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Title: Parametric and Structural Sensitivities of Turbine‐Height Wind Speeds in the Boundary Layer Parameterizations in the Weather Research and Forecasting Model

Abstract

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 inter-member 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 themore » 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.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [4];  [5]; ORCiD logo [2]
  1. CMA‐NJU Joint Laboratory for Climate Prediction Studies, School of Atmospheric SciencesNanjing University Nanjing China, Pacific Northwest National Laboratory Richland WA USA
  2. Pacific Northwest National Laboratory Richland WA USA
  3. Pacific Northwest National Laboratory Richland WA USA, College of Global Change and Earth System Science, Beijing Normal University Beijing China
  4. UCAR/Cooperative Programs for the Advancement of Earth System Science and NOAA/Geophysical Fluid Dynamics Laboratory Princeton NJ USA
  5. Korea Institute of Atmospheric Prediction Systems Seoul South Korea
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1560172
Alternate Identifier(s):
OSTI ID: 1560173; OSTI ID: 1562917
Report Number(s):
[PNNL-SA-142837]
[Journal ID: ISSN 2169-897X]
Grant/Contract Number:  
[AC07‐76RL01830; AC05-76RL01830]
Resource Type:
Published Article
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
[Journal Name: Journal of Geophysical Research: Atmospheres Journal Volume: 124 Journal Issue: 12]; Journal ID: ISSN 2169-897X
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; parametric sensitivity; structural uncertainty; pbl parameterization; turbine-height wind speed; WRF

Citation Formats

Yang, Ben, Berg, Larry K., Qian, Yun, Wang, Chen, Hou, Zhangshuan, Liu, Ying, Shin, Hyeyum Hailey, Hong, Songyou, and Pekour, Mikhail. Parametric and Structural Sensitivities of Turbine‐Height Wind Speeds in the Boundary Layer Parameterizations in the Weather Research and Forecasting Model. United States: N. p., 2019. Web. doi:10.1029/2018JD029691.
Yang, Ben, Berg, Larry K., Qian, Yun, Wang, Chen, Hou, Zhangshuan, Liu, Ying, Shin, Hyeyum Hailey, Hong, Songyou, & Pekour, Mikhail. Parametric and Structural Sensitivities of Turbine‐Height Wind Speeds in the Boundary Layer Parameterizations in the Weather Research and Forecasting Model. United States. doi:10.1029/2018JD029691.
Yang, Ben, Berg, Larry K., Qian, Yun, Wang, Chen, Hou, Zhangshuan, Liu, Ying, Shin, Hyeyum Hailey, Hong, Songyou, and Pekour, Mikhail. Mon . "Parametric and Structural Sensitivities of Turbine‐Height Wind Speeds in the Boundary Layer Parameterizations in the Weather Research and Forecasting Model". United States. doi:10.1029/2018JD029691.
@article{osti_1560172,
title = {Parametric and Structural Sensitivities of Turbine‐Height Wind Speeds in the Boundary Layer Parameterizations in the Weather Research and Forecasting Model},
author = {Yang, Ben and Berg, Larry K. and Qian, Yun and Wang, Chen and Hou, Zhangshuan and Liu, Ying and Shin, Hyeyum Hailey and Hong, Songyou and Pekour, Mikhail},
abstractNote = {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 inter-member 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.},
doi = {10.1029/2018JD029691},
journal = {Journal of Geophysical Research: Atmospheres},
number = [12],
volume = [124],
place = {United States},
year = {2019},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
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DOI: 10.1029/2018JD029691

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