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WRF模式边界层参数化方案对川渝盆地西南涡降水模拟的影响

吴志鹏 李跃清 李晓岚 胡小明 周国兵 邓承之

吴志鹏, 李跃清, 李晓岚, 等. 2021. WRF模式边界层参数化方案对川渝盆地西南涡降水模拟的影响[J]. 大气科学, 45(1): 58−72 doi: 10.3878/j.issn.1006-9895.2005.19171
引用本文: 吴志鹏, 李跃清, 李晓岚, 等. 2021. WRF模式边界层参数化方案对川渝盆地西南涡降水模拟的影响[J]. 大气科学, 45(1): 58−72 doi: 10.3878/j.issn.1006-9895.2005.19171
WU Zhipeng, LI Yueqing, LI Xiaolan, et al. 2021. Influence of Different Planetary Boundary Layer Parameterization Schemes on the Simulation of Precipitation Caused by Southwest China Vortex in Sichuan Basin Based on the WRF Model [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(1): 58−72 doi: 10.3878/j.issn.1006-9895.2005.19171
Citation: WU Zhipeng, LI Yueqing, LI Xiaolan, et al. 2021. Influence of Different Planetary Boundary Layer Parameterization Schemes on the Simulation of Precipitation Caused by Southwest China Vortex in Sichuan Basin Based on the WRF Model [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(1): 58−72 doi: 10.3878/j.issn.1006-9895.2005.19171

WRF模式边界层参数化方案对川渝盆地西南涡降水模拟的影响

doi: 10.3878/j.issn.1006-9895.2005.19171
基金项目: 国家自然科学基金项目91937301、42030611,第二次青藏高原综合科学考察研究项目2019QZKK0103、2019QZKK0105,四川省气象局与南京信息工程大学局校合作项目SCJXHZ03,四川省科技计划项目2016JY0046
详细信息
    作者简介:

    吴志鹏,男,1985年出生,硕士研究生,主要从事中尺度数值天气模拟的研究。E-mail: 361913145@qq.com

    通讯作者:

    李跃清,E-mail: yueqingli@163.com

  • 中图分类号: P435

Influence of Different Planetary Boundary Layer Parameterization Schemes on the Simulation of Precipitation Caused by Southwest China Vortex in Sichuan Basin Based on the WRF Model

Funds: National Natural Science Foundation of China (Grants 91937301, 42030611), The Second Tibetan Plateau Scientific Expedition and Research (STEP) Program (Grants 2019QZKK0103, 2019QZKK0105); Cooperation Project between Sichuan Provincial Meteorological Bureau and Nanjing University of Information Science–Technology (Grant SCJXHZ03); Sichuan Provincial Science and Technology Project (Grant 2016JY0046)
  • 摘要: 应用WRF v4.0模式五种边界层参数化方案(YSU、MYJ、MYNN2、ACM2和SH),对2016 年汛期(5~9月)在川渝盆地东部造成暴雨的所有西南涡过程进行了数值模拟,检验评估了它们对各量级降水的预报能力,并基于加密的L波段秒级探空资料对比分析了模拟与实况边界层结构的差异,结合各方案对湍流运动的算法特点探讨了其差异的原因,最后对ACM2方案进行了湍流强度调整,由此改善其对于川渝盆地边界层与西南涡降水的模拟能力。结果表明:ACM2和YSU方案TS评分表现较好,相对其它方案ACM2空报较少,这种可以根据周围环境的稳定性切换局地或非局地算法的方案更适合于盆地西南涡降水模拟,但边界层方案对西南涡降水的空报都较普遍,尤以大量级降水更明显;精细的探空资料进一步表明,所有方案模拟的白天边界层高度都偏高,湍流混合强度都偏强。通过参数调整而降低混合强度的ACM2方案,模拟的边界层温湿结构则更符合实际观测,其边界层下部温度更低、湿度更高,减少了大量级降水的空报,使盆地西南涡降水模拟有一定改善;边界层参数化方案对西南涡模拟的差别主要体现为不同的西南涡位置与降水强度,但归根到底都源于方案的局地或非局地特性、不同的混合强度这两方面原因。因此,根据不同特定区域下垫面环境与气候状况合理选择方案的特性和混合强度是准确模拟边界层结构及其降水过程的关键。
  • 图  1  嵌套区域图(红点处为重庆站)。d01格距为27 km,格点数为200×160;d02格距为9 km,格点数为288×216;d03格距为3 km,格点数为480×360

    Figure  1.  Forecast and nest area diagram (red spot is Chongqing station). d01 grid resolution is 27 km and grid number is 200×160; d02 grid resolution is 9 km and grid number is 288×216; d03 grid resolution is 3 km and grid number is 480×360

