases and a high signal-to-noise ratio, and the results indicate that changes in PBLH under shared socioeconomic pathways exhibit a dipole pattern in both summer and winter. Specifically, PBLH is projected to decrease over North China and increase over Central China and South China in summer, while in winter PBLH tends to increase stronger in southern China and weaker in the northern flank. To reveal the mechanism governing the PBLH, we find that changes of PBLH is closely associated with surface energy. SHFLX and near surface RH are the dominant factors shaping the changes in the spatial heterogeneity of PBLH in the future. This study has important implications for the improvement of surface energy and PBLH in climate models in order to effectively predict the future changes of air pollutants.