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双参数微物理方案的冰相过程模拟及冰核数浓度的影响试验

沈新勇 梅海霞 王卫国 黄文彦

沈新勇, 梅海霞, 王卫国, 黄文彦. 双参数微物理方案的冰相过程模拟及冰核数浓度的影响试验[J]. 大气科学, 2015, 39(1): 83-99. doi: 10.3878/j.issn.1006-9895.1405.13310
引用本文: 沈新勇, 梅海霞, 王卫国, 黄文彦. 双参数微物理方案的冰相过程模拟及冰核数浓度的影响试验[J]. 大气科学, 2015, 39(1): 83-99. doi: 10.3878/j.issn.1006-9895.1405.13310
SHEN Xinyong, MEI Haixia, WANG Weiguo, HUANG Wenyan. Numerical Simulation of Ice-Phase Processes Using a Double-Moment Microphysical Scheme and a Sensitivity Test of Ice Nuclei Concentration[J]. Chinese Journal of Atmospheric Sciences, 2015, 39(1): 83-99. doi: 10.3878/j.issn.1006-9895.1405.13310
Citation: SHEN Xinyong, MEI Haixia, WANG Weiguo, HUANG Wenyan. Numerical Simulation of Ice-Phase Processes Using a Double-Moment Microphysical Scheme and a Sensitivity Test of Ice Nuclei Concentration[J]. Chinese Journal of Atmospheric Sciences, 2015, 39(1): 83-99. doi: 10.3878/j.issn.1006-9895.1405.13310

双参数微物理方案的冰相过程模拟及冰核数浓度的影响试验

doi: 10.3878/j.issn.1006-9895.1405.13310
基金项目: 国家重点基础研究发展计划(973计划)项目2013CB430103、2015CB453200,国家自然科学基金项目41375058、41175065,江苏高等学校优秀科技创新团队计划项目PIT2012

Numerical Simulation of Ice-Phase Processes Using a Double-Moment Microphysical Scheme and a Sensitivity Test of Ice Nuclei Concentration

  • 摘要: 利用耦合Morrison 2-mon(MOR)双参数微物理方案的中尺度天气研究与预报模式(WRF)中的单气柱模式,对热带暖池国际云试验(TWP-ICE)期间的个例进行数值模拟。通过与观测资料和云分辨率模式的模拟结果进行对比,检验MOR方案对热带对流云系的微物理特征的模拟能力。模拟结果显示:MOR方案能够较好地模拟出热带云系中液相和冰相水凝物的垂直分布以及随时间的演变特征。地表向下长波辐射和大气顶向外长波辐射的量级和时间演变趋势同观测也非常接近。对与冰晶和雪有关的云微物理特征分析之后发现:季风活跃期,冰晶主要的源汇项有凝华增长过程、沉降过程、冰晶向雪的自动转化以及冰晶被雪碰并的过程。由于冰晶主体位于温度低于―20℃的高空,因而它对雨水的形成主要是间接贡献。同时期雪的主要源汇项中,凝华增长和沉降过程占据着主导地位。雪的凝华过程消耗了大量的水汽,可能抑制了冰晶的增长。另外雪的融化过程非常强盛,是产生降水的重要因子。季风抑制期,冰相的微物理过程变得相对简单且整体削弱,以凝华升华和沉降过程为主。凝华凝冻核的数浓度(Ndep)的气溶胶敏感性试验表明:季风抑制期,高空的冰晶云的宏观和微观性质对凝华凝冻核数浓度的响应情况呈现显著的线性特征。冰晶的含量随着Ndep的增加而增加,反之降低。该时期微物理过程主要同冰晶有关,水分的分配较为简单,Ndep增加时,高空冰云中小冰晶粒子数目增多且云顶升高,使得大气顶部向外长波辐射(OLR)值减小,反之冰云主体中冰晶有效半径增加,高空的冰云更加透明,云顶更低,对 OLR值增加起促进作用。而季风活跃期,微物理过程复杂,冰晶云的宏微观特征对Ndep的响应表现出一定的不规律特征。
  • [1] Bryan G H, Wyngaard J C, Fritsch J M. 2003. Resolution requirements for the simulation of deep moist convection [J]. Mon. Wea. Rev., 131 (10): 2394-2416.
    [2] 陈炯, 郑永光, 邓莲堂, 等. 2003. WRF 模式中不同边界层参数化方案对2003 年7 月江淮暴雨的数值模拟及其比较 [C]//中国气象学会2003年年会论文集 (7). 北京: 气象出版社, 221-224. Chen Jiong, Zheng Yongguang, Deng Liantang, et al. 2003. The effects of different boundary layer parameterization schemes in WRF on the numerical simulation for a rainstorm over Changjiang-Huaihe river basin in July 2003 [C]//Proceedings of the 2003 Chinese Meteorological Society (in Chinese). Beijing: China Meteorological Press, 221-224.
