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

Ye Liu,Yun Qian,Larry K Berg

doi:10.5194/wes-7-37-2022

Abstract

Abstract. We investigate the sensitivity of turbine-height wind speed forecast to initial condition (IC) uncertainties over the Columbia River Gorge (CRG) and Columbia River Basin (CRB) for two typical weather phenomena, i.e., local-thermal-gradient-induced marine air intrusion and a cold frontal passage. Four types of turbine-height wind forecast anomalies and their associated IC uncertainties related to local thermal gradients and large-scale circulations are identified using the self-organizing map (SOM) technique. The four SOM types are categorized into two patterns, each accounting for half of the ensemble members. The first pattern corresponds to IC uncertainties that alter the wind forecast through a modulating weather system, which produces the strongest wind anomalies in the CRG and CRB. In the second pattern, the moderate uncertainties in local thermal gradient and large-scale circulation jointly contribute to wind forecast anomaly. We analyze the cross section of wind and temperature anomalies through the gorge to explore the evolution of vertical features of each SOM type. The turbine-height wind anomalies induced by large-scale IC uncertainties are more concentrated near the front. In contrast, turbine-height wind anomalies induced by the local IC thermal uncertainties are found above the surface thermal anomalies. Moreover, the wind forecast accuracy in the CRG and CRB is limited by IC uncertainties in a few specific regions, e.g., the 2 m temperature within the basin and large-scale circulation over the northeast Pacific around 140∘ W.

Highlights

Renewable energy has become an alternative to fossil fuels in the last few decades (Al-Dousari et al, 2019), and windgenerated electricity has seen growth worldwide (Shaw et al, 2019)
To successfully manage wind energy, it is of immense importance to accurately forecast the power supplied to the power grid (Siuta et al, 2017a), which relies on the performance of numeral weather prediction (NWP) models in representing the flow features (Siuta et al, 2017b; Willis et al, 2018; Smith and Ancell, 2019)
This study aims to (1) assess the sensitivity of turbineheight wind speed forecasts in the Columbia River Gorge (CRG) and Columbia River Basin (CRB) to initial condition (IC) uncertainties related to local thermal conditions and large-scale circulations and (2) identify the regions of IC uncertainties which have the largest influence on wind forecast

Summary

Introduction

Renewable energy has become an alternative to fossil fuels in the last few decades (Al-Dousari et al, 2019), and windgenerated electricity has seen growth worldwide (Shaw et al, 2019). To successfully manage wind energy, it is of immense importance to accurately forecast the power supplied to the power grid (Siuta et al, 2017a), which relies on the performance of numeral weather prediction (NWP) models in representing the flow features (Siuta et al, 2017b; Willis et al, 2018; Smith and Ancell, 2019). The performance of NWP models is sensitive to resolution, model physics, initial/boundary conditions, and parameterizations of the sub-grid processes (e.g., Yang et al, 2013, 2017, 2019; Qian et al, 2015; Siuta et al, 2017a; Berg et al, 2019, 2021; Smith and Ancell, 2019; Xia et al, 2021), which influences forecasts of wind power (Banta et al, 2013, 2018). In an operational mesoscale model, the initial conditions (ICs) are frequently

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