Monday, 7 January 2019
Hall 4 (Phoenix Convention Center - West and North Buildings)
Wind is an important atmospheric variable which is receiving increased attention as the world seeks to shift from carbon-intensive fuels in order to mitigate climate change. This has resulted in an increased need for more temporally and spatially continuous wind information which is often met through the use of reanalysis data. This project has two parts; assessing the skill with which reanalysis products reproduce observed winds and methods for extrapolating the reanalyzed wind data to hub-height for use in estimating wind power potential. The initial focus is on the representation of daily and monthly average 10-meter wind speed data in the Upper Midwest (UMW) by six global reanalysis datasets against surface observations for the period 1979 - 2016. While it was found that higher resolutions and complexity in more recent generations of reanalysis models produced more accurate wind speeds in the region, particularly for daily winds, important biases remained. High variability in the observed monthly data resulted in lower correlations less accurate wind speed distributions and lower temporal agreement between the reanalyses and observations at longer time scales. Linear trends in the reanalyzed wind speeds were significantly underestimated compared to observations as well. This was followed by an assessment of the accuracy of several common methods for extending the surface wind data from three reanalyses (of the six) that were found to be the most accurate to 80 meters against tall tower data taken from 1995 – 2007. Here is was notable that methods which accounted for the influences of surface roughness and atmospheric stability were able to produce more accurate hub-height wind patterns, in general. These findings will be important to future modeling efforts, potential applications of the data, and to wind energy planning. Future work will use these data to understand the impact of various modes of variability in the climate system on wind and wind energy potential in the UMW.
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