边界层参数化方案在“灰色区域”尺度下的适用性评估

刘梦娟; 张旭; 陈葆德

doi:10.3878/j.issn.1006-9895.1704.16269

边界层参数化方案在“灰色区域”尺度下的适用性评估

doi: 10.3878/j.issn.1006-9895.1704.16269

刘梦娟^{1, 2,},
张旭^{1, 3, ,},
陈葆德^{1, 3}

1.
上海区域高分辨率数值预报创新中心, 上海 200030
2.
上海中心气象台, 上海 200030
3.
中国气象局上海台风研究所, 上海 200030

基金项目:

国家自然科学基金项目 41505087

国家自然科学基金项目 41575101

国家重点研发计划“政府间科技合作项目”重点专项 2016YFE0109700

详细信息

作者简介:
刘梦娟, 女, 1987年出生, 助理工程师, 主要从事边界层观测资料、数值模拟研究。E-mail:mengjuan.liu@gmail.com

通讯作者:
张旭, E-mail:zhangx@mail.typhoon.gov.cn

中图分类号: P456.7
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- 被引次数: 0
出版历程
- 收稿日期: 2016-11-24
- 网络出版日期: 2017-04-25
- 刊出日期: 2018-01-15

Assessment of the Suitability of Planetary Boundary Layer Schemes at "Grey Zone" Resolutions

Mengjuan LIU^{1, 2
,},
Xu ZHANG^{1, 3
, ,},
Baode CHEN^{1, 3}

1.
Shanghai Innovative Center of Regional High Resolution Numerical Weather Prediction, Shanghai 200030
2.
Shanghai Central Meteorological Observatory, Shanghai 200030
3.
Shanghai Typhoon Institute of China Meteorological Administration, Shanghai 200030

Funds:

National Natural Science Foundation of China 41505087

National Natural Science Foundation of China 41575101

National Key Research and Development Program of China 2016YFE0109700

摘要

摘要: 随着数值预报模式分辨率的提高，当模式网格距与含能湍涡的长度尺度相当时，模式动力过程可解析一部分湍流运动，而剩余的湍流运动仍需参数化，此时便产生了湍流参数化的“灰色区域”问题。对传统的PBL（Planetary Boundary Layer）方案在“灰色区域”下的适用性评估，是改进PBL方案以使其能够适应分辨率变化的前提和基础。本研究基于干对流边界层的大涡模拟试验，比较了WRF（Weather Research and Forecast Model）模式中四种常用的边界层参数化方案[YSU（Yonsei University）、MYJ（Mellor-Yamada-Janjic）、MYNN2.5（Mellor-Yamada-Nakanishi-Niino Level 2.5）、MYNN3）]在“灰色区域”尺度下的表现。研究表明，混合层内总热通量对所使用的参数化方案和水平分辨率均不敏感。不同参数化方案中次网格与网格通量的比例表现出对水平网格距不同的依赖性。局地PBL方案（MYJ、MYNN2.5）在混合层内的平均位温随网格距减小而增大，次网格通量随网格距减小而减小，较参考湍流场对次网格通量有所低估。YSU方案的非局地项几乎不随水平格距改变而变化，对次网格通量的表征并未表现出较强的分辨率依赖性，且过强的非局地次网格输送使混合层内温度层结呈弱稳定，抑制了可分辨湍流输送，不易于激发次级环流。MYNN3方案的非局地次网格通量（负梯度输送项）随网格距减小而减小，使其对次网格通量的表征具有较好的分辨率依赖性。PBL方案在“灰色区域”尺度下的适用性与具体分辨率有关。以分辨率500 m为例，四种PBL方案中不存在一种最佳方案，能对边界层的热力结构和湍流统计特征均有准确的描述。
- 边界层参数化方案 /
- 灰色区域 /
- 大涡模拟 /
- 非局地输送
Abstract: As the resolution in numerical weather prediction models increases, turbulent motion can be partially resolved by grid scale dynamics.However, a substantial part of turbulent motion still needs to be parameterized, which results in the so-called "grey zone" problem.Assessment of the suitability of traditional PBL (Planetary Boundary Layer) schemes at "grey zone" resolutions would provide foundation for future improvement of PBL schemes, making them more adaptive to the variation of resolutions.In this study, the authors assess the performance of four PBL schemes that are commonly used in WRF, i.e.YSU (Yonsei University), MYJ (Mellor-Yamada-Janjic), MYNN (Mellor-Yamada-Nakanishi-Niino Level 2.5) and MYNN3 in the simulation of convective PBL at "grey-zone" resolutions using LES (Large-Eddy Simulation).Results indicate that at higher resolutions, domain-averaged potential temperature increases in the mixing layer with local PBL schemes such as MYJ and MYNN2.5, while subgrid scale flux decreases and falls below the reference value constructed from LES.The nonlocal terms in YSU hardly change with grid size and do not show distinct scale-sensitivity.In contrast, the counter-gradient term in MYNN3 decreases with reduced grid-size and exhibits a certain degree of scale-sensitivity.The strong nonlocal subgrid mixing in YSU results in a weak, stable stratification in the mixing layer and suppresses resolved-scale turbulence mixing, thus impeding the onset of convectively induced secondary circulations in the model.The suitability of PBL schemes at "grey zone" resolutions varies with certain resolutions.For example, at the resolution of 500 m, none of the four PBL schemes performs well to accurately simulate both the thermal structure and turbulent statistics in the PBL.
- PBL parameterization schemes /
- Grey zone /
- LES (Large-Eddy Simulation) /
- Nonlocal mixing

