论文

WRF模式不同边界层参数化方案模拟兰州冬季边界层高度的研究

  • 王丽霞 ,
  • 王颖 ,
  • 赖锡柳 ,
  • 杨雪玲
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  • 兰州大学大气科学学院, 兰州 730000;青海省人工影响天气办公室, 西宁 810001;兰州大学半干旱气候变化教育部重点实验室, 兰州 730000

收稿日期: 2015-09-16

  网络出版日期: 2017-02-28

基金资助

国家自然科学基金项目(41205077)

Study on the Simulation of Boundary Layer Height in Lanzhou in Winter using WRF Model with Different Boundary Layer Parameterization Schemes

  • WANG Lixia ,
  • WANG Ying ,
  • LAI Xiliu ,
  • YANG Xueling
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  • College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China;Qinghai Province Weather Modification Office, Xining 810001, China;Key Laboratory for Semi-Arid Climate of the Ministry of Education, Lanzhou 730000, China

Received date: 2015-09-16

  Online published: 2017-02-28

摘要

本文利用WRF模式中YSU、MYJ和ACM2三种不同的边界层参数化方案,模拟了2005年1月20-31日兰州市冬季大气边界层高度,并将模拟的边界层高度与同期系留探空资料位温廓线法计算的大气边界层高度进行了比较分析,从闭合方法和混合层高度计算方法等方面探讨了各个方案模拟结果的差异。结果表明三种不同的参数化方案均模拟出了兰州市冬季边界层高度日变化的基本特征,其中,MYJ方案明显偏高,YSU和ACM2方案次之;统计分析结果显示,ACM2方案能较好地模拟兰州市冬季边界层高度。

本文引用格式

王丽霞 , 王颖 , 赖锡柳 , 杨雪玲 . WRF模式不同边界层参数化方案模拟兰州冬季边界层高度的研究[J]. 高原气象, 2017 , 36(1) : 162 -172 . DOI: 10.7522/j.issn.1000-0534.2016.00011

Abstract

In this paper, YSU (Yonsei University scheme), MYJ (Mellor-Yamada-Janjic scheme) and ACM2(Asymmetric Convective Model, version 2) three different boundary layer parameterization schemes in WRF (Weather Research and Forecasting) model were used to simulate the planetary boundary layer height (PBLH) during 20 January to 31 January, 2005 in winter in Lanzhou, and compared the simulation results with the PBLH obtained from temperature profiles which calculated from the data of captive balloon sounding at the same period, and analysis the differences of each scheme simulation results from the closed method and the mixed layer height calculation etc.The analysis shows that:YSU, MYJ, and ACM2 in WRF model can capture the basic characteristics of PBLH in Lanzhou in winter, wherein, MYJ scheme is significantly higher, YSU and ACM2 scheme followed; Statistical analysis showed that, ACM2 scheme can simulate the PBLH in Lanzhou in winter better.

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