Impacts of Climate Change on Global Wind Resources in a CMIP5 Ensemble

The planning and implementation of global wind energy resources are being conducted in the context of today’s climate. However, as anthropogenic greenhouse gas emissions continue to modify Earth’s energy balance and global atmospheric circulation, future changes in the near–surface climate should be considered to maximize the power generating potential of available wind energy technology (i.e., wind farms). We investigate large–scale changes in potential wind power across the globe in response to high and low future emissions scenarios by applying an industry wind turbine power curve to the future simulations of an ensemble of 10 fully coupled global climate models (GCMs) associated with the Coupled Model Intercomparison Project Phase 5 (CMIP5). We consider not only changes in wind speed but those in air density as well.

At the planetary scale, our calculations reveal strong hemispheric asymmetry of future changes in potential wind power, involving decreases across the Northern Hemisphere midlatitudes and increases across the tropics and Southern Hemisphere subtropics. The changes across the northern midlatitudes are robust responses at both mid-21^st century and late 21^st century time periods and in both high and low emissions scenarios, whereas the Southern Hemisphere changes appear critically sensitive to emissions scenario.

Amid these planetary scale patterns are regional variations of substantial magnitude including, for example, a roughly 15–20% decrease over the U.S. Great Plains and upper Midwest, ~10–30% increase over eastern Brazil, and ~5–40% increase over northeastern Australia at 2080–2100 (where ranges given are due to emissions uncertainty). These patterns are largely explainable through simple diagnostic fields that reveal the effect of a reduced midlatitude zonal mean meridional temperature gradient (driving the northern midlatitude decrease) and enhanced land-sea thermal gradients (driving the tropical and southern subtropical increases).

While the relatively coarse spatial and temporal resolution of the models upon which these projections are made may not allow high-fidelity predictions of wind resource that would be required for localized wind farm siting, this investigation does highlight areas around the globe where more refined investigations with downscaling can lend critical insight into the likely impacts of climate change on wind resources. Further, because the relatively coarse spatial and temporal resolution of GCMs may not fully capture important variability in wind resources, we also quantify uncertainty in these estimates. The applicability of these results to the local scale is thus addressed using several years of hourly data from tall towers in both flat and complex terrain in North America as well as atmospheric reanalysis data.