The linkage between CMIP5 climate models’ abilities to simulate precipitation and vector winds

Abstract

Precipitation is one of the major challenges in climate modeling. Among various factors, the large-scale atmospheric circulation plays an important role in modulating regional precipitation through dynamic processes that has been widely discussed in previous studies. However, few efforts have been made to investigate the relationship of model abilities to simulate precipitation and vector winds. Such an investigation may help to understand the source of uncertainty of precipitation simulation. Here, we examined the relationship between model performances in simulating precipitation with that in simulating vector winds by using the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Our results suggest that the model biases/uncertainties in simulating climatological mean precipitation often accompanied by the biases/uncertainties in vector wind fields. Model ability to simulate precipitation is closely related to the ability to simulate vector winds, especially over monsoon regions and the regions with warm and moist advection or high terrains, such as the South Asian and East Asian summer monsoon region, the Alaskan region, the Rocky Mountain, etc. Over these regions, the models with higher horizontal resolution tends to generate improved simulations in both the vector winds and precipitation relative to the models with coarse horizontal resolution. Besides, the model’s ability to simulate vector winds, compared to simulate the zonal wind, meridional wind, and skin temperature, is more closely related to the ability to simulate precipitation. This indicates that it is more meaningful to evaluate the vector winds than the zonal or meridional wind from the perspective of improving regional precipitation simulation.