Publications Published in Renewable Energy

1. A neural network approach to local downscaling of GCM output for assessing wind power implications of climate change. Sailor, D. J.; Hu, T.; Li, X.; Rosen, J. N..
   Renewable Energy: 2000
   Notes
   A methodology is presented for downscaling General Circulation Model (GCM) output to predict surface wind speeds at scales of interest in the wind power industry under expected future climatic conditions. The approach involves a combination of Neural Network tools and traditional weather forecasting techniques. A Neural Network transfer function is developed to relate local wind speed observations to large scale GCM predictions of atmospheric properties under current climatic conditions. By assuming the invariability of this transfer function under conditions of doubled atmospheric carbon dioxide, the resulting transfer function is then applied to GCM output for a transient run of the National Center for Atmospheric Research coupled ocean-atmosphere GCM. This methodology is applied to three test sites in regions relevant to the wind power industry—one in Texas and two in California. Changes in daily mean wind speeds at each location are presented and discussed with respect to potential implications for wind power generation.
   
   
   
2. Climate change implications for wind power resources in the Northwest United States. Sailor, David J.; Smith, Michael; Hart, Melissa.
   Renewable Energy:
   Notes
   Using statistically downscaled output from four general circulation models (GCMs), we have investigated scenarios of climate change impacts on wind power generation potential in a five-state region within the Northwest United States (Idaho, Montana, Oregon, Washington, and Wyoming). All GCM simulations were extracted from the standardized set of runs created for the Intergovernmental Panel on Climate Change (IPCC). Analysis of model runs for the 20th century (20c3m) simulations revealed that the direct output of wind statistics from these models is of relatively poor quality compared with observations at airport weather stations within each state. When the GCM output was statistically downscaled, the resulting estimates of current climate wind statistics are substantially better. Furthermore, in looking at the GCM wind statistics for two IPCC future climate scenarios from the Special Report on Emissions Scenarios (SRES A1B and A2), there was significant disagreement in the direct model output from the four GCMs. When statistical downscaling was applied to the future climate simulations, a more coherent story unfolded related to the likely impact of climate change on the region's wind power resource. Specifically, the results suggest that summertime wind speeds in the Northwest may decrease by 5–10%, while wintertime wind speeds may decrease by relatively little, or possibly increase slightly. When these wind statistics are projected to typical turbine hub heights and nominal wind turbine power curves are applied, the impact of the climate change scenarios on wind power may be as high as a 40% reduction in summertime generation potential.
   
   
   
3. On the potential change in solar radiation over the US due to increases of atmospheric greenhouse gases. Pan, Zaitao; Segal, Moti; Arritt, Raymond W.; Takle, Eugene S..
   Renewable Energy: 2004
   Notes
   Solar radiation is the most important source of renewable energy available to reduce fossil CO2 atmospheric emissions and also is an important factor in heating, ventilation, and air conditioning (HVAC) energy considerations. Solar radiation may be affected by climate changes induced by CO2 emissions. In this study, a refined regional climate model was used to generate seasonal global radiation climatologies for the US under the present and mid 21st century enhanced atmospheric CO2 level. Simulated seasonal-mean daily global radiation (direct plus diffuse incident radiation on a horizontal surface) under the present climate showed overall reasonable agreement with observed patterns but with negative biases in most locations. In most of the US, the enhanced CO2 simulation (future climate) showed a trend of decreased seasonal-mean daily global radiation availability in the range of 0–20%. The most noticeable decrease was simulated in the western US during fall, winter, and spring. In small areas in the southern and northwestern US some increase in global radiation was simulated. Changes in global radiation during summer were relatively low.
   
   
   
4. Vulnerability of wind power resources to climate change in the continental United States. Breslow, P. B.; Sailor, D. J..
   Renewable Energy: 2002
   Notes
   Renewable energy resources will play a key role in meeting the world's energy demand over the coming decades. Unfortunately, these resources are all susceptible to variations in climate, and hence vulnerable to climate change. Recent findings in the atmospheric science literature suggest that the impacts of greenhouse gas induced warming are likely to significantly alter climate patterns in the future. In this paper we investigate the potential impacts of climate change on wind speeds and hence on wind power, across the continental US. General Circulation Model output from the Canadian Climate Center and the Hadley Center were used to provide a range of possible variations in seasonal mean wind magnitude. These projections were used to investigate the vulnerability of current and potential wind power generation regions. The models were generally consistent in predicting that the US will see reduced wind speeds of 1.0 to 3.2% in the next 50 years, and 1.4 to 4.5% over the next 100 years. In both cases the Canadian model predicted larger decreases in wind speeds. At regional scales the two models showed some similarities in early years of simulations (e.g. 2050), but diverged significantly in their predictions for 2100. Hence, there is still a great deal of uncertainty regarding how wind fields will change in the future. Nevertheless, the two models investigated here are used as possible scenarios for use in investigating regional wind power vulnerabilities, and point to the need to consider climate variability and long term climate change in citing wind power facilities.