Impact of wind-energy generation on climate

Preprint of the paper

Abbasi, S. A., Tabassum-Abbasi., and Abbasi, T., (2016). Impact of wind-energy generation on climate: a rising spectre, Renewable and Sustainable Energy Reviews, dx.doi.org/10.1016/j.rser.2015.12.262

Uploaded with permission from Elsevier, received from its Global Rights Department on 27 March 2018

Impact of wind-energy generation on climate: a rising spectre by # S. A. Abbasi*, Tabassum-Abbasi, and Tasneem Abbasi Centre for Pollution Control & Environmental Engineering Pondicherry University, Chinakalapet Puducherry 605 014, India Abstract Several theoretical studies have been reported in recent years which have indicated that large-scale wind farms can have an impact on local and regional meteorology, possibly on climate. Now evidence of it based on field observations has also begun to emerge. The present review traces the evolution of this knowledge. It discusses the theoretical studies on the possibility of wind turbines effecting climate change, and summarizes the emerging confirmation of those predictions. The concluding part of the review assesses the implications of these findings in the context of the world’s past experience on global warming and its present thrust to meet substantial portions of its energy needs with renewables. Key words: Wind energy, wind turbines, weather, climate change, global warming, solar energy

1. Introduction 1.1 The expected surge in the large-scale development of wind energy Among the ways in which electricity can be generated from renewable energy sources (RES), the one based on wind turbines is believed to be the least harmful to the environment (Katsaprakakis, 2012; Badger et al., 2014; Reikard et al., 2015). It has also been the most cost effective of the RES till now (Caduff et al., 2012). Due to the combination of these two factors wind energy is the most extensively utilized of all renewable energy sources for electricity generation if large hydropower is excluded from consideration (as it usually is). But even as wind energy-based power generation has recorded a 300-fold growth between 1990 and the present, its contribution to the world’s energy basket is a modest 0.2% , largely confined to five nations—China, the USA, Germany, Spain, and India (Leung and Yang, 2012; Tabassum-Abbasi et al., 2014). But there are attempts to improve this share and the Inter-governmental Panel on Climate Change in their recent report (IPCC, 2011) has hoped that in excess of 20% of the world’s electricity demand would be met with wind energy by 2050. The USA aims to reach this goal much earlier—by 2030 (USDE 2008). The “20-20-20” target set by the European Union (EU 2011) which aims at reducing greenhouse gases by 20%, reduce primary energy use by 20%, and enhance the contribution of

*Corresponding author < [email protected]> #Concurrently Visiting Associate Professor, Department of Fire Protection Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA.

renewable sources to meet 20% of the EU’s energy demand by the year 2020, also aims to rely heavily on wind energy for meeting the first and the third of its targets (Bakker et al., 2012). If these scenarios are to be realized, wind energy deployment must grow exponentially from now onwards to achieve several hundred-fold growth from its today’s levels of 300 GW. Preliminary estimates (Miller et al., 2011) indicate that to produce that kind of power, continental-scale wind farms would be required. For example using onshore wind farm production rate of 2 W m-2, which is a generous estimate that will be hard to achieve as the best sites that can enable that level of energy extraction will get used up soon, implies that 2 million square kilometers of wind farm area would the needed to produce 4 TW. This is about a fourth of the area occupied by the 48 contiguous states of the USA. If the global energy demand continues to grow at the rate it has been in the recent past, more and more wind farms of similarly large areas would be required to maintain 20% share of wind energy in the overall energy generation. To reduce pressures on land and the man−machine conflicts associated with inland wind farms, there are vigorous efforts to take wind energy extraction offshore. But this option has special problems of its own―higher costs and serious disturbances to marine ecosystems being two of the most significant (Tabassum Abbasi et al., 2014; Astariz et al., 2015).

1.2 Known environmental impacts and the rising scourge of impact on climate Among the negative environmental impacts of wind turbines which have been identified since the late 1970s (Harte and Jassby 1978; Abbasi et al., 1995; Abbasi and Abbasi 2000; 2012; TabassumAbbasi et al., 2014) are visual, noise, image flicker, interference with TV transmission signals, and bird hits. But evidence has now emerged of another impact of wind turbines which till recently was not considered to be of any consequence: weather modification, with the possibility of causing climate change. It was being forecast on the basis of theoretical studies reported during 2004-2011 but has now been confirmed with field measurements. This paper is perhaps the first review of the emerging field of study. It is aimed at stimulating more work as well as to prompt a serious re-thinking on how much reliance on wind power is really justified and how best to realize the wind energy potential without seriously deepening the global environmental crisis already precipitated by excessive fossil fuel use. 2. Evolution of knowledge on the wind turbines’ impact on weather The windmill was invented 3000 years ago (Johnson, 1985; Hills, 1994) and till the beginning of the fossil fuel era some 260 years ago windmills provided the third most used source of mechanical power in the world after human/animal labour and watermills (Abbasi et al., 2011a).

