Identification of reliable locations for wind power generation through a global analysis of wind droughts

Wind power is a critical low-carbon resource expected to contribute a substantial share of global electricity by mid-century, but its variability can stress power systems. Prolonged periods of low wind speeds—"wind droughts"—have already caused notable system impacts in regions like Northwestern Europe (summer–autumn 2021), the Western and Southern United States (2015), and India (2020). Energy system planning therefore requires an understanding of the severity, distribution, and temporal trends of wind droughts. Traditional intensity-duration-frequency approaches identify continuous low-wind episodes but can miss the combined effect of consecutive droughts separated by brief normal periods. To address this, the study employs an energy deficit metric integrating deficit depth and duration over annual periods to capture compounded scarcity. The research question is whether recent wind droughts reflect climate variability versus long-term trends, and which regions combine abundant wind with low variability to support reliable wind-centric systems.

Prior work has assessed persistence and frequency of low wind speed events and storage requirements under renewable variability using intensity-duration-frequency analyses, typically finding 10–20 day low-wind events with ~10-year return periods. Studies on climate change impacts indicate possible increases in wind energy potential in Northern Europe and decreases in the Southeast by century’s end, with broader results showing decreased surface winds across northern mid-latitudes and increases in southern tropics/subtropics. However, projections are sensitive to boundary conditions, yielding substantial uncertainty for planners. Over the contiguous U.S., trends toward reduced annual wind speeds have been reported. European wind variability is linked to atmospheric modes like the North Atlantic Oscillation, influencing over- and under-generation relative to seasonal means. Overall, uncertainties in modelled wind changes and the importance of multidecadal variability motivate a historical, observation-constrained analysis using reanalysis.

The study analyzes ERA5 reanalysis data (Copernicus/ECMWF) from 1979–2022 at hourly resolution on a 0.25°×0.25° grid, using 100-m wind components, surface pressure, and 2-m temperature. From wind speed, power density (WPD) is computed hourly as 0.5·p·V^3/(R·T), serving as a proxy for wind resource at turbine hub height. The analysis defines and quantifies: (1) Climatological Seasonal Wind Power Density (CSWPD) by averaging each hour across all years to form a climatological hourly profile; (2) Seasonal variability via an energy deficit metric representing storage needed to convert the normalized climatological seasonal profile into constant output over a year; (3) Weather variability via an energy deficit comparing each year’s normalized hourly WPD to the normalized climatological seasonal hourly profile; (4) Wind drought severity via an energy deficit comparing each year’s hourly WPD (normalized to the year with the lowest mean WPD across the record to emulate a fixed-size system) against the normalized climatological seasonal profile. The energy deficit metric is computed by integrating the generation balance over time, E_deficit(t)=∫(P_target−P_generation) dt over the annual period, after concatenating profiles to avoid edge effects, and taking E_deficit,max as the difference between the maximum and minimum of the integral within the year. Metrics are mapped globally over land and coastal areas (excluding Greenland and Antarctica) and analyzed as percentile ranks for power density (ascending) and variabilities (descending) to identify locations combining high resource and low variability. Trends in annual mean power density, weather variability, and wind drought severity are assessed via linear regression per grid cell; statistical significance is determined with p<0.05. The analysis spans ~400 billion data points per variable (~3 TB total).