    图  2  2016年5~9月所有西南涡过程的五种边界层参数化方案降水TS平均评分:(a)24 h预报;(b)48 h预报

    Figure  2.  TS (Threat Score) mean scores of the five planetary boundary layer (PBL) schemes for all the Southwest China vortex (SWCV) processes in 2016 flood season(From May to September)at (a) 24-h precipitation and (b) 48-h precipitation forecast time

    图  3  2016年几次西南涡过程5种方案的边界层模拟高度与观测高度对比:(a)“6.1”过程;(b)“6.23”过程;(c)“6.30”过程;(d)“6.19”过程;(e)“7.14”过程;(f)“7.18”过程。BJT:北京时间

    Figure  3.  Comparison between the observed PBL height and simulated height with the five schemes of the several SWCV processes in 2016: (a) “6.1” process;(b) “6.23” process; (c) “6.30” process; (d) “6.19” process; (e) “7.14” process; (f) “7.18” process. BJT: Beijing time

    图  4  2016年“6.19”过程重庆站上空位温、水汽混合比层结廓线:(a)初始位温;(b)24 h位温;(c)48 h位温;(d)初始水汽混合比;(e)24 h水汽混合比;(f)48 h水汽混合比

    Figure  4.  Profiles of potential temperature and QVAPOR (water vapor mixing ratio) over Chongqing station during the “6.19” process in 2016: (a–c) Potential temperature profiles at (a) 0, (b) 24, and (c) 48-h forecast time; (d–f) QVAPOR profiles at (d) 0, (e) 24, and (f) 48-h forecast time

    图  5  2016年“6.23”与“7.18”过程重庆站上空位温、水汽混合比层结廓线:(a)“6.23”过程6 h位温;(b)“7.18”过程6 h位温;(c)“7.18”过程30 h位温;(d)“6.23”过程6 h水汽混合比;(e)“7.18”过程6 h水汽混合比;(f)“7.18”过程30 h水汽混合比

    Figure  5.  Profiles of potential temperature and QVAPOR over Chongqing station during the “6.23” and “7.18” processes in 2016: (a) Potential temperature profile at 6 h in the “6.23” process; (b, c) potential temperature profile at (b) 6 and (c) 30 h in the “7.18” process; (d) QVAPOR profile at 6 h in the “6.23” process; (e, f) QVAPOR profile at (e) 6 and (f) 30 h in the “7.18” process

    图  6  基于ACM2方案不同混合强度p值的2016年“6.19”过程重庆站上空边界层高度、位温和水汽混合比层结廓线:(a)边界层高度;(b)48 h位温;(c)48 h水汽混合比

    Figure  6.  PBL height, potential temperature, and QVAPOR profiles over Chongqing station during the “6.19” process in 2016, simulating with the ACM2 (Asymmetric convective model 2) scheme that modified to different values of p: (a) PBL height; (b) potential temperature profile at 48 h; (c) QVAPOR profile at 48 h

    图  7  五种边界层参数化方案与基于ACM2方案不同混合强度p值预报的2016年“6.19”过程48 h 700 hPa位势高度场(蓝色等值线,单位:gpm)、风场(风标)和24~48 h累积降水量(彩色阴影,单位:mm):(a)观测;(b)YSU方案;(c)MYJ方案;(d)SH方案;(e) MYNN2方案;(f)ACM2方案;(g)ACM2 (p=2.25);(h)ACM2 (p=2.5);(i)ACM2 (p=2.75);(j)ACM2 (p=3.0)

    Figure  7.  The 48-h prediction of 700-hPa geopotential height field (blue contour,unit:gpm), wind field (barb) and 24–48-h cumulative precipitation (color shaded,unit:mm) with five PBL schemes and ACM2 modified at different values of p in the “6.19” process in 2016: (a) Observations; (b) YSU scheme; (c) MYJ scheme; (d) SH scheme; (e) MYNN2 scheme; (f) ACM2 scheme; (g) ACM2(p= 2.25); (h) ACM2(p= 2.5); (i) ACM2(p= 2.75); (j) ACM2(p= 3.0)

    图  8  基于ACM2方案不同混合强度p值的2016年“6.19”过程和全年西南涡过程24~48 h累积降水平均TS评分:(a)“6.19”过程;(b)全年西南涡过程平均

    Figure  8.  TS score during 24 h-48 h of ACM2 scheme with different values of p in the “6.19” process and the average TS score of all the SWCV processes in 2016: (a) “6.19” process; (b) average of all processes

    表  1  2016年汛期盆地东部区域性暴雨过程及影响系统

    Table  1.   Heavy rainfall processes and affecting weather systems in the eastern part of the Sichuan Basin in 2016

