Impact of moisture divergence on systematic errors in precipitation around the Tibetan Plateau in a general circulation model

Yi Zhang,Jian Li

doi:10.1007/s00382-016-3005-y

Abstract

Current state-of-the-art atmospheric general circulation models tend to strongly overestimate the amount of precipitation around steep mountains, which constitutes a stubborn systematic error that causes the climate drift and hinders the model performance. In this study, two contrasting model tests are performed to investigate the sensitivity of precipitation around steep slopes. The first model solves a true moisture advection equation, whereas the second solves an artificial advection equation with an additional moisture divergence term. It is shown that the orographic precipitation can be largely impacted by this term. Excessive (insufficient) precipitation amounts at the high (low) parts of the steep slopes decrease (increase) when the moisture divergence term is added. The precipitation changes between the two models are primarily attributed to large-scale precipitation, which is directly associated with water vapor saturation and condensation. Numerical weather prediction experiments using these two models suggest that precipitation differences between the models emerge shortly after the model startup. The implications of the results are also discussed.

Highlights

Despite the rapid development of atmospheric general circulation models (AGCMs), systematic model errors in the climatological mean state remain a major challenge to the scientific community (e.g., Huang et al 2007; Xie et al 2012; Magnusson et al 2013a; Zhang and Li 2013)
At the eastern steep edge of the plateau, CAM5 produces excessive precipitation amounts above the 2000-m contour line and insufficient amounts below it. This reflects a key problem that the model tends to overestimate the orographic precipitation amounts at the high parts of steep slopes, whereas it underestimates the amount of precipitation at the low parts
By adding an additional moisture divergence term in the advection equation of an AGCM, the results demonstrated the large sensitivity of orographic precipitation to this additional term, which fundamentally influences the moisture saturation and condensation by redistributing the water vapor

Summary

Introduction

Despite the rapid development of atmospheric general circulation models (AGCMs), systematic model errors in the climatological mean state remain a major challenge to the scientific community (e.g., Huang et al 2007; Xie et al 2012; Magnusson et al 2013a; Zhang and Li 2013). The ensemble of Coupled Model Intercomparison Project Phase 3 (CMIP3) models overestimates the amount of precipitation over the Tibetan Plateau by up to 100 % (Xu et al 2010) This is true for other regions with high mountains, e.g., the Andes mountains, where both regional and global models tend to produce excessive precipitation (Alves and Marengo 2010; Gulizia and Camilloni 2015). Precipitation typically reflects processes associated with water vapor condensation, latent heat release and cloud occurrence, which fundamentally influence the water balance and radiative forcing that are the essential driving forces of atmospheric circulation. They in turn may affect physical processes that are responsible for precipitation. To mitigate systematic model errors in orographic precipitation, the model must be fine-tuned (e.g., Mauritsen et al 2012) such that it can adequately simulate precipitation amounts around mountainous regions

Methods

Results

Conclusion