Effects of a Modified Sub-grid-scale Terrain Parameterization Scheme on the Simulation of Low-layer Wind over Complex Terrain

Liu Yujue; Miao Shiguang; Liu Lei; Hu Fei

doi:10.11898/1001-7313.20190107

Vol.30, NO.1, 2019

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Liu Yujue, Miao Shiguang, Liu Lei, et al. Effects of a modified sub-grid-scale terrain parameterization scheme on the simulation of low-layer wind over complex terrain. J Appl Meteor Sci, 2019, 30(1): 70-81. DOI: 10.11898/1001-7313.20190107.

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Liu Yujue, Miao Shiguang, Liu Lei, et al. Effects of a modified sub-grid-scale terrain parameterization scheme on the simulation of low-layer wind over complex terrain. J Appl Meteor Sci, 2019, 30(1): 70-81. DOI: 10.11898/1001-7313.20190107.

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Effects of a Modified Sub-grid-scale Terrain Parameterization Scheme on the Simulation of Low-layer Wind over Complex Terrain

DOI: 10.11898/1001-7313.20190107

Liu Yujue¹,
Miao Shiguang^{1
,
,},
Liu Lei²,
Hu Fei^2,3

1.
Institute of Urban Meteorology, CMA, Beijing 100089
2.
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
3.
University of Chinese Academy of Sciences, Beijing 100049

Received Date: 2018-05-16
Rev Recd Date: 2018-08-10
Publish Date: 2019-01-31

Abstract

Abstract

Due to the limited representation of observation over complex terrain, high resolution model becomes a favorable tool. Fine numerical simulation of wind field is quite important for micro-siting wind farms and wind energy resources assessment, especially in the complex terrain area. The accuracy of low-layer wind simulation over mountain area is one of the difficulties and key points in the field of wind energy research. The state-of-the-art WRF (Weather Research and Forecasting) model is one of the most widely used mesoscale numerical weather models for wind energy assessment in recent years. However, effects of sub-grid-scale topographic shape on surface wind field are not considered. With the new WRF version 3.4.1, a sub-grid-scale terrain parameterization scheme named Jiménez scheme is added into the YSU (Yonsei University) planet boundary layer parameterization scheme. The Jiménez scheme is designed aiming to reduce the systematic error of wind speed overestimation over valleys or plains and underestimation over hills conversely. However, correction effects of original WRF simulated 10 m wind speed by Jiménez scheme show great differences under different horizontal resolutions, particularly when over high hills. A series of sensitive numerical experiments are carried out under windy days for the Taihang Mountains in the west of Beijing-Tianjin-Hebei area. The main purpose of these experiments is to address some of issues regarding Jiménez scheme and try to solve the existing problems by establishing a relationship between the key topographic parameter C_t and the model grid spacing(dx/dy) to fit different numerical simulation for high resolution based on secondly SRTM topographic dataset. The simulated 10 m wind speed results of WRF without Jiménez scheme, with original Jiménez scheme and modified Jiménez scheme version are compared with observations of 3 automatic weather stations during the MOUNTAOM (MOUNtain Terrain Atmospheric Observations and Modeling) campaign which is prepared for 2022 winter Olympic Games. Results show that the modified Jiménez scheme can partially correct the error of the original Jiménez scheme at lower and higher resolutions. The simulated 10 m wind speed near the ground by modified version is closer to the actual condition. The correction method for Jiménez sub-grid-scale terrain scheme can provide reference for high resolution wind simulations over complex terrain and help users to obtain more detailed information on the surface wind field for wind energy related researches and applications.
- WRF;
- complex terrain;
- sub-grid-scale terrain parameterization scheme;
- fine-resolution simulation

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References(31)

Figures and Tables

图 1 模拟区域和分析区域(填色为地形高度)

(黑框为模拟范围，蓝框为小海坨山所在区域)

Fig. 1 Computational and analytical domains with the terrain elevation (the shadeded denotes terrain)

(black frame denotes simulation domain, blue frame denotes Xiaohaituo mountain)

