GSTDTAP  > 气候变化
DOI10.1029/2018JD029691
Parametric and Structural Sensitivities of Turbine-Height Wind Speeds in the Boundary Layer Parameterizations in the Weather Research and Forecasting Model
Yang, Ben1,2; Berg, Larry K.2; Qian, Yun2; Wang, Chen2,3; Hou, Zhangshuan2; Liu, Ying2; Shin, Hyeyum Hailey4,5; Hong, Songyou6; Pekour, Mikhail2
2019-06-27
发表期刊JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
ISSN2169-897X
EISSN2169-8996
出版年2019
卷号124期号:12页码:5951-5969
文章类型Article
语种英语
国家Peoples R China; USA; South Korea
英文摘要

Structural and parametric problems associated with physical parameterizations are often tied together in weather and climate models. This study examines the sensitivities of turbine-height wind speeds to structural and parametric uncertainties associated with the planetary boundary layer (PBL) parameterizations in the Weather Research and Forecasting model over an area of complex terrain. The sensitivity analysis is based on experiments from two perturbed parameter ensembles using the Mellor-Yamada-Nakanishi-Niino (MYNN) and Yonsei University (YSU) PBL schemes, respectively. In each scheme, most of the intermember variances can be explained by a few parameters. Compared to the YSU parameters, the MYNN parameters induce relatively weaker (stronger) impacts on wind speeds during daytime (nighttime). The two schemes can overall reproduce the observed diurnal features of turbine-height wind speeds. Differences in the daytime wind speeds are evident between the two ensembles. The daytime biases exist even with well-tuned parameter values in MYNN, indicating the structural error. The YSU scheme better matches monthly mean daytime observations, partly due to the compensation among the biases in different wind strengths. Compared to YSU, MYNN generally better agrees with observations in both weak and strong wind conditions. However, the improvements accomplished for one condition by parameter tuning may degrade model performances for others, suggesting the relationships that link different conditions are not accurately represented in the parameterizations. Simulated biases due to structural errors are further identified by evaluating them for different time of day and locations. Ultimately, this study improves understanding of structural limitations in the PBL schemes and provides insights on further parameterization development.


英文关键词parametric sensitivity structural uncertainty PBL parameterization turbine-height wind speeds WRF
领域气候变化
收录类别SCI-E
WOS记录号WOS:000477800000003
WOS关键词TURBULENCE CLOSURE-MODEL ; FLUX-PROFILE RELATIONSHIPS ; YAMADA LEVEL-3 MODEL ; VERTICAL DIFFUSION ; SUMMER MONSOON ; SIMULATION ; ATMOSPHERE ; ENERGY ; IMPACT ; SCHEME
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/184156
专题气候变化
作者单位1.Nanjing Univ, Sch Atmospher Sci, CMA NJU Joint Lab Climate Predict Studies, Nanjing, Jiangsu, Peoples R China;
2.Pacific Northwest Natl Lab, Richland, WA 99352 USA;
3.Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing, Peoples R China;
4.UCAR, Cooperat Programs Adv Earth Syst Sci, Princeton, NJ USA;
5.NOAA, Geophys Fluid Dynam Lab, Princeton, NJ USA;
6.Korea Inst Atmospher Predict Syst, Seoul, South Korea
推荐引用方式
GB/T 7714
Yang, Ben,Berg, Larry K.,Qian, Yun,et al. Parametric and Structural Sensitivities of Turbine-Height Wind Speeds in the Boundary Layer Parameterizations in the Weather Research and Forecasting Model[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2019,124(12):5951-5969.
APA Yang, Ben.,Berg, Larry K..,Qian, Yun.,Wang, Chen.,Hou, Zhangshuan.,...&Pekour, Mikhail.(2019).Parametric and Structural Sensitivities of Turbine-Height Wind Speeds in the Boundary Layer Parameterizations in the Weather Research and Forecasting Model.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,124(12),5951-5969.
MLA Yang, Ben,et al."Parametric and Structural Sensitivities of Turbine-Height Wind Speeds in the Boundary Layer Parameterizations in the Weather Research and Forecasting Model".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 124.12(2019):5951-5969.
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