Natural climate variations in the United States wind resource are assessed by using cyclostationary empirical orthogonal functions (CSEOFs) to decompose wind reanalysis data. Compared to approaches that average climate signals or assume stationarity of the wind resource on interannual time scales, the CSEOF analysis isolates variability associated with specific climate oscillations, as well as their modulation from year to year. Contributions to wind speed variability from the modulated annual cycle (MAC) and the El Nino-Southern Oscillation (ENSO) are quantified, and information provided by the CSEOF analysis further allows the spatial variability of these effects to be determined. The impacts of the MAC and ENSO on the wind resource are calculated at existing wind turbine locations in the United States, revealing variations in the wind speed of up to 30% at individual sites. The results presented here have important implications for predictions of wind plant power output and siting.
机构:
China Meteorol Adm, Natl Climate Ctr, Beijing, Peoples R China
Michigan State Univ, Dept Geog, E Lansing, MI 48824 USAChina Meteorol Adm, Natl Climate Ctr, Beijing, Peoples R China
Li, X.
Zhong, S.
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Michigan State Univ, Dept Geog, E Lansing, MI 48824 USAChina Meteorol Adm, Natl Climate Ctr, Beijing, Peoples R China
Zhong, S.
Bian, X.
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USDA, Forest Serv, No Res Stn, E Lansing, MI USAChina Meteorol Adm, Natl Climate Ctr, Beijing, Peoples R China
Bian, X.
Heilman, W. E.
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USDA, Forest Serv, No Res Stn, E Lansing, MI USAChina Meteorol Adm, Natl Climate Ctr, Beijing, Peoples R China
机构:
MIT, MIT Joint Program Sci & Policy Global Change, Cambridge, MA 02139 USAMIT, MIT Joint Program Sci & Policy Global Change, Cambridge, MA 02139 USA
Gunturu, U. B.
Schlosser, C. A.
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MIT, MIT Joint Program Sci & Policy Global Change, Cambridge, MA 02139 USAMIT, MIT Joint Program Sci & Policy Global Change, Cambridge, MA 02139 USA