Time Evolution and Diurnal Variability of the Parametric Sensitivity of Turbine‐Height Winds in the MYNN‐EDMF Parameterization

Abstract

The Mellor‐Yamada‐Nakanishi‐Niino (MYNN) parameterization applied in the Weather Research and Forecasting (WRF) model has been augmented to include the Eddy‐Diffusion Mass‐Flux (EDMF) approach to better represent transport by boundary‐layer eddies. This change includes the addition of new parameters associated with convective updrafts and boundary‐layer clouds that lead to new parametric sensitivities in the turbine‐height wind speed compared to simulations using the standard MYNN parameterization. This work builds on efforts focused on WRF's MYNN parameterization by examining the sensitivity of wind speed to parameters in the MYNN‐EDMF parameterization as a function of simulation duration. Summer and winter periods were selected from the second Wind Forecast Improvement Project (WFIP2). Five sets of simulations were completed for each season, with durations ranging from 2 to 6 days. The results show that the sensitivity to the new parameters associated with the EDMF scheme is generally small compared to other parameters in clear conditions, but the sensitivity to the entrainment becomes significant when the updraft fraction is large. The spread in the perturbed parameter ensembles was found to grow quickly over the first 8–19 h in the summer simulations and 17–24 h in the winter simulations with little change after that, regardless of the simulation length. A strong diurnal cycle in the parameter sensitivity was also found associated with the atmospheric stability, as well as an increase in the sensitivity to the entrainment parameter used in the EDMF parameterization that is associated with increasing fractional area covered by plumes.

Local thermal gradient and large-scale circulation impacts on turbine-height wind speed forecasting over the Columbia Basin

“…The model simulations capture the wind ramp event, but the simulated increase in wind speed is smaller and occurs later than is observed. The underestimation also exists in our previous study using a small domain for the same location and period but is smaller in magnitude than the current analysis (Berg et al, 2021). Therefore, we assume that forecasting uncertainties from the outer domain may cause underestimation of the wind speed.…”

“…In the second case, August 21-22, 2016, a synoptic-scale cold frontal passage was observed in the CRB, driving cross-barrier flows over the Cascade Mountain Range. This period was marked by a wind ramp event with a maximum speed reaching 14 m s -1 in the CRG (Berg et al, 2021). We denote it hereafter as the cold-front case.…”

“…resolution, model physics, initial/boundary conditions, and parameterizations of the sub-grid processes (e.g., Yang et al, 2013Yang et al, , 2017Yang et al, , 2019Qian et al, 2015;Siuta et al, 2017a;Berg et al, 2019Berg et al, , 2021Smith and Ancell, 2019), which ultimately influences forecasts of wind power (Banta et al, 2013(Banta et al, , 2018. The uncertainties associated with the model initialization decreases the reliability of the deterministic forecasts and can have serious financial consequences (Marquis et al, 2011).…”

“…Sharp wind ramps are frequently associated with a strong thermally driven gradient, with the total aggregated normalized power generation fluctuating from near zero to 100% (Wilczak et al, 2019). The local thermal gradient-induced diurnal wind patterns are often interrupted by synoptic-scale systems, such as strong cold-fronts (Sharp and Mass, 2004), leading to strong wind ramps (Berg et al, 2021). The combined effects of various weather systems and a general lack of observations over the Pacific Ocean increase the complexity of wind forecast and make the forecasting errors sensitive to the atmospheric ICs over the Pacific Northwest.…”

Characteristics of a pre-monsoon dryline atmospheric boundary layer over the rain shadow region: A case study

“…In addition, the retrieval algorithm is augmented with the threshold method during the nonsunshine hours. ABLH retrievals are further evaluated considering the growth rate of the ABL as suggested by Rey-Sanchez et al (2021). The ABLH retrieval algorithm has been validated against the MWRP-based ABLH estimates and the correlation coefficient was found to be 0.87 (R 2 ) between these two independent measurements.…”