地理学报 ›› 2019, Vol. 74 ›› Issue (11): 2329-2341.doi: 10.11821/dlxb201911010

• 气候变化与生态环境 • 上一篇    下一篇

2017年夏季秦岭降水的数值模拟及其空间分布

辛蕊,段克勤()   

  1. 陕西师范大学地理科学与旅游学院,西安 710119
  • 收稿日期:2018-12-11 修回日期:2019-07-18 出版日期:2019-11-25 发布日期:2019-11-01
  • 通讯作者: 段克勤 E-mail:kqduan@snnu.edu.cn
  • 作者简介:辛蕊(1994-), 女, 河北保定人, 硕士生, 主要从事区域气候变化数值模拟研究。E-mail: syrus. xin@snnu.edu.cn
  • 基金资助:
    国家自然科学基金项目(41771030);中央高校基本科研业务费专项资金(2018CSLZ002)

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)

摘要:

秦岭是中国气候的分界线,其高海拔地区降水数据的缺乏,限制了对秦岭高山气候及水资源变化的研究。为认知秦岭地区降水的空间分布,利用WRF模式,采用GF、KF和BMJ 3种对流参数化方案,对秦岭及周边地区2017年夏季降水进行了模拟。结果显示,模拟和卫星数据都揭示降水与地形呈剖面一致性,从南到北呈条带状分布的空间格局,在秦岭出现一条降水高值带,秦岭对水汽向北输送有明显的阻滞作用,造成南坡降水量显著大于北坡。模拟值要比卫星降水数据偏大,其中KF方案模拟降水偏多的主要原因为强烈的对流不稳定性导致对流降水的过高估计,GF方案则由于大气偏湿激发网格尺度降水,造成大尺度降水的模拟偏多,而BMJ方案模拟值与观测值最为接近。把模式分辨率提高到2 km,可显著改善模式对秦岭山区的模拟水平,但2 km高分辨率仍不足以完全显式解析积云对流过程,需要恰当的积云参数化的协同作用。

关键词: WRF模式, 秦岭, 降水, 积云参数化, 水平分辨率

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