中国科学 地球科学 2012,42: 301-312 DOI:     ISSN: 1674-7240 CN: 11-5842/P

本期目录 | 下期目录 | 过刊浏览 | 高级检索                                                            [打印本页]   [关闭]
论文
扩展功能
本文信息
补充材料
PDF(1132KB)
[HTML全文]
参考文献
服务与反馈
把本文推荐给朋友
加入我的书架
加入引用管理器
引用本文
Email Alert
文章反馈
浏览反馈信息
本文关键词相关文章
WRF 和MM5
北京地区
局地大气环流
模拟精度
比较研究
本文作者相关文章
PubMed

MM5和WRF对北京地区低层大气局地环流模拟能力的对比研究

刘振鑫①②, 刘树华①②③*, 胡非, 李炬, 马雁军, 刘和平

① 北京大学物理学院大气与海洋科学系, 北京 100871;
② 中国气象局北京城市气象研究所, 北京 100089;
③ 中国科学院大气物理研究所大气边界层物理和大气化学国家重点实验室, 北京 100029;
④ 中国气象局沈阳大气环境研究所, 沈阳 110016;
⑤ Department of Physics, Atmospheric Sciences & General Science, Jackson State University, P O Box 17660, Jackson, MS, USA

摘要

为了检验中尺度模式MM5 和WRF 在大气边界层局地环流研究中的适用性, 本文应用MM5V3.7 和WRFV2.2 对北京地区低层大气中温度场和风场等边界层特征量进行了若干个例模拟, 将模拟结果与该区域19 个自动气象站的观测资料进行相关性检验和误差分析,比较两个中尺度模式对该地区大气边界层中存在的中尺度局地耦合环流结构的模拟能力.结果表明WRF 与MM5 对该地区由海陆风环流、山谷风环流和城市热岛环流共同作用形成的大气边界层局地耦合环流的位置、范围、结构特征和日变化特征的模拟均与实测结果较为吻合; WRF 和MM5 对近地面温度场的模拟精度均明显高于对近地面风场的模拟精度. MM5比WRF 对于地表热力过程的描述更加细致精确, 因而对该地区近地面温度场的模拟精度比WRF 略高. WRF 对近地面风场, 尤其是对阵风背景下的近地面风场结构有比MM5 更好的模拟能力. 另外, 模拟结果以及其统计分析均表明: WRF 与MM5 对近地面风场的模拟精确度均由城郊到市区逐渐降低, 反映了两种模式对城市复杂下垫面精细结构条件下的陆面过程的描述均有待进一步改进.

关键词 WRF 和MM5   北京地区   局地大气环流   模拟精度   比较研究  

Abstract:

Keywords:
收稿日期 2010-07-19 修回日期 2011-05-02 网络版发布日期  
DOI:
基金项目:

国家自然科学基金(批准号: 40875004)、中国气象局北京城市气象研究所城市气象科学研究基金(编号: UMRF200702)、科学技术部公益性行业专项(气象)科研专项基金(编号: GYHY200806020)、 国家科技支撑计划项目(编号: 2008BAC37B00)和中央级公益性科研院所基本科研业务费专项基金(编号: IUMKY200701)资助

通讯作者: 刘树华
Email: lshuhua@pku.edu.cn
作者简介:

参考文献:

