Journal
CLIMATE DYNAMICS
Volume 54, Issue 3-4, Pages 2511-2531Publisher
SPRINGER
DOI: 10.1007/s00382-020-05125-5
Keywords
Wind energy; Climate change; Variable-resolution climate modeling; Clustering
Categories
Funding
- California Energy Commission under the Electric Program Investment Charge Grant [EPC-15-068]
- U.S. Department of Energy (DOE) under Lawrence Berkeley National Laboratory [DE-AC02-05CH11231]
- National Institute of Food and Agriculture, U.S. Department of Agriculture, hatch project under California Agricultural Experiment Station project [CA-D-LAW-2203-H]
- Department of Energy Office of Science [DE-SC0016605]
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Wind energy production is expected to be affected by shifts in wind patterns that will accompany climate change. However, many questions remain on the magnitude and character of this impact, especially on regional scales. In this study, clustering is used to group and analyze large-scale wind patterns in California using model simulations from the variable-resolution Community Earth System Model (VR-CESM). Specifically, simulations have been produced that cover historical (1980-2000), mid-century (2030-2050), and end-of-century (2080-2100) time periods. Once clustered, observed changes to wind patterns can be analyzed in terms of both the change in frequency of those clusters and changes to winds within-clusters. Statistically significant capacity factors changes have been found at all five wind plant sites. Decomposition of the capacity factor changes into frequency changes and within-cluster changes enables a better understanding of their drivers. A further examination of the synoptic-scale fields associated with each cluster then provides a better understanding of how changes to large-scale meteorological fields are important for driving changes in localized wind speeds.
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