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
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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。Abstract: Five planetary boundary layer (PBL) parameterization schemes [Yonsei University (YSU), Mellor–Yamada–Janjic (MYJ), Mellor–Yamada–Nakanishi–Niino Level 2.5 (MYNN2), Shin-Hong (SH), and the asymmetric convective model, version 2 (ACM2)] in the Weather Research and Forecast model (WRF v4.0), were used to simulate all well-developed Southwest China vortex (SWCV) processes in the eastern Sichuan basin in 2016. Each level of precipitation prediction was verified, and the L-band radiosonde data with temporal resolution of 1 s were used to reveal the fine structure of the PBL during a midday. The differences between the observation and simulation are assessed, and the reasons are discussed based on the characteristics of the turbulence algorithm used in each scheme. Finally, the parameter of turbulence intensity was adjusted for the ACM2 scheme to improve the structure of the PBL that influences the simulation of the precipitation in the eastern Sichuan basin. The results show that the ACM2 and YSU schemes show a relatively better TS performance. Compared with other schemes, ACM2 has fewer false alarms. The attribute of ACM2 that can modify local or nonlocal algorithms according to the stability of the surrounding environment seems to be more suitable for the Sichuan basin precipitation simulation than the other schemes. However, all PBL schemes show a high false-alarm rate in the prediction of the SWCV precipitation, especially when the precipitation is heavy. The sounding data with 1 s temporal and 3 m spatial resolution further show that all the PBL schemes predict a higher PBL height compared with that of the observations, which means that the simulation has a stronger mixing intensity compared with that of the real atmosphere. By parameter adjustment, using the ACM2 scheme with reduced mixing intensity, the potential temperature and humidity structure in PBL are more aligned with the observations. Further, the potential temperature of the low PBL is low, humidity is high, and false alarm reports of heavy precipitation are reduced, which leads to an improvement regarding the precipitation simulation in the Sichuan basin. The different characters of the PBL schemes that are used in the simulation of the SWCV mainly lead to different positions of the vortex and precipitation intensity. Essentially, these characters are derived from a local or nonlocal attribute and the intensity of vertical mixing. A selection based on regional features of a research object is the key to the accurate simulation of a PBL structure and precipitation process.
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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)
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 hPa 700 hPa 850 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 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。 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 a c 实况无降水 b d 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。 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* 0.779 0.78 0.764 0.78 1.008 1.053∆ 1.015 0.903 1.005* 中雨 0.443* 0.43 0.442 0.431 0.439 1.158 1.191∆ 1.156 1.021* 1.156 大雨 0.28 0.272 0.281* 0.276 0.28 1.223 1.229∆ 1.21 1.096* 1.236 暴雨 0.137 0.132 0.134 0.123 0.137* 1.678 1.657 1.668 1.433* 1.678∆ 大暴雨 0.028* 0.023 0.027 0.016 0.027 5.443∆ 5.021 5.051 3.698* 5.087 48 h 小雨 0.793 0.791 0.794 0.78 0.795* 1.027 1.059∆ 1.019* 0.944 1.029 中雨 0.454* 0.443 0.441 0.451 0.452 1.279 1.295∆ 1.245 1.104* 1.285 大雨 0.292 0.282 0.284 0.305* 0.291 1.374∆ 1.335 1.278 1.186* 1.353 暴雨 0.148 0.152 0.148 0.17* 0.155 1.9689∆ 1.9097 1.78 1.767* 1.95 大暴雨 0.05 0.04 0.051 0.065* 0.051 14.878 15.159 14.442 12.270* 15.288∆ 注:*代表最佳方案,∆代表空报最多方案 -
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