    暴雨过程时间(北京时)影响系统
    500 hPa700 hPa850 hPa地面
    “5.6”5月6日14时~8日08时低槽、高原涡西南涡西南涡、急流冷锋、热低压
    “6.1”6月31日20时~7月2日20时低槽、高原涡西南涡、急流西南涡、急流冷锋、辐合线
    “6.19”6月18日18时~20日14时低槽西南涡、急流西南涡、急流辐合线
    “6.23”6月23日18时~25日08时低槽西南涡、急流西南涡、急流冷锋、热低压
    “6.27”6月26日20时~28日20时低槽切变线、急流切变线冷锋、辐合线
    “6.30”6月30日02时~7月1日10时低槽、高原涡西南涡、急流西南涡、急流辐合线
    “7.14”7页13日19时~15日08时低槽、高原涡西南涡西南涡冷锋
    “7.18”7月18日14时~20日08时低槽西南涡、急流西南涡、急流冷锋、辐合线
    “9.9”9月9日02时~20时低槽切变线切变线辐合线
    下载: 导出CSV

    表  2  五种边界层参数化方案简介与选用利弊

    Table  2.   Listing of chosen weather research forecast planetary boundary layer (PBL) schemes along with a reference, a brief description, and their pros and cons

    边界层参数化方案方案类型方案描述
    YSU Hong et al.(2006)1阶非局地闭合K方案与MRF类似,除了在边界层顶对夹卷层有更准确的描述,加强了热力驱动的自由混合强度,减少了动力强迫性对流混合,但仍然发现其在深厚湿对流模拟中对边界层混合强度计算偏强。边界层高度由浮力廓线决定。
    MYJ Janjić(2001)1.5阶局地闭合方案局地垂直混合的一维湍流动能(TKE)预测方案,只计算在相邻格点上的通量交换,对较大涡旋完成的垂直混合往往计算不够,适合在稳定层结使用。边界层高度定义为TKE的生成不能平衡其耗散的最低模式层高度。
    ACM2 Pleim(2007)1阶局地—非局地混合型闭合方案通过牺牲更多的计算资源,ACM2同时具备了局地与非局地的理念,它通过调整湍流扩散项和非局地项之间的比例系数来实现从稳定条件下的涡动扩散算法到不稳定条件下局地和非局地输送算法,使其平稳转换Pleim(2007)。也有研究指出ACM2在夜间的混合强度偏强Coniglio et al.(2013)
    MYNN2 Nakanishi and Niino(2006)1.5阶局地闭合方案在MYJ基础上改进,不通过观测而基于大涡模拟的结果表达稳定度和混合高度,使得方案更适合在对流状态的边界层描述。即便如此,依旧受到局地方案的约束,可能对较大涡旋产生的湍流混合强度模拟不够。
    SH Shin and Hong(2015)优化对流环境下的1阶非局地闭合K方案由YSU改进而来。在对流边界层中加入了垂直传输的尺度依赖性,分别对待对流环境下的非局地传输和其余小尺度涡流引起的局地传输,在稳定状态下的边界层垂直混合或自由大气中保持和YSU一样,在WRF3.7以后SH方案也同样诊断TKE与混合高度。但SH方案的启动调整(Spin-up)相对大涡模拟有偏差,达到准平衡状态较晚。
    下载: 导出CSV

    表  3  标准2×2二分类事件列联表

    Table  3.   Contingency table of standard 2×2 bicategorical event

    预报有降水预报无降水
    实况有降水ac
    实况无降水bd
    注:a代表预报准确的,b代表空报的,c代表漏报的,d代表实况和降水均没有的情况。
    下载: 导出CSV

    表  4  所有过程五种参数化方案降水24 h、48 h 预报的TS平均值和BS平均值

    Table  4.   TS mean-score values of five PBL schemes for all Southwest China vortex (SWCV) processes at 24- and 48-h precipitation and the same for BS at 24 and 48 h

    全过程TS平均全过程BS平均
    YSU方案MYJ方案MYNN2方案ACM2方案SH方案YSU方案MYJ方案MYNN2方案ACM2方案SH方案
    24 h小雨0.781*0.7790.780.7640.781.0081.0531.0150.9031.005*
    中雨0.443*0.430.4420.4310.4391.1581.1911.1561.021*1.156
    大雨0.280.2720.281*0.2760.281.2231.2291.211.096*1.236
    暴雨0.1370.1320.1340.1230.137*1.6781.6571.6681.433*1.678
    大暴雨0.028*0.0230.0270.0160.0275.4435.0215.0513.698*5.087
    48 h小雨0.7930.7910.7940.780.795*1.0271.0591.019*0.9441.029
    中雨0.454*0.4430.4410.4510.4521.2791.2951.2451.104*1.285
    大雨0.2920.2820.2840.305*0.2911.3741.3351.2781.186*1.353
    暴雨0.1480.1520.1480.17*0.1551.96891.90971.781.767*1.95
    大暴雨0.050.040.0510.065*0.05114.87815.15914.44212.270*15.288
    注:*代表最佳方案,代表空报最多方案
    下载: 导出CSV
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  • 收稿日期:  2019-06-13
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