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It is possible that in the long history of windmills, during which their popularity and extent of use continually increased for all but a hundred-odd years of the previous two centuries, some clash of interest might have occurred between the owners of windmills and those who had no stakes in the windmills but had to endure the windmills’ noise or intrusion on the scenery. But no documentation of such clash is found in scientific literature. The mention of likely adverse environmental impacts— especially noise, interference in TV signals and possible danger to birds—began to be made only in the late 1970s (Harte and Jassby 1978) when the concept of wind farms or wind parks was becoming well-entrenched as a means to generate power comparable in magnitude to the medium or large scale conventional power plants (Faxen, 1978; Vermeulen et al., 1979). At that stage it was speculated (Harte and Jassby 1978) that slowing of winds by turbines may effect evaporation in lakes situated downwind, making them warmer. It may also lead to increase in soil moisture. But there were no studies to judge whether these impacts will be significant or would be of a type that will get soon assimilated by adoptive responses. Experimental findings on medium and large-scale turbine-generated wakes, which intensified in the late 1970s (Faxen, 1978; Vermeulen et al., 1979) and continued through to the present millennium (Connel and George, 1981; Taylor 1983; Milborrow et al., 1984 Lundin et al., 1990; Magnusson, 1999; Inanova and Nadyozhina, 2000), have provided a clear indication of how the extraction of the wind’s kinetic energy by the turbines impacts downstream wind speeds. Prognostic and diagnostic models (Ivanova and Nadyozhina 2000; Leclerc et al., 1999) have shown that wind turbines and farms significantly impact hub-height level wind speed and turbulence in proportion to the size and the number of the turbines involved (Chang et al., 2013; Rhodes et al., 2013; Wu and Prtē-Agel, 2013; Hidalgo et al., 2014). Velocity deficits of the order of 10% or more can occur immediately downstream of wind turbine arrays even in offshore wind farms (Christiansen and Hasager 2005, 2006). These deficits are strongly dependant on atmospheric stability (Smith et al., 2013; Hidalgo et al., 2014); they may last for 5 Km in unstable atmospheric conditions but may persist for 21 Km or more when the atmospheric stability is neutral. Parallely, studies on the atmospheric disturbances caused by human modifications of the landscape have been carried out (Chen and Avissar 1994; Dalu et al., 1996; vidale et al., 1997; Weaver and Avissar 2001). A meeting of these two lines of investigation has ultimately led to attempts which have examined the possibility of the impact of wind turbines on the weather. The rationale of the attempts has come from the understanding that a) the fluxes of heat and moisture from the earth’s surface into the adjacent atmosphere are fundamental driving forces of atmospheric motions in the planetary boundary layer (Stull, 1988; Zhang et al., 2013; Badger et al., 2014); b) these fluxes are strongly influenced by the kinetic energy carried by the winds over the land surface; c) the flux of energy associated with the near-surface winds is relatively small — about 1.5 Wm-2 — but influences much larger energy fluxes by the heat and moisture that the winds transport; d) the response of the atmosphere to this forcing depends strongly on the scale of the landscape variability that determines the distribution of these fluxes; e) large-scale wind farms would not only introduce

