Acta Geographica Sinica ›› 2019, Vol. 74 ›› Issue (11): 2329-2341.doi: 10.11821/dlxb201911010

• Climate Change and Ecological Environment • Previous Articles     Next Articles

Numerical simulation and spatial distribution of summer precipitation in the Qinling Mountains

XIN Rui,DUAN Keqin()   

  1. School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
  • Received:2018-12-11 Revised:2019-07-18 Online:2019-11-25 Published:2019-11-01
  • Contact: DUAN Keqin E-mail:kqduan@snnu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(41771030);The Fundamental Research Funds For the Central Universities(2018CSLZ002)

Abstract:

The Qinling Mountains serve as a dividing line for China's climate. The dearth of precipitation data in high-altitude areas limits the study of climate and water resource changes in this region. To determine the spatial distribution of precipitation, the weather research forecasting (WRF) model was used to simulate summer precipitation in the Qinling Mountains and surrounding areas in 2017 by employing three convective parameterization schemes (KF, BMJ and GF). Both the simulation results and satellite data reveal that precipitation is consistent with the terrain's topography, and there is a spatial pattern of strip distribution from south to north accompanied by a high precipitation zone in the Qinling Mountains. The mountains have an evident blocking effect on the northward transport of water vapour, resulting in precipitation on the southern slope of the Qinling Mountains being significantly greater than that on the northern slope. However, the analogue value is larger than the satellite precipitation data. The primary reason that more precipitation is observed in the KF scheme simulation is that the strong convective instability leads to an overestimation of convective precipitation. The GF scheme simulates grid-scale precipitation, which result in more large-scale precipitation due to atmospheric wetness. The simulated values of the BMJ scheme are closest to the observed values. Increasing the resolution to 2 km can significantly improve the simulation level of the model in the Qinling Mountains, and there is great potential for improving precipitation estimation at the highest elevations of the mountains by using a suitable cumulus parameterization scheme.

Key words: WRF model, Qinling Mountains, precipitation, cumulus parameterization scheme, horizontal resolution