HTML全文

图 1 从LES（Large-Eddy Simulation）试验构造参考湍流变量示意图

Figure 1. Schematic diagram illustrating the construction of REF (reference) from LES (Large-Eddy Simulation)

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图 2 模式积分4小时后PBL（Planetary Boundary Layer）方案及LES（黑色实线）的平均位温垂直廓线

Figure 2. Vertical profiles of domain-averaged potential temperature after 4 h integration simulated by PBL (Planetary Boundary Layer) schemes and LES. The black solid lines indicate results from LES

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图 3 模式积分4小时后PBL方案及LES（黑色实线）的平均位温梯度垂直廓线

Figure 3. Vertical profiles of domain-averaged potential temperature gradient after 4 h integration simulated by PBL schemes and LES. The black solid lines indicate results from LES

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图 4 模式积分4小时后PBL方案（彩色）与参考湍流场（灰色）总热通量垂直廓线

Figure 4. Vertical profiles of total heat fluxes simulated by PBL schemes (colored lines) and from REF (grey lines) after 4 h integration

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图 5 模式积分4小时后PBL方案的总热通量相对误差随均一化水平网格距的变化

Figure 5. Relative errors of the total heat fluxes simulated by PBL schemes as a function of Δx/z_i after 4 h integration

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图 6 模式积分4小时后PBL方案（红、蓝点线）与REF（红、蓝实线）在混合层内网格（红色）与次网格（蓝色）热通量的比例随均一化水平网格距的变化

Figure 6. Ratios of the resolved-scale heat fluxes (REF: red solid lines; PBL: red dotted lines) and sub-grid heat fluxes (REF: blue solid lines; PBL: blue dotted lines) to the total against the dimensionless mesh in the mixing layer after 4 h integration

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图 7 模式积分4小时后PBL方案及REF在Δ=500 m时z=0.1z_i位温扰动（上）及垂直速度（下）的水平分布

Figure 7. Horizontal distributions of perturbation of potential temperature (θ', top panel) and vertical velocity (w, bottom panel) at z=0.1z_i with grid interval of Δ=500 m after 4 h integration simulated by PBL schemes and REF

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图 8 模式积分4小时后PBL方案（彩色）与REF（灰色）次网格热通量垂直廓线

Figure 8. Vertical profiles of sub-grid heat fluxes simulated by PBL schemes (colored lines) and from REF (grey lines) after 4 h integration

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图 9 YSU（上）和MYNN3（下）方案的（a、c）局地次网格和（b、d）非局地次网格热通量垂直廓线