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landscape heterogeneity in regions of about 100–200 km or more, but also slow down wind speeds by extracting energy from the winds; and f) the resultant changes in turbulent motions would have the potential to organize into much larger, or mesoscale, circulations. Various investigations using numerical models have suggested that the perturbations caused by introduction of landscape roughness can be intense, and may play an influential role in producing and organizing clouds and precipitation. Moreover they could have effects that are significant at scales much larger than simply the scale of the systems themselves (Pielke et al., 1991; Segal et al., 1988, 1989, Yan and Anthes 1988; Pinty et al., 1989; Chen and Avissar 1994; Lynn et al., 1995; Seth and Giorgi 1996; Avissar and Liu 1996). A few studies exist which have identified possible signatures of this type of landscape-induced mesoscale circulations in certain regions and for certain conditions (Rabin et al., 1990; Bougeault et al., 1991; Cutrim et al., 1995; Brown and Arnold 1998). Subsequent work, based on more precise meteorological observations and more sophisticated modeling (Vidale et al., 1997; Zhong and Doran 1997, 1998), have further underscored the importance of mesoscale landscape effects in the context of climate and climate prediction. The build-up created by all these studies led, in 2004, to the first two reports on the theoretical evidence of the impacts of wind farms on local meteorology. The reports came from two groups that were seemingly working independent of each other as each did not refer to the other’s work (Baidya Roy et al., 2004; Keith et al., 2004). Nevertheless, the two groups had one author (Pacala) common. 3. Impact of wind turbines on weather and climate 3.1 Lead-up theoretical studies Baidya Roy et al., (2004) used the Regional Atmospheric Modeling System (RAMS) to simulate the effects of a hypothetical wind farm in a region (in Oklahoma) which is rich in wind resources and is set to be exploited to its full potential (Cotton et al., 2003; EERE, 2002). The model was run with data of a 15-day period which involved strong precipitation events followed by a dry spell. This enabled investigations on the impacts of wind farms under both wet and dry synoptic conditions. The simulations confirmed what the earlier findings had indicated – that the wind farms would lower the wind speed quite significantly (at the level of the turbine hub-height) and drastically affect the vertical distribution of temperature, humidity, surface sensible heat fluxes and surface latent heat fluxes. The latter is caused due to the enhanced vertical mixing effected by the turbulence created in the wake of the rotors. The impact was likely to be the highest during the early hours of the day, mostly due to the strong hub-height level winds associated with the nocturnal low-level jet.

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As the nocturnal boundary layer is relatively stable with large vertical gradients of momentum, humidity and temperature, it was likely to experience the effect of enhanced vertical mixing much more strongly than a well-mixed diurnal boundary layer. In the exploration of Keith et al., (2004), also, the meteorological impact of wind turbines was modeled in a hypothetical wind farm, but the approach was to alter surface drag coefficients in a suite of numerical experiments using two different general circulation models, one originating from the National Center for Atmospheric Research (NCAR) and the other from the Geophysical Fluid Dynamics Laboratory (GFDL; Princeton). When running both models, the drag coefficients were perturbed uniformly over an area defined by the wind-farm arrays. The analysis led the authors to conclude that the climatic impacts of wind power may be ‘non-negligible’. Even as this broad conclusion was emphatic, the authors could not achieve a quantitative evaluation of the extent of the changes likely to be induced due to the extraction of wind power. These two studies on the possible impact of wind-based power generation on climate have been followed by other modeling efforts which have reinforced the surmise that wind turbines if used in numbers adequate to generate 20% or 30% of the global electricity in years to come, would have significant impact on climate. The analysis of Adams and Keith (2007) indicates that large wind farms directly influence the atmospheric boundary layer by (a) reducing wind speeds, (b) generating blade scale turbulence in the wake of the turbines, and (c) generating shear driven turbulence due to the reduced wind speeds in the turbine wake. Large wind turbines can also have indirect effects on the local climate by influencing surface roughness, advection of heat and moisture, and turbulent transport in the boundary layer (Kirk-Davidoff and Keith 2008). Applying a general circulation model (GCM) to a hypothetical, continent-scale wind farm, Barrie and Kirk-Davidoff (2010) have also found that atmospheric anomalies initially develop at the wind farm site due to a slowing of the obstructed wind. The anomalies then propagate downstream and gather force when they reach the North Atlantic. These responses were seen to occur within a short forecast timeframe, which suggested that predictable influences on weather may be possible. Wang and Prinn (2010) have used a three-dimensional climate model to simulate the potential climate effects associated with installation of windmills to meet 10% or more of global energy demand. The assessment reveals that in such a scenario surface warming exceeding 10°C over land installations can be expected. More significantly, Wang and Prinn (2010) forecast that impacts resulting in significant warming or cooling can occur even in places remote from wind farms. Alterations of the global distributions of rainfall and clouds can also occur. The impacts have their origin in the competing effects of increase in roughness and decrease in wind speed on near-surface turbulent heat fluxes, the differing nature of land and ocean surface friction, and the dimensions of the installations parallel and perpendicular to the prevailing winds. The perturbations caused by offshore wind turbines are likely to be lesser (Wang and Prinn, 2011) but this advantage may be offset by greater intermittancy and unpredictability of offshore wind−speeds.