    [3] Comstock J M, Ackerman T P, Mace G G. 2002. Ground-based lidar and radar remote sensing of tropical cirrus clouds at Nauru Island: Cloud statistics and radiative impacts [J]. Journal of Geophysical Research: Atmospheres (1984-2012), 107 (D23): AAC 16-1-AAC 16-14.
    [4] 董昊, 徐海明, 罗亚丽. 2012. 云凝结核浓度对 WRF 模式模拟飑线降水的影响: 不同云微物理参数化方案的对比研究 [J]. 大气科学, 36 (1): 145-169. Dong Hao, Xu Haiming, Luo Yali. 2012. Effects of cloud condensation nuclei concentration on precipitation in convection permitting simulations of a squall line using WRF model: Sensitivity to cloud microphysical schemes [J]. Chinese Journal Atmospheric Science (in Chinese), 36 (1): 145-169.
    [5] Fan J, Comstock J M, Ovchinnikov O. 2010. The cloud condensation nuclei and ice nuclei effects on tropical anvil characteristics and water vapor of the tropical tropopause layer [J]. Environ. Res. Lett., 5 (4), 044005, doi: 10.1088/1748-9326/5/4/044005.
    [6] Gettelman A, Morrison H, Ghan S J. 2008. A new two-moment bulk stratiform cloud microphysics scheme in the Community Atmosphere Model, Version 3 (CAM3). Part II: single-column and global results [J]. J. Climate, 21: 3660-3679.
    [7] Ghan S, Randall D, Xu K-M, et al. 2000. A comparison of single column model simulations of summertime midlatitude continental convection [J]. J. Geophys. Res., 105 (D2): 2091-2124.
    [8] Hack J J, Pedretti J A. 2000. Assessment of solution uncertainties in single-column modeling frameworks [J]. J. Climate, 13 (2): 352-365.
    [9] 金莲姬, 银燕, 王盘兴, 等. 2007. 热带深对流云砧数值模拟及云凝结核数浓度对其影响的初步试验 [J]. 大气科学, 31 (5): 793-804. Jin Lianji, Yin Yan, Wang Panxing, et al. 2007. Numerical modeling of tropical deep convective anvil and sensitivity test on its response to changes in the cloud condensation nuclei concentration [J]. Chinese Journal Atmospheric Science (in Chinese), 31(5): 793-804.
    [10] 鞠永茂, 王汉杰, 钟中, 等. 2008. 一次梅雨锋暴雨云物理特征的数值模拟研究 [J]. 气象学报, 66 (3): 381-395. Ju Yongmao, Wang Hanjie, Zhong Zhong, et al. 2008. A simulation study on the characteristics of cloud microphysics of rain storm in a meiyu front [J]. Acta Meteorologica Sinica (in Chinese), 66(3): 381-395.
    [11] 康丽莉, 雷恒池, 肖稳安. 2003. 中尺度模式中各种湿物理过程的数值模拟 [J]. 南京气象学院学报, 26 (1): 76-83. Kang Lili, Lei Hengchi, Xiao Wenan. 2003. Simulation of various moist physical processes in mesoscale model [J]. Journal of Nanjing Institute of Meteorology (in Chinese), 26(1): 76-83.
    [12] Lean H W, Clark P A, Dixon M, et al. 2008. Characteristics of high- resolution versions of the Met Office Unified Model for forecasting convection over the United Kingdom [J]. Mon. Wea. Rev., 136 (9): 3408-3424.
    [13] 李娟, 毛节泰, 胡志晋, 等. 2004. 冰核浓度变化对云辐射的模拟试验 [J]. 气象学报, 62 (1): 77-86. Li Juan, Mao Jietai, Hu Zhijin, et al. 2004. Numerical simulation experiments for the effects of changes of atmospheric ice nuclei concentrations on radiant properties of cloud [J]. Acta Meteorologica Sinica (in Chinese), 62(1): 77-86.
    [14] Lim K-S S, Hong S-Y. 2010. Development of an effective double-moment cloud microphysics scheme with prognostic Cloud Condensation Nuclei (CCN) for weather and climate models [J]. Mon. Wea. Rev., 138 (5): 1587-1612.
    [15] Luo Y, Xu K-M, Morrison H, et al. 2008. Arctic mixed-phase clouds simulated by a cloud-resolving model: Comparison with ARM observations and sensitivity to microphysics parameterizations [J]. J. Atmos. Sci., 65 (4): 1285-1303.
    [16] 马国忠, 银燕, 王秋京. 2010. 东北地区春季冷锋云系降水个例数值模拟及机理研究 [J]. 黑龙江气象, 27 (4): 4-8. Ma Guozhong, Yin Yan, Wang Qiujing. 2010. Mechanism and numerical simulating study of the cold front precipitation in Northeast China [J]. Heilongjiang Meteorology (in Chinese), 27(4): 4-8.
