Climate change impacts on wind power generation

Pryor, Sara C.; Barthelmie, R.J.; Bukovsky, Melissa; Leung, L. Ruby; Sakaguchi, Kôichi

doi:10.1038/s43017-020-0101-7

Cited by 186 publications

(108 citation statements)

References 162 publications

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“…In line with our results, Pryor et al (2020) have argued in a recent review that natural wind variability dominates over forced changes due to anthropenic climate change. They further argue that the attribution of wind speed changes based on comparing a relatively short time period is substantially complicated by low-frequency climate variability and report that it is currently unclear whether future climate change will lead to further stilling or increased windiness.…”

supporting

confidence: 93%

“…In the wider context of climate change impacts on wind energy, our results using the 1%CO 2 experiment support early conceptual arguments that global warming would reduce wind speeds through a reduction of meridional pressure gradients following increased warming at the poles relative to mid-and low latitudes (e.g., Klink, 2007). In non-idealized systems, however, current best knowledge suggests that there are so many interacting and competing processes that it is "unknown whether anthropogenic warming will result in stilling (decreases in wind speed) or increased windiness" (Pryor et al, 2020).…”

mentioning

confidence: 58%

“…To meaningfully compare with observations and prior work, we investigate 10m wind speeds. So far, climate change impacts on wind energy were usually computed based on extrapolated near surface winds (e.g., Pryor et al, 2020;Schlott et al, 2018;Tobin et al, 2016;Karnauskas et al, 2018;Wohland et al, 2017) using logarithmic or power law relationships (Emeis, 2018).…”

Section: Methodsmentioning

confidence: 99%

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Wind speed stilling and its recovery due to internal climate variability

Wohland¹,

Folini²,

Pickering³

2021

Preprint

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Abstract. Near-surface winds affect many processes on planet Earth, ranging from fundamental biological mechanisms such as pollination to man-made infrastructure that is designed to resist or harness wind. The observed systematic wind speed decline up to around 2010 (stilling) and its subsequent recovery have therefore attracted much attention. While this sequence of downward and upwards trends and good connections to well established modes of climate variability suggest that stilling could be a manifestation of multidecadal climate variability, a systematic investigation is currently lacking. Here, we use the Max Planck Institute Grand Ensemble (MPI-GE) to decompose internal variability from forced changes in wind speeds. We report that wind speed changes resembling observed stilling and its recovery are well in line with internal climate variability, both under current and future climate conditions. Moreover, internal climate variability outweighs forced changes in wind speeds on 20 year timescales by one order of magnitude. Albeit smaller, forced changes become relevant in the long run as they represent alterations of mean states. In this regard, we reveal that land use change plays a pivotal role in explaining MPI-GE ensemble mean wind changes in the representative concentration pathways 2.6, 4.5, and 8.5. Our results demonstrate that multidecadal wind speed variability is of greater relevance than forced changes over the 21st century, in particular for wind related infrastructure like wind energy.

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supporting

confidence: 93%

mentioning

confidence: 58%

Section: Methodsmentioning

confidence: 99%

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Wind speed stilling and its recovery due to internal climate variability

Wohland¹,

Folini²,

Pickering³

2021

Preprint

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“…The spatial resolution is almost double that of MERRA as is the number of vertical levels [36]. Wind speeds are provided at 100 m which is relevant for the wind industry [37]. ERA5 assimilates an unprecedented range of in situ and remote sensing observations and generates a wide array of output fields [38].…”

Section: Era5mentioning

confidence: 99%

Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas

et al. 2021

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The Outer Continental Shelf along the U.S. east coast exhibits abundant wind resources and is now a geographic focus for offshore wind deployments. This analysis derives and presents expected extreme wind and wave conditions for the sixteen lease areas that are currently being developed. Using the homogeneous ERA5 reanalysis dataset it is shown that the fifty-year return period wind speed (U50) at 100 m a.s.l. in the lease areas ranges from 29.2 to 39.7 ms−1. After applying corrections to account for spectral smoothing and averaging period, the associated pseudo-point U50 estimates are 34 to 46 ms−1. The derived uncertainty in U50 estimates due to different distributional fitting is smaller than the uncertainty associated with under-sampling of the interannual variability in annual maximum wind speeds. It is shown that, in the northern lease areas, annual maximum Swind speeds are generally associated with intense extratropical cyclones rather than cyclones of tropical origin. Extreme wave statistics are also presented and indicate that the 50-year return period maximum wave height may substantially exceed 15 m. From this analysis, there is evidence that annual maximum wind speeds and waves frequently derive from the same cyclone source and often occur within a 6 h time interval.

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“…Overall, we think that incorporating wind dispersal into metacommunity studies can yield interesting results for many groups of organisms (e.g., from passive dispersers like diatoms to active dispersers like flying insects) and can help to explain biodiversity patterns at regional and global scales. This might become especially relevant in the context of climate change, which is already affecting global wind patterns (Kling & Ackerly, 2020; Pryor et al., 2020).…”

Section: Discussionmentioning

confidence: 99%

Blowin’ in the wind: Wind directionality affects wetland invertebrate metacommunities in Patagonia

Epele

Santos

Sarremejane

et al. 2021

Global Ecol Biogeogr

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Aim To assess the relative importance of wind intensity and direction in explaining wetland invertebrate metacommunity organization. Location Seventy‐eight wetland ponds in Patagonia (Argentina) covering a study area of 3.5 × 105 km2. Time period Ponds were sampled once between 2006 and 2014. Major taxa studied One hundred and fifty‐eight taxa of wetland aquatic invertebrates. Methods We generated two beta diversity matrices (based on flying and non‐flying invertebrates) and six predictor matrices, including three environmental distance matrices, a topographic distance between ponds, and two wind pairwise matrices differing in wind speed. Using Moran spectral randomization of Mantel (MSR‐Mantel) tests (which account for spatial autocorrelation), we assessed the relationship between the response and the predictor matrices. We used a network‐constrained version of the nestedness metric based on overlap and decreasing fill (NODF), to assess if wind anisotropy (i.e., direction‐dependent) affected community nestedness among ponds. Results Flying dispersers’ dissimilarity was significantly explained by environmental variables, whereas non‐flying invertebrates’ dissimilarity was not significantly explained by any of the distances tested. When wind direction was ignored, wind speed had a negligible effect on both types of communities, whereas when it was considered a consistent nested pattern emerged, with the eastern ponds (downwind) communities being subsets of those from the western ponds (upwind). Main conclusions We found that the invertebrate communities were mainly assembled by a combination of environmental factors and wind directionality, although this depended on the dispersal ability of the organisms.

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Climate change impacts on wind power generation

Cited by 186 publications

References 162 publications

Wind speed stilling and its recovery due to internal climate variability

Wind speed stilling and its recovery due to internal climate variability

Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas

Blowin’ in the wind: Wind directionality affects wetland invertebrate metacommunities in Patagonia

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