Figure 9. Vertical profiles of (a, c) local and (b, d) nonlocal sub-grid heat fluxes simulated by YSU (top panel) and MYNN3 (bottom panel) schemes

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图 10 z=500 m处可分辨湍流动能的时间序列。PBL方案积分8小时，LES积分4小时

Figure 10. Time series of resolved-scale turbulent kinetic energy (TKE) at z=500 m. PBL schemes are integrated for 8 hours. LES simulation covers a period of four hours

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图 11 PBL方案积分1小时与8小时后的区域平均位温垂直廓线

Figure 11. Vertical profiles of domain-averaged potential temperature after 1 h and 8 h integrations simulated by PBL schemes

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图 12 PBL方案积分（a）1小时与（b）8小时后在z=0.1 z_i处的垂直速度（w）水平分布

Figure 12. orizontal distributions of vertical velocity (w) at z=0.1 z_i from simulations of YSU, MYJ, MYNN2.5, and MYNN3 schemes after (a) 1 h and (b) 8 h integrations simulated by PBL schemes

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图 13 YSU敏感性试验中z=100 m处可分辨湍流动能的时间序列

Figure 13. Time series of resolved-scale turbulent kinetic energy at z=100 m from YSU sensitivity experiments

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图 14 模式积分4小时后Δ=500 m的PBL方案及LES的平均位温垂直廓线

Figure 14. Vertical profiles of domain-averaged potential temperature simulated by PBL schemes and LES (black solid line) at Δ=500 m after 4 h integration

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图 15 模式积分4小时后Δ=500 m的PBL方案与REF（a）总热通量、（b）次网格、（c）网格热通量垂直廓线

Figure 15. Vertical profiles of (a) total, (b) sub-grid, and (c) resolved-scale heat fluxes simulated by PBL schemes and from REF at Δ=500 m after 4 h integration

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表 1 PBL（Planetary Boundary Layer）试验设计参数（模式层高均为2 km，积分8小时）

Table 1. List of model settings in PBL (Planetary Boundary Layer) test (model depth: 2 km; integration length: 8 h)

湍流参数化方法	Δ_{x, y} / m	Δ_t/ s	n_z	n_{x, y}
LES(Large-Eddy Simulation)	50	0.2	100	600
PBL(LYSU, MYJ, MYNN2.5, MYNN3)	250	1	100	360
	500	2	100	180
	1000	4	100	180
	3000	10	100	180
	9000	30	100	180
注：Δ_{x, y}为水平网格距，Δ_t为时间步长，n_z为垂直方向格点数，n_{x, y}为水平方向格点数。

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表 2 Δ=500 m时各PBL方案近地层及浮力特征值

Table 2. Summary of surface and bulk PBL parameters when distance of model grid (Δ) is 500 m

方案	w_*/ m s^-1	u_*/m s^-1	z_i/ m	ζ	R_E	R
REF	2.08	0.50	1160	-28.55	-0.24	-
YSU	2.06	0.58	1140	-18.27	-0.25	0.36
MYJ	2.03	0.53	1080	-22.85	-0.12	1.13
MYNN2.5	2.05	0.54	1120	-21.41	-0.19	-0.01
MYNN3	2.03	0.56	1080	-18.57	-0.14	0.50
注：w_为对流特征速度，u_为地表摩擦速度，z_i边界层高度，R为混合层总热通量相对误差，无量纲数$\zeta ={z_i}/L$（其中，L为奥布霍夫长度），夹卷率${R_E}={\left\langle {w'\theta '} \right\rangle _{{z_i}}}/{\left\langle {w'\theta '} \right\rangle _{{\rm{SFC}}}}$为边界层高度容量与地面热通量之比。

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表 3 YSU敏感性试验设计

Table 3. List of parameters used in YSU sensitivity experiments

试验名	边界层参数化方案	Δ / m	负梯度项倍数	夹卷项倍数	运行时间
CRTL 试验	YSU	1000	1	1	8
2CT (Counter-gradient Term) 试验	YSU	1000	2	0	8
1CT 试验	YSU	1000	1	0	8
0CT 试验	YSU	1000	0	0	8

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