Does wind energy extraction have an effect on atmospheric disturbances, global warming and global cooling, and the strengthening of local gradients and synoptic vorticity? What positive and negative effects will wind energy have on the Earth's atmospheric gradients?

Wind contributes to climate balance by transporting heat from warmer to cooler regions. Modern wind turbines extract approximately 40–50% of the kinetic energy from the wind passing through their swept area. This study estimates the thermal impact caused by the energy extraction of wind farms, using the Carnot efficiency model to calculate equivalent thermal energy added to the local atmosphere. Case studies in Southern Spain and the United States suggest that, in regions with small natural temperature gradients, the installation of wind farms could significantly alter local temperatures, potentially enhancing storm risk. Quantitative results support the need for detailed environmental assessments before deploying wind farms in sensitive regions.Wind plays a key role in regulating Earth’s climate by distributing heat across different geographic regions. Wind energy is widely regarded as a clean alternative to fossil fuels, but its physical interaction with the atmosphere may have unintended consequences. Each wind turbine extracts energy from air masses, potentially reducing wind flow and altering local energy balances. This paper evaluates whether the energy extracted by wind farms, when considered through thermodynamic principles, contributes significantly to local heating and possibly weather intensification. Using Carnot efficiency, we estimate the thermal equivalent of wind energy extraction and analyze its implications. 2 Methodology 2.1 Thermodynamics Framework According to Carnot's theorem, the maximum efficiency η of a heat engine operating between two temperatures Th (hot) and Tc (cold), where Tc Pt=Pe/η Where: • Pt is the equivalent thermal power injected into the local climate system. • η is Carnot efficiency, calculated from the temperature difference of the system. Due to the typically small temperature gradient (2–20ºC) between the wind turbine’s air layers and surroundings, the efficiency η is very low, resulting in a multiplication factor ranging from ~15× to ~150×. TEMPERATURE DIFFERENCE (ºC) EFFICIENCY (%) THERMAL MULTIPLIER (×) 2 0.67 149.5 3 1.00 99.8 5 1.66 60.1 7 2.32 43.1 9 2.98 33.6 11 3.62 27.6 15 4.91 20.4 Case Study: Offshore Wind Farm in Fuengirola, Spain To assess the potential thermal effects of wind energy extraction, we analyze a modeled offshore wind farm near Fuengirola (Málaga, southern Spain), where sea temperature and wind conditions are well-documented. Parameters: • Electrical Power Output (Pe): 990 MW (9.90 × 10⁸ W) • Local Temperature Gradient (ΔT): 7°C • Sea Surface Temperature (Th): 25°C (validated by remote sensing studies in the western Mediterranean) [1] • Carnot Efficiency (η): 2.3% • Equivalent Thermal Power (Pt = Pe / η): 42.64 GW • Operating Time: 12 hours (43,200 s) • Thermal Energy Transferred to Atmosphere (Et): 4.28 × 10¹³ J Affected Volume: • Estimated Impact Area: 1,000 hectares = 1.00 × 10⁷ m² [2] • Air Column Height (hub + rotor radius): 270 m • Volume of Affected Air: 2.70 × 10⁹ m³ • Air Density (ρ): 1.168 kg/m³ • Air Mass in Volume: 3.15 × 10⁹ kg • Specific Heat Capacity of Air (c): 1.01 × 10³ J/kg·ºC Interpretation: This theoretical model indicates that a single 12-hour operation of a large-scale wind farm could increase local air temperature within the affected volume by over 13°C, assuming all thermal energy remains confined — a highly simplified upper-limit scenario. This underlines the potential for significant microclimatic change, warranting further environmental modeling and field validation. References [1] La teledetección de la temperatura superficial del mar: una validación de algoritmos en las aguas litorales del Mediterráneo español. Cuadernos de Geografía, Universitat de València. [2] José Quereda’s Lab (data cited on estimated affected area: 1,000 hectares for Fuengirola coastline). 4 Limitations and Area of Influence in the Fuengirola Model The Fuengirola case study represents a simplified upper-bound estimate of local thermal impact from offshore wind farm activity. One key limitation lies in the assumption of a confined volume of 1,000 hectares and a vertical air column of 270 meters. In reality, the affected area may extend far beyond the immediate swept volume due to atmospheric mixing, horizontal advection, and turbulent wake effects generated by the turbines. These aerodynamic wakes can alter airflow patterns, reduce wind speeds downwind, and contribute to thermal retention and recirculation in areas not directly above the turbines Additionally, thermal stratification behind the turbines—especially during stable atmospheric conditions—can increase localized heating, extending both vertically and laterally. These factors suggest that the real-world thermal footprint of wind farms could be larger and more diffuse than estimated in the enclosed model, requiring field data and CFD (computational fluid dynamics) simulations to accurately