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In the backdrop of mounting theoretical evidence that large wind farms can influence climate, Baidya Roy and Traiteur (2010) have explored the possibility of ‘low-impact’ wind farms to minimize the impacts on surface temperature. One option to achieve it, according to the authors, is to design roters that generate less turbulence in their wakes, thereby lessening the downstream impacts on the local climate. The other option is to locate wind farms in areas where background atmospheric boundary layer (ABL) turbulence is high due to natural reasons. Of these two, the engineering solution is expensive because it involves designing new rotors. The siting solution is convenient in terms of its reliance on currently available technology, but it requires wind farms to be sited in regions with high background ABL turbulence. Firstly, prolonged exposure to such turbulence may be damaging to the rotors, and, secondly, it may put wind farms away from the points of use of their power, enhancing transmission costs and losses. Hence either of the solution leads to secondary problems and it is difficult to say whether the trade-off would be favourable. In another application, of a weather research and forecasting (WRF) model, Fiedler and Bukovsky (2011) have found that the presence of a mid-west wind farm, either giant or small, can have an enormous impact on the weather and the amount of precipitation. In further work based on WRF by Finch et al., (2012; 2013a), a new wind farm parameterization was developed and the effects of wind turbines were represented by imposing a momentum sink on the mean flow, transferring kinetic energy into electricity and turbulent kinetic energy (TKE). The parameterization seeked to improve upon previous models, basing the atmospheric drag of turbines on the thrust coefficient of a modern commercial turbine. It was applied to an idealized offshore wind farm consisting of 10 x 10 turbine array similar to the scale of the Thanet Offshore Wind Farm which is currently the largest offshore wind farm in the world. Simulations revealed that a wind speed deficit would extend throughout the depth of the neutral boundary layer, above and downstream from the farm, for 60 KM. Within the farm the maximum wind speed deficit may touch 16%. Increases of TKE, upto nearly a factor of 7, could occur within the farm. This increase may extend to the top of the ABL above the farm due to vertical transport and wind shear, significantly enhancing turbulent momentum fluxes. Simulations showed that daytime convective conditions in the wind farm have little bearing on wind speeds, as the momentum deficits generated by the wind farm are rapidly compensated by the mixing occurring through the depth of the boundary layer. In contrast, the stable layer within the rotor area at nighttime inhibits turbulent mixing of the momentum deficit. It leads to a shallower wake and a greater reduction in the wind speed within the wake, causing a warming of upto I K at the bottom of the rotor area. The authors (Fitch et al., 2013 b) also suggest that modeling wind farms on the basis of an increase in surface aerodynamic roughness results in an atmospheric response that is very different from that found in LES studies and wind tunnel experiments reported earlier. In their assessment, models based on direct parameterization of the elevated drag (and source of turbulence) produce a more

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realistic wake structure, and are thus recommended for wind farm impact forecasting over the models based on enhanced roughness approach. 3.2 Direct evidence from field data In an attempt to take the purely theoretical studies, reported during 2004-2011, closer to the real-life situations, Baidya Roy, (2011) used data from a commercial wind turbine for a sub-grid scale rotor parameterization for feed to a mesoscale regional climate model (RCM). The RCM was equipped with state-of-the-art microphysics and land-surface scheme. The impacts were explored on nearsurface temperature, humidity and surface fluxes of sensible and latent heat. The author also examined the spatial distribution of the impacts within and downwind the wind farms especially focusing on the importance of the spatial scale of wind farms. The model output reveals that wind farms generate statistically significant impacts on near-surface air temperature and humidity as well as surface sensible and latent heat fluxes. These impacts depend on the atmospheric lapse rates of equivalent potential temperature and total water mixing ratio. The magnitudes of the impacts are not only constrained by the hub-height wind speed but also depend to some extent on the size of the wind farms. Sensitivity analysis shows that these impacts are not confined to the wind farms but extend a significant distance downwind. For example the hydrometeorology of the study area up to 18–23 km downwind was affected. The typical lengthscale of the wind farm wakes was seen to be approximately 20 km and was independent of the size of the wind farms as well as the background meteorology. A surmise of great concern was that the impacts from wind turbines on surface meteorological conditions are likely to affect agricultural practices as well as communities living in residential areas around the farms. Now the first concrete evidence based on field observations has come from Zhou et al., (2012). On the basis of an analysis of satellite data for the period of 2003–2011 over a region in west-central Texas, where four of the world’s largest wind farms are located, Zhou et al., (2012) have found a significant warming trend of up to 0.72°C per decade, particularly at night-time, over wind farms relative to nearby non-wind-farm regions. The authors have been able to link this warming to the impact of wind farms because the spatial pattern and magnitude of the warming has coupled very well with the geographic distribution of wind turbines. The findings of (Zhou et al., 2013) have been corroborated by an independent study on San Gorogonio Pass Wind Farm situated in Southern California, by Walsh-Thomas et al., (2012). These authors have found that downwind regions, south and east of the wind farms, are typically warmer than those west of the wind farm. The extent of downwind warming varied from 4 to 8 degrees celcius. A typical pattern of downwind rise in ambient temperature as observed by Walsh- Thomas et al., (2012) is presented in Figure 1. Some other observation which implicate wind turbines in local