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图 2 小海坨山地形(填色)

(黑色圆点为自动气象站)

Fig. 2 Analytical domain for Xiaohaituo Mountain (the shaded)

(black dots denote automatic weather stations)

DownLoad: Full-Size Img PowerPoint

图 3 3个个例10 m风速差值集合平均场(填色)(等值线表示地形高度，单位：m)

(a)T1_1与T0_1的差值，(b)T1_2与T0_2的差值，(c)T1_3与T0_3的差值

Fig. 3 Ensenble averaged bias of 10 m wind speed of 3 cases (the shaded)(the contour denotes the terrain height, unit:m)

(a)difference between T1_1 and T0_1, (b)difference between T1_2 and T0_2, (c)difference between T1_3 and T0_3

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Fig. 4 Ensemble averaged daily bias of simulated and observed 10 m wind speed at Xidazhuangke, Erhaituo and Xiaohaituo of T0 and T1 from 3 cases

DownLoad: Full-Size Img PowerPoint

图 5 模拟区域和小海坨山区域不同水平分辨率Δ²h水平分布(填色)

(等值线表示地形高度，单位：m)

Fig. 5 Δ²h distribution of computational domain and Xiaohaituo Mountain with different resolutions (the shaded)(the contour denotes the terrain height, unit:m)

DownLoad: Full-Size Img PowerPoint

图 6 小海坨山区域30个点的分布

(填色表示地形)

Fig. 6 The distribution of 30 points in Xiaohaituo Mountain (the shaded denotes terrain)

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Fig. 7 The corresponding Δ²h values of 30 points at different resolutions

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图 8 3个个例小海坨山区域10 m风速差值集合平均场(填色)(等值线表示地形高度，单位：m)

(a)T1C_1与T1_1差值，(b)T1C_2与T1_2差值，(c)T1C_3与T1_3差值

Fig. 8 Ensenble averaged bias of 10 m wind speed of 3 cases in Xiaohaituo Mountain (the shaded) (the contour denotes the terrain height, unit:m)

(a)difference between T1C_1 and T1_1, (b)difference between T1C_2 and T1_2, (c)difference between T1C_3 and T1_3

DownLoad: Full-Size Img PowerPoint

Fig. 9 Ensemble averaged daily bias of simulated and observed 10 m wind speed at Xidazhuangke, Erhaituo and Xiaohaituo of T1C and T1 from 3 cases

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Table 1 Schemes of different experiments

试验组名称	试验名称	水平分辨率	时间积分步长/s	次网格地形方案
	T0_1	3 km×3 km	18
T0	T0_2	1 km×1 km	6
	T0_3	333 m×333 m	2
	T1_1	3 km×3 km	18	Jiménez方案
T1	T1_2	1 km×1 km	6	Jiménez方案
	T1_3	333 m×333 m	2	Jiménez方案
	T1C_1	3 km×3 km	18	修正Jiménez方案
T1C	T1C_2	1 km×1 km	6	修正Jiménez方案
	T1C_3	333 m×333 m	2	修正Jiménez方案

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Table 2 Statistic results of simulated 10 m wind speed (unit:m·s^-1)

试验	平均偏差			均方根误差
试验	西大庄科站	二海陀站	小海陀站	西大庄科站	二海陀站	小海陀站
T0_1	4.057	-0.411	-1.791	1.860	2.626	3.098
T0_2	1.270	-2.103	-3.955	2.499	2.136	2.473
T0_3	0.744	-1.838	-0.248	1.873	2.850	3.433
T1_1	5.813	1.191	0.420	2.497	2.021	2.458
T1_2	-0.461	1.062	-2.118	1.764	2.042	1.746
T1_3	-0.742	-3.506	-2.598	1.811	3.820	4.108
T1C_1	3.135	-0.588	-0.392	1.776	2.391	2.689
T1C_2	0.055	0.129	-1.200	1.644	1.565	1.591
T1C_3	0.279	-0.639	-0.016	1.300	1.583	1.791

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