quantify.Case Study: Hurricane Milton vs. U.S. Wind Energy (2023–24) To contextualize the large-scale thermal impact of wind power, we compare the total wind energy production in the United States during a single year with the kinetic energy of Hurricane Milton — a benchmark for atmospheric energy concentration. Using a simplified cylindrical model, Hurricane Milton reached a diameter of 390 km and a vertical height of 12 km, with winds peaking at 115 mph (51.5 m/s). The estimated mass of the moving air column was approximately 1.76 × 10¹⁵ kg, yielding a kinetic energy of 2.33 × 10¹⁸ J. During 2023–2024, the United States produced approximately 47.7 TWh of wind energy, equivalent to 1.72 × 10¹⁷ J of electrical output. However, due to the low Carnot efficiency at the sea–air interface during hurricane conditions (only ~1.32%), the equivalent thermal energy released into the atmosphere is amplified:This result implies that the climatic thermal disturbance from one year of wind energy in the U.S. is equivalent to the energy of 5.6 hurricanes the size of Milton. This comparison highlights the potential for large-scale wind energy deployment to influence atmospheric energy balances and storm-related risk profiles.Excel table Calculo de la energia del Huracan Milton altura sobre el mar m 12000 diametro en florida m 390000 velocidad (115MPh) m/s 51.5 densidad del aire kg/m3 1.225 masa de aire kg 1.75605E+15 energia huracan Milton 1/2m*v^2 J 2.32874E+18 Temperatura media en Florida durante el Milton ºC 26.5 Temperatura media mar durante el Milton ºC 30.5 eff carnot 1.32% 1/eficiencia 75.9 Cambio climatico producido en USA debido a la eolica energia eolica USA 2023-24 1 año Twh 47.7 J 1.7172E+17 Cambio climatico producido = energia/eficiencia de carnot J 1.30357E+19 Energia eolica/miltons J/J 5.60 Chatgpt verification: Verification complete: Your original calculations for Hurricane Milton’s energy and air mass are accurate. • Air mass: ~1.756 × 10¹⁵ kg • Kinetic energy: ~2.33 × 10¹⁸ J The dimensions (diameter = 390 km, height = 12 km, speed = 115 mph) are plausible for a major hurricane like Milton, and the calculation using a cylindrical volume is acceptable for a first-order estimate.Recommended Study: Thermal Monitoring of Large-Scale Wind Farms To assess the true atmospheric impact of large-scale wind farms, a longitudinal observational study is essential. We propose selecting a wind farm site of significant scale — either under construction or recently built — and conducting atmospheric and thermal measurements during a minimum period of two years before and after installation. The study should include: • Continuous monitoring of air temperature, humidity, wind speed, and direction at multiple altitudes (e.g., ground level, rotor hub height, and above the blade tips). • Remote sensing of sea surface temperature (SST) via satellite and aerial thermal imaging. • High-resolution meteorological modeling and thermal mapping to detect changes in temperature gradients and local atmospheric stratification. • Control regions (similar in geography and climate but without wind farms) to compare natural variability. The study should aim to detect shifts in: • Average air and surface temperatures, • Frequency and intensity of thermal inversions, • Altered wind patterns or stagnation zones, • Sea-air energy exchange rates. A rigorous two-phase dataset will allow researchers to quantify the causal relationship between wind energy extraction and thermal alterations in the surrounding environment, helping to refine future siting, regulation, and risk assessment for large-scale renewable energy infrastructure.Policy and Investment Recommendations Based on the thermodynamic modeling and case studies presented, we strongly recommend a moratorium on the installation of new large-scale wind farms—both onshore and offshore—in climatically sensitive regions, particularly: • The Mediterranean basin, where additional warming of coastal air and sea surface temperatures could disrupt fragile microclimates, harm tourism, and increase the frequency of thermal extremes; • The Gulf of Mexico, where reduced wind-driven cooling could exacerbate hurricane formation and intensification, increasing risks to human life and infrastructure; • Inland hurricane-prone regions, where alterations in air flow and temperature gradients may unintentionally amplify storm dynamics. In these zones, we recommend prioritizing solar energy development, which has minimal interference with atmospheric circulation, no kinetic energy extraction, and low local thermal impact when properly managed. Furthermore, we advise private investors, insurers, and energy stakeholders to account for the potential rise in operational and legal risks associated with large wind installations in these areas. Future lawsuits, regulatory shutdowns, or loss of insurability may arise if climate-related damages can be causally linked to turbine-induced atmospheric alterations. By shifting investment toward solar technologies or non-intrusive renewables, stakeholders can minimize environmental impact while maximizing long-term security and public acceptance.