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weather modification have also come to light. In Xilingo League, Inner Monogolia, precipitation data provided by the country’s Water. Statistics Bureau shows that there has been an unprecedented drought since 2005, and that this drought has developed much faster in areas that had wind turbines operating (Baidya Roy and Justin 2010). An analysis of temperature records at the San Gorgonio wind fields in the US indicate that giant wind turbines could be changing local temperatures by warming surface temperatures at night and cooling them in the daytime (Zhou et al., 2012). A more recent report based on field observations, by Zhou et al., (2013) takes further their earlier work on the impact of wind farms situated in West-Central Texas (Zhou et al., 2012), and shows that there is consistently a warming effect of 0.31-0.70 °C at nighttime for the 2003-2011 period, during which data was collected, and which can be attributed to the wind farms. The largest warming effect is observed at ~ 10:30 p.m in summer. As the nocturnal ABL is typically stable and much thinner than the daytime ABL, the turbine enhanced vertical mixing produces a stronger nighttime effect. The stronger wind speed and the higher frequency of the wind speed within the optimal power generation range in summer than winter and at nighttime than daytime likely drives wind turbines to generate more electricity and turbulence and consequently results in the strongest warming effect at nighttime in summer. A parallel report by Smith et al., (2013) corroborates these findings. Their observations of wakes from individual wind turbines, and a multi-megawatt wind energy installation in the Midwestern US, indicate that directly downstream of a turbine, there is a clear impact on wind speed and turbulence intensity. This causes a significant decrease in the vertical gradients of temperature largely by increasing the temperature at 2 m. Considering that many of the sites possessing rich wind power resources happen to consist of agricultural fields it becomes necessary to forecast the impact of wind power extraction on agricultural production (Rejewski et al., 2013 a, b). Surface drag and fluxes of wind which influence wind power generation depend on the nature of crop in the wind farm and its management. On the other hand, turbine-generated changes in mean wind speed, pressure, and turbulence have the potential to influence fluxes of heat, moisture, and CO2 that are vital for agricultural productivity. Given that the wakes of wind turbines can persist up to 15 rotor diameters downwind of a turbine the resulting impact on microclimate may influence the biological productivity of the surrounding crops (Rajewski et al., 2013 a). In an attempt to guage these impacts, Rajewski et al., (2013 b) organized a crop-wind-energy experiment at the edge of a large wind farm in terms of surface fluxes of momentum, heat, moisture, and carbon dioxide (CO2). The data it generated was stratified according to wind direction, diurnal condition, and turbine operational status. It was seen that the flux differences were negligible when the turbines were non-operational. With turbines ON, there was a difference which ranged from being statistically insignificant to a five-fold increase depending on the direction of wind and whether it was day time or night. The findings indicate that besides effecting the local weather, wind turbines may impact crop yields.

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3.3 Maximum extractable wind power and the consequence of extracting its large fraction There is another question associated with the consequence of the extraction of the wind’s kinetic energy by turbines: how much is realistically extractable? If what we wish to extract is a significant fraction of the extractable maximum, it can be conjectured that the extraction of that fraction is likely to have a significant impact on the climate. According to the estimation of Archer and Jacobson (2005), as much as 72 TW of wind power can be extracted over land even if only 13% of the most windy land areas are utilized. The estimate of Lu et al., (2009) is even more liberal: 125 TW, through it is based on utilizing a larger land area, and bigger wind turbines. More recently, Jacobson and Archer (2010) have stated that if 11.5 TW of electricity is generated with wind turbines, it would amount to a mere