    [17] Mather J H, McFarlane S A, Miller M A, et al. 2007. Cloud properties and associated radiative heating rates in the tropical western Pacific [J]. J. Geophys. Res., 112, D05201, doi: 10.1029/2006JD007555.
    [18] May P T, Mather J H, Vaughan G, et al. 2008. Field research: Characterizing oceanic convective cloud systems [J]. Bull. Amer. Meteor. Soc., 89 (2): 153-155.
    [19] Morrison H, Milbrandt J. 2011. Comparison of two-moment bulk microphysics schemes in idealized supercell thunderstorm simulations [J]. Mon. Wea. Rev., 139 (4): 1103-1130.
    [20] Morrison H, Pinto J O. 2005. Mesoscale modeling of springtime Arctic mixed-phase stratiform clouds using a new two-moment bulk microphysics scheme [J]. J. Atmos. Sci., 62 (10): 3683-3704.
    [21] Morrison H, Curry J A, Khvorostyanov V I. 2005a. A new double-moment microphysics parameterization for application in cloud and climate models. Part I: description [J]. J. Atmos. Sci., 62 (6): 1665-1677.
    [22] Morrison H, Curry J A, Shupe M D, et al. 2005b. A new double-moment microphysics parameterization for application in cloud and climate models Part II: Single-column modeling of Arctic clouds [J]. J. Atmos. Sci., 62: 1678-1693.
    [23] Morrison H, Thompson G, Tatarskii V. 2009. Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes [J]. Mon. Wea. Rev., 137 (3): 991-1007.
    [24] Narita M, Ohmori S. 2007. Improving precipitation forecasts by the operational nonhydrostatic mesoscale model with the Kain-Fritsch convective parameterization and cloud microphysics [C]//Preprints, 12th Conference on Mesoscale Processes, Waterville Valley, NH, Am. Meteor. Soc., CD-ROM, 3.7. [Available online at http://ams.confex.com/ams/pdfpapers/126017.pdf.]
    [25] 荣艳敏, 银燕. 2010. 对流云对大气气溶胶和相对湿度变化响应的数值模拟 [J]. 大气科学, 34 (4): 815-826. Rong Yanmin, Yin Yan. 2010. The response of convective clouds to aerosol and relative humidity: A numerical study [J]. Chinese Journal Atmospheric Science (in Chinese), 34(4): 815-826.
    [26] Seo E-K, Liu G. 2006. Determination of 3D cloud ice water contents by combining multiple data sources from satellite, ground radar, and a numerical model [J]. J. Appl. Meteor. Climatol., 45 (11): 1494-1504.
    [27] Solomon A, Morrison H, Persson O, et al. 2009. Investigation of microphysical parameterizations of snow and ice in Arctic clouds during M-PACE through model-observation comparisons [J]. Mon. Wea. Rev., 137 (9): 3110-3128.
    [28] Song X L, Zhang G J. 2011. Microphysics parameterization for convective clouds in a global climate model: Description and single-column model tests [J]. J. Geophys. Res., 116, D02201, doi: 10.1029/2010JD014833.
    [29] Stith J L, Hagerty J A, Heymsfield A J, et al. 2004. Microphysical characteristics of tropical updrafts in clean conditions [J]. J. Appl. Meteor., 43 (5): 779-794.
    [30] 孙建华, 赵思维. 2003. 华北地区 “12·7” 降雪过程的数值模拟研究 [J]. 气候与环境研究, 8 (4): 387-401. Sun Jianhua, Zhao Siwei. 2003. A numerical simulation of snowfall in North China on 7 December 2001 [J]. Climatic and Environmental Research (in Chinese), 8 (4): 387-401.
    [31] Van Weverberg K, Voglemann A M, Lin W, et al. 2012. The role of cloud microphysics parameterization in the simulation of mesoscale convect: 4309-4329.louds and precipitation in the tropical Western Pacific [J]. J. Atmos. Sci., 70 (4): 1104-1128. doi: 10.1175/JAS-D-12-0104.1.
    [32] Varble A, Fridlind A M, Zipser E J, et al. 2011. Evaluation of cloud- resolving model intercomparison simulations using TWP-ICE observations: Precipitation and cloud structure [J]. J. Geophys. Res., 116: D12206. doi: 10.1029/2010JD015180.
    [33] 肖辉, 银燕. 2011. 污染气溶胶对山西一次降水过程影响的数值模拟 [J]. 大气科学, 35 (2): 235-246. Xiao Hui, Yin Yan. 2011. A numerical study of polluted aerosol effects on precipitation in Shanxi Province [J]. Chinese Journal Atmospheric Science (in Chinese), 35(2): 235-246.