- Abundant and reliable regions: The American Midwest, Northeastern Canada, Australia, the Sahara, Argentina, parts of Central Asia and Southern Africa show relatively high mean power densities (commonly 250–500 W/m²) and low seasonal and weather variability, making them favorable for sustained wind generation. - Variability patterns: Europe exhibits relatively high power densities but also higher seasonal variability (often 0.15–0.25 fraction of a year) and higher weather variability, contributing to more frequent and prolonged wind droughts. Weather variability is more uniform globally, with notably low values in parts of Africa and Australia. - Distribution by domain: Over land, most grid cells have mean power density <200 W/m² and seasonal variability deficits 0.04–0.20 (more likely 0.08–0.16). Coastal areas have 200–600 W/m² with seasonal variability broadly 0.04–0.20. Sea/ice regions have highest WPD (300–1500 W/m²), with seasonal variability commonly 0.08–0.12. Weather variability deficits are typically 0.04–0.16. - Composite suitability: Minimum percentile rank across WPD, seasonal variability, and weather variability highlights the American Midwest, Northeastern Canada, Australia, the Sahara, Argentina, Central Asia, and Southern Africa as top regions for both strong and reliable wind resources. Central and Northwestern Europe score lower due to higher variability. - Historical wind droughts: Analyzed over land/coastal areas with mean WPD ≥150 W/m² (covering ~48% of land/coastal extent excluding Greenland/Antarctica), the most severe wind droughts often occurred before significant wind deployment. By continent, the worst years cluster in the late 2000s–2010s in Asia; are more uniformly distributed in North America and Oceania; show notable events in South America in 1985, 1998, 2016; in Africa largely in the 1980s–1990s with a major 2010 event; and in Europe in the 1980s and 2010s (notably 2009–2010). - Event identification: The metric identifies a deeper drought in Northwestern Europe in 2010 than in 2021; extensive droughts in the American Midwest in the 1980s–1990s; India in 2021; and the Western US in 2015. - Severity and probabilities: The most severe droughts occurred in Central Asia, Northwestern Europe, the Mediterranean Sea, and Northern Canada, with energy deficit lengths of up to several weeks (e.g., 2000 h ≈ 12 weeks). Northwestern Europe has a 60–80% probability of experiencing years with >400 h of deficit (~17 days) relative to the climatological target. Lowest probabilities of long droughts occur in the American Midwest, the Sahara, Argentina, and Australia. - Trends (annual percentage change): Power density shows significant positive trends in parts of the Tropics (0.1–3%), Central North America (0.1–1%), Central Africa (0.1–3%), the Amazon (0.3–3%), and the Indian Ocean (0.1–0.3%); negative trends in Central Europe and India (−0.1 to −1%). Weather variability shows little widespread change, with small significant patches in North America (−0.3 to 1%), the Amazon (−0.3 to −3%), Eastern Europe (−0.3 to −3%), and Western Africa (0.3 to 3%). Wind drought severity trends are negative (improving) over tropical oceans (−1 to −10%), Central North America (−1 to −3%), the Amazon (−1 to −10%), and Africa (−1 to −10%); and positive (worsening) in India and Western Africa (1 to 3%). - Extent of significant trends: Among land/coastal areas with mean WPD ≥150 W/m², statistically significant trends occur over 11% (power density), 4% (weather variability), and 7% (wind drought severity). - Planning insight: In many locations, the most severe droughts produce energy deficits 2–3 times larger than typical-year droughts, overshadowing observed trends in severity; historical records are therefore valuable for planning resilient wind-reliant systems.

The study integrates depth and duration of wind scarcity into an annual energy deficit metric to identify regions combining high wind resource with low variability and to assess long-term changes. Findings show that several continental interior and subtropical regions (e.g., American Midwest, Argentina, Australia, Sahara, parts of Central Asia and Southern Africa) offer both abundant and relatively reliable wind resources, whereas Northwestern and Central Europe, despite high power density, exhibit higher weather and seasonal variability, increasing the frequency and severity of wind droughts. The analysis indicates limited widespread trends in weather-driven variability; instead, changes in annual mean wind power density dominate observed trends in drought severity. Importantly, many of the most severe historical wind droughts occurred before large-scale wind deployment, underscoring the utility of long-term reanalysis data for designing robust systems. For system integration, regions like Northwestern Europe may face larger storage or firming needs due to higher wind drought probability, linked to atmospheric modes (e.g., North Atlantic Oscillation). An illustrative example suggests that a 300 GW offshore fleet with a 0.4 capacity factor experiencing a representative 400 h annual deficit would face a ~48 TWh energy shortfall relative to climatology, necessitating substantial storage or complementary generation—orders of magnitude larger than historical cumulative electrochemical storage (~16 GWh by 2021). Overall, the results guide siting, portfolio diversification, and storage planning to mitigate prolonged low-wind periods.

By developing and applying an annual energy deficit metric to 44 years of ERA5 data, the study identifies global regions with both abundant and comparatively reliable wind resources and quantifies the historical prevalence and trends of wind droughts. Key contributions include a combined assessment of seasonal and weather variability, recognition that severe historical droughts often predate large-scale wind deployment, and evidence that trends in mean wind power density typically outweigh changes in weather variability for drought severity. These insights can inform siting of wind projects, storage sizing, and complementary resource planning. Future research should disentangle the roles of natural multidecadal variability versus anthropogenic climate change in regional wind patterns; evaluate spatial aggregation and interconnection benefits across larger balancing areas; incorporate co-planning with solar and demand variability; and refine resource assessments using higher-resolution models and bias-corrected datasets that better capture orography and boundary-layer processes.

- Reanalysis biases: 100-m wind speeds from ERA5 can have biases due to terrain orography, limited assimilated data coverage, and model resolution. - Spatial resolution: 0.25° (~30 km) grid cannot resolve complex topography and sub-grid effects relevant to wind siting. - Temporal resolution: Hourly data do not capture rapid extremes such as gusts that can affect power system stability. - Boundary layer parametrization: Model representation of stability can degrade wind speed accuracy. - Record length: 44 years may not capture multidecadal variability modes, risking misinterpretation of long-term trends. - Multidecadal cycles: Documented multidecadal variability (e.g., in German wind generation) may overlap the analysis period. - Spatial aggregation not modeled: Metrics are computed per grid cell and annual period; benefits of geographic diversity and interconnection are not explicitly captured. - System context: The target profiles are for characterization and do not represent actual demand profiles or integrated resource portfolios; complementarity with solar or other generation and demand-side dynamics is not evaluated.