A review of recent studies on wind resource projections under climate change

This review analyzed 75 studies published 2017-2021 investigating future wind resource evolution. It provides comprehensive information on the studies' specifications and globally summarizes the reported wind resource changes. The studies show substantial differences in design, limiting their comparability. Most studies evaluated a small number of regional climate models driven by general circulation models from CMIP5 under the worstcase scenario RCP8.5. The use of worst-case scenarios can be justified, intending to study climate change impacts for the most significant climate change signal. To quantify the differences between present and future resources, very short evaluation periods with average durations of 23.8 and 24.9 years were used. Our analysis reveals that the availability and distribution of wind resources would likely change in the future. The changes' magnitudes are usually greatest under the most pessimistic climate change scenarios. The direction of the changes varies spatially. The strongest wind resource decline was observed in the Western United States. Declining wind resources are likely in most parts of the northern hemisphere. For southern Brazil, a distinct wind resource increase is projected. For the design of future studies, it is recommended to use (1) the more realistic climate change scenarios SSP245, SSP460, and SSP370, (2) multi-model ensembles, which allow testing the statistical significance of the detected changes, (3) longer investigation periods (>= 30 years) to reinforce the climate change relevance of the statements made.

Automated summary

This review analyzed 75 studies published between 2017 and 2021, investigating the future evolution of wind resources. The studies showed that the availability and distribution of wind resources are likely to change in the future, with the greatest changes observed under the most pessimistic climate change scenarios. It is recommended for future studies to use more realistic climate change scenarios, multi-model ensembles, and longer investigation periods.