    [34] Wang W, Liu X, Xie S, et al. 2009. Testing ice microphysics parameterizations in the NCAR Community Atmospheric Model Version 3 using Tropical Warm Pool-International Cloud Experiment data [J]. J. Geophys. Res., 114: D14107. doi: 10. 1029/2008JD011220.
    [35] 吴伟. 2011. 基于CloudSat及MODIS卫星云产品对GRAPES全球模式和WRF模式云微物理方案的对比检验 [D]. 兰州大学博士论文, 97pp. Wu Wei. 2011. Comparison to the sensitivity of GRAPES and WRF Model cloud microphysical parameterization schemes using CloudSat and MODIS satellite data [D]. Ph. D. dissertation (in Chinese). College of Atmospheric Sciences, Lanzhou University, 97pp.
    [36] Xie S, Hume T, Jakob C, et al. 2010. Observed large-scale structures and diabatic heating and drying profiles during TWP-ICE [J]. J. Climate, 23 (1): 57-79.
    [37] 许焕斌, 段英. 1999. 云粒子谱演化研究中的一些问题 [J]. 气象学报, 57 (4): 450-460. Xu Huanbin, Duan Ying. 1999. Some questions in studying the evolution of size distribution spectrum of hydrometeor particles [J]. Acta Meteorologica Sinica (in Chinese), 57(4): 450-460.
    [38] 于翡, 姚展予. 2009. 一次积层混合云降水实例的数值模拟分析 [J]. 气象, 35 (12): 3-11. Yu Fei, Yao Zhanyu. 2009. Numerical study on the complex of the stratiform and embedded convective cloud precipitation: A case study [J]. Meteorological Monthly (in Chinese), 35 (12): 3-11.
    [39] 余贞寿, 王红雷. 2010. 微物理过程和对流参数化对台风“莫拉克”(0908)路径模拟影响研究 [C]//第七届长三角气象科技论坛论文集, 148-155. Yu Zhenshou, Wang Honglei. 2010. A numerical study of the effect of various microphysics and cumulus parameterization schemes on typhoon Morakot (0908) track [C]//The Proceedings of 7th Yangtze River Delta Science and Technology Forum (in Chinese), 148-155.
    [40] Zeng X P, Tao W K, Zhang M H, et al. 2009. An indirect effect of ice nuclei on atmospheric radiation [J]. J. Atmos. Sci., 66 (1): 41-61.
    [41] 张大林. 1998. 各种非绝热物理过程在中尺度模式中的作用 [J]. 大气科学, 22 (4): 548-561. Zhang Dalin. 1998. Roles of various diabatic physical processes in mesoscale models [J]. Chinese Journal Atmospheric Science (in Chinese), 22 (4): 548-561.
    [42] Zhang J, Lohmann U, Lin B. 2002. A new statistically based autoconversion rate parameterization for use in large-scale models [J]. J. Geophys. Res., 107 (D24): AAC 3-1-AAC 3-16, doi: 10.1029/2001JD001484.
    [43] Zhang M H, Lin J L. 1997. Constrained variational analysis of sounding data based on column-integrated budgets of mass, heat, moisture, and momentum: Approach and application to ARM measurements [J]. J. Atmos. Sci., 54: 1503-1524.
    [44] Zhang M H, Lin J L, Cederwall R T, et al. 2001. Objective analysis of ARM IOP data: Method and sensitivity [J]. Mon. Wea. Rev., 129: 295-311.
    [45] 赵思雄, 曾庆存. 2005. 东亚强寒潮——冷涌越过赤道并引发南半球热带气旋和强降水的个例研究 [J]. 气候与环境研究, 10 (3): 507-525. Zhao Sixiong, Zeng Qingcun. 2005. A study of East Asia strong cold wave—Surge crossing equator and influencing the development of tropical cyclone and heavy rainfall in the Southern Hemisphere [J]. Climatic and Environmental Research (in Chinese), 10 (3): 507-525.
    [46] 邹德龙, 罗栩羽, 范绍佳, 等. 2012. 不同天气系统影响下广东省酸雨特征对比分析——气象场数值模拟 [J]. 中国环境科学, 32 (8): 1439- 1446. Zou Delong, Luo Xuyu, Fan Shaojia, et al. 2012. Comparative analysis of the features of acid rain under the influence of different weather systems in Guangdong Province—Numerical simulation of meteorological fields [J]. China Environmental Science (in Chinese), 32 (8): 1439-1446.
    [47] Zhou Y P, Tao W K, et al. 2007. Use of high-resolution satellite observations to evaluate cloud and precipitation statistics from cloud-resolving model simulations. Part I: South China Sea monsoon experiment [J]. J. Atmos. Sci., 64
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