Wind Resource Assessment in the Southern Plains of the US: Characterizing Large-Scale Atmospheric Circulation with Cluster Analysis

Abstract

Abstract:A new approach for wind resource assessment in the Southern Plains of the US is proposed here. This new approach establishes the baseline frequency of occurrence of large-scale atmospheric circulations (weather regimes) by cluster analysis, using 38-yr NCEP-NCAR reanalysis daily data from 1979-2016. These baseline frequency values can help quantify the departure of wind resource from the long-term mean for a given month. In specific, two scenarios featuring favorable and unfavorable wind energy productions in the Callahan Divide Energy Center of Texas, US, are evaluated by the new approach of wind resource assessment in details. For the favorable scenario, it is found that the jet stream is configured to enhance the southwesterly flow over the Southern Plains, with a frequency of occurrence being nearly three times of the baseline frequency, whereas for the unfavorable scenario, the jet stream is found to suppress the low-level jet over the Southern Plains, with a frequency of occurrence being more than twice the baseline frequency. Hence, the new approach is proven to provide an objective and more efficient way in conducting wind resource assessment.

Offshore wind resource assessment by characterizing weather regimes based on self-organizing map

“…Previous studies used large-scale atmospheric circulation patterns such as North Atlantic Oscillation, and the East Atlantic and Scandinavian modes to assess wind resources (Brayshaw et al 2011, Zubiate et al 2017. Detailed WRs using extended classification or cluster method are capable of capturing characteristics of surface weather systems with more details (Cradden and McDermott 2018, Dong 2018, Millstein et al 2019, Bloomfield et al 2020. Other studies have contributed with insight into the meteorological effects on wind resource characteristics, such as ramp events (Ohba et al 2016, 2022, Bloomfield et al 2018, regional imbalance in wind power (Gibson et al 2015), and spatial planning with the guide of WRs (Grams et al 2017).…”

Skillful seasonal prediction of wind energy resources in the contiguous United States

“…Wind energy provides a renewable and clean energy source that does not directly produce greenhouse gas emissions or air pollutants, so it plays a crucial role in the transition to a sustainable and low-carbon energy system and helps mitigate climate change by reducing the dependence on fossil fuels 1 . One challenge that remains, however, is that wind power availability is highly variable on multiple time scales ranging from day-to-day weather patterns [2][3][4][5] , seasonal-interannual large-scale modes of variability [6][7][8][9][10] , and up to centennial climate changes 11,12 . In the United States, with the steady increase of wind energy production over the last 20 years 13 , the latest U.S. Wind Turbine Database up to May 2023 contains 72,732 turbines with a total rated capacity of 142,435 megawatts 14 .…”

“…These climate patterns can contribute to seasonal variations in wind energy by altering atmospheric circulation and wind speed patterns, thus producing potential predictability sources of wind energy. Skillful seasonal predictions of jet stream and extratropical storm tracks, which strongly modulate interannual variability of wind energy resources over CONUS 3,6,7 , have been achieved mainly via the ENSO teleconnection in state-of-the-art dynamical seasonal prediction system multiple months in advance [22][23][24][25] . Thus, there may exist emerging opportunities in seasonal prediction of wind energy over CONUS.…”

“…regions (Fig. 1a, c), in which air masses from north and south sweeping over the relatively flat and smooth terrain 27 , interacting with the Rocky Mountain terrain forcing 28 , seasonal jet stream 3,29,30 (Supplementary Fig. S1) and extratropical storm tracks (Supplementary Fig.…”