1 刘树华, 刘振鑫, 李炬, 等. 京津冀地区大气局地环流耦合效应的数值模拟. 中国科学D 辑: 地球科学, 2009, 39: 88–98
2 李晓莉, 毕宝贵, 李泽椿. 北京冬季城市边界层结构形成机制的初步数值研究. 气象学报, 2005, 63: 889–902
3 佟华, 陈仲良, 桑建国. 城市边界层数值模式研究以及在香港地区复杂地形下的应用. 大气科学, 2004, 28: 957–978
4 Hu X M, Liu S H, Wang Y C, et al. Numerical simulation of wind and temperature fields over Beijing area in summer. Acta Meteorol Sin, 2005, 19: 120–127
5 杨玉华, 徐祥德, 翁永辉. 北京城市边界层热岛的日变化周期模拟. 应用气象学报, 2003, 14: 61–68
6 苏福庆, 任阵海, 高庆先, 等. 北京及华北平原边界层大气中污染物的汇聚系统—边界层输送汇. 环境科学研究, 2004, 17: 21–23
7 Grell G A, Dudhia J, Stauffer D R. A description of the fifth-generation Penn State/NCAR Meso-scale Model (MM5). NCAR Technical Note. 1995  
8 Ratnam J V, Kumar K K. Sensitivity of the simulated monsoons of 1987 and 1988 to convective parameterization schemes in MM5. J Clim, 2005, 18: 2724–2743  
9 Reisner J, Rasmussen R M, Bruintjes R T. Explicit forecasting of supercooled liquid water in winter storms using the MM5 meso-scale model. Quart J Royal Meteorol Soc, 1998, 124: 1071–1107  
10 Kotroni V, Lagouvardos K. Precipitation forecast skill of different convective parameterization and microphysical schemes: Application for the cold season over Greece. Geophys Res Lett, 2001, 28: 1977–1980  
11 Angevine W M, Mitchell K. Evaluation of the NCEP meso-scale Eta Model convective boundary layer for air quality applications. Monthly Weather Rev, 2001,129: 2761–2775  
12 Chandrasekar A, Philbrick C R, Clark R, et al. Evaluating the performance of a computationally efficient MM5/CALMET system for developing wind field inputs to air quality models. Atmos Environ, 2003, 37: 3267–3276  
13 Grell G A, Emeis S, Stockwell W R, et al. Application of a multiscale, coupled MM5/chemistry model to the complex terrain of the VOTALP valley campaign. Atmos Environ, 2000, 34: 1435–1453
14 Jackson B, Chau D, Gurer K, et al. Comparison of ozone simulations using MM5 and CALMET/MM5 hybrid meteorological COOS fields for the July/August 2000 episode. Atmos Environ, 2006, 40: 2812–2822  
15 Mao Q, Gautney L L, Cook T M, et al. Numerical experiments on MM5-CMAQ sensitivity to various PBL schemes. Atmos Environ, 2006, 40: 3092–3110  
16 Miao J F, Chen D, Wyser K, et al. Evaluation of MM5 meso-scale model at local scale for air quality applications over the Swedish west coast: Influence of PBL and LSM parameterizations. Meteorol Atmos Phys, 2008, 99: 77–103  
17 Shafran P C, Seaman N L, Gayno G A. Evaluation of numerical predictions of boundary layer structure during the Lake Michigan Ozone Study. J Appl Meteorol, 2000, 39: 412–426  
18 Berg L K, Zhong S Y. Sensitivity of MM5-simulated boundary layer characteristics to turbulence parameterizations. J Appl Meteorol, 2005, 44: 1467–1483  
19 Chen F, Dudhia J. Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Monthly Weather Rev, 2001, 129: 569–585  
20 Lin W S, Wang A Y, Wu C S, et al. A case modeling of sea-land breeze in Macao and its neighborhood. Adv Atmos Sci, 2001, 18: 1231–1240  
21 Miao J F, Chen F, Wyser K. Modelling subgrid scale dry deposition velocity of O3 over the Swedish west coast with MM5-PX model. Atmos Environ, 2006, 40: 415–429  
22 Perez C, Jimenez P, Jorba O, et al. Influence of the PBL scheme on high-resolution photochemical simulations in an urban coastal area over the Western Mediterranean. Atmos Environ, 2006, 40: 5274– 5297  
23 Betts A K, Chen F, Mitchell K E, et al. Assessment of the land surface and boundary layer models in two operational versions of the NCEP Eta Model using FIFE data. Monthly Weather Rev, 1997, 125: 2896–2916  
24 Hanna S R, Yang R X. Evaluations of meso-scale models’ simulations of near-surface winds, temperature gradients, and mixing depths. J Appl Meteorol, 2001, 40: 1095–1104  
25 Zhong S Y, In H J, Bian X D, et al. Evaluation of real-time high-resolution MM5 predictions over the Great Lakes region. Weather Forecast, 2005, 20: 63–81  
26 Xiu A J, Pleim J E. Development of a land surface model. Part I: Application in a meso-scale meteorological model. J Appl Meteorol, 2001,40: 192–209  
27 殷达中, 陈家宜. 一个陆面过程参数化模式与MM5 的耦合. 大气科学, 2000, 24: 177–186
28 Michalakes J, Dudhia J, Gill D, et al. Design of a next-generation regional weather research and forecast model. NCAR Technical Note. 2001  
29 Grell G A, Peckham S E, Schmitz R, et al. Fully coupled “online” chemistry within the WRF model. Atmos Environ, 2005, 39: 6957– 6975  
30 Grell G A, Emeis S, Stockwell W R, et al. Application of a multiscale, coupled MM5/chemistry model to the complex terrain of the VOTALP valley campaign. Atmos Environ, 2000, 34: 1435–1453
31 陈炯, 王建捷. 北京地区夏季边界层结构日变化的高分辨模拟对比. 应用气象学报, 2006, 17: 403–411
32 缪国军, 张镭, 舒红. 利用WRF 对兰州冬季大气边界层的数值模拟. 气象科学, 2007, 27: 169–175
33 Welsh P, Wildman A, Shaw B, et al. Implementing the Weather Research and Forecast (WRF) model with local data Assimilation at NWS WFO Jacksonville Florida. In: 20th Conference on Weather and Forecasting/16th Conference on Numerical Weather Prediction: Seattle, Washington, USA, 2004. 11–15  
34 Jorba O, Loridan T, Jime′nez-Guerrero P. Linking the advanced research WRF meteorological model with the Chimere chemistry- transport model. Environ Model Software, 2008, 1: 1–3
35 Zhong S Y, Fast J. An evaluation of the MM5, RAMS, and Meso-Eta models at subkilometer resolution using VTMX field campaign data in the Salt Lake Valley. Monthly Weather Rev, 2003, 131: 1301– 1322  
36 刘宁微, 王奉安. WRF 和MM5 模式对辽宁暴雨模拟的对比分析. 气象科技, 2006, 34: 364–369
37 蒙伟光, 闫敬华, 扈海波. 城市化对珠江三角洲强雷暴天气的可能影响. 大气科学, 2007, 31: 364–376
38 代成颖, 高志球, 王琳琳, 等. 两种土壤温度算法的对比分析. 大气科学, 2009, 33: 135–144
39 Alapaty K, Raman S, Niyogi D. Uncertainty in the specification of surface characteristics: A study of prediction errors in the Boundary Layer. Boundary-Layer Meteorol, 1997, 82: 475–502  
40 Niyogi D, Raman S, Alapaty K. Uncertainty in specification of surface characteristics. Part 2: Hierarchy of interaction explicit statistical analysis. Boundary-Layer Meteorol, 1999, 91: 341–366

本刊中的类似文章
1.王苏民;薛滨;.中更新世以来若尔盖盆地环境演化与黄土高原比较研究[J]. 中国科学 地球科学, 1996,26(4 ): 323-328
2.于淑秋;卞林根;林学椿; .北京城市热岛“尺度”变化与城市发展[J]. 中国科学 地球科学, 2005,35(S1): 97-106

Copyright 2008 by 中国科学 地球科学