16.2 Parametric and Structural Sensitivities of Turbine‐Height Wind Speeds in the Weather Research and Forecasting Model

Thursday, 16 January 2020: 1:45 PM
256 (Boston Convention and Exhibition Center)
Yun Qian, PNNL, Richland, WA; and B. Yang, L. K. Berg, C. Wang, Z. Hou, Y. Liu, H. Shin, S. Y. Hong, and M. Pekour

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.
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