Temporal and Spatial Variability of Wind Resources in the United States as Derived from the Climate Forecast System Reanalysis

This study examines the spatial and temporal variability of wind speed at 80m above ground (the average hub height of most modern wind turbines) in the contiguous United States using Climate Forecast System Reanalysis (CFSR) data from 1979 to 2011. The mean 80-m wind exhibits strong seasonality and...

Full description

Bibliographic Details
Main Authors: Lejiang Yu, Shiyuan Zhong, Xindi Bian, Warren, E. Heilman
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2014
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.682.5657
http://www.fs.fed.us/nrs/pubs/jrnl/2015/nrs_2015_yu_001.pdf
id ftciteseerx:oai:CiteSeerX.psu:10.1.1.682.5657
record_format openpolar
spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.682.5657 2023-05-15T15:09:42+02:00 Temporal and Spatial Variability of Wind Resources in the United States as Derived from the Climate Forecast System Reanalysis Lejiang Yu Shiyuan Zhong Xindi Bian Warren E. Heilman The Pennsylvania State University CiteSeerX Archives 2014 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.682.5657 http://www.fs.fed.us/nrs/pubs/jrnl/2015/nrs_2015_yu_001.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.682.5657 http://www.fs.fed.us/nrs/pubs/jrnl/2015/nrs_2015_yu_001.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.fs.fed.us/nrs/pubs/jrnl/2015/nrs_2015_yu_001.pdf text 2014 ftciteseerx 2016-01-08T17:57:58Z This study examines the spatial and temporal variability of wind speed at 80m above ground (the average hub height of most modern wind turbines) in the contiguous United States using Climate Forecast System Reanalysis (CFSR) data from 1979 to 2011. The mean 80-m wind exhibits strong seasonality and large spatial variability, with higher (lower) wind speeds in the winter (summer), and higher (lower) speeds over much of the Midwest and U.S. Northeast (U.S. West and Southeast). Trends are also variable spatially, with more upward trends in areas of the Great Plains and IntermountainWest of the United States and more downward trends elsewhere. The leading EOF mode, which accounts for 20 % (summer) to 33 % (winter) of the total variance and represents in-phase variations across the United States, responds mainly to the North Atlantic Oscillation (NAO) in summer and El Niño–SouthernOscillation (ENSO) in the other seasons. The dominant variation pattern can be explained by a southerly/southwesterly (westerly) anomaly over the U.S. East (U.S. West) as a result of the anomalous mean sea level pressure (MSLP) pattern. The second EOF mode, which explains about 15%of the total variance and shows a seesaw pattern, is mainly related to the springtime Arctic Oscillation (AO), the summertime recurrent circumglobal teleconnection (CGT), the autumn Pacific decadal oscillation (PDO), and the winter El Niño Modoki. The anomalous jet stream and MSLP patterns associated with these indices are responsible for the wind variation. 1. Text Arctic North Atlantic North Atlantic oscillation Unknown Arctic Pacific
institution Open Polar
collection Unknown
op_collection_id ftciteseerx
language English
description This study examines the spatial and temporal variability of wind speed at 80m above ground (the average hub height of most modern wind turbines) in the contiguous United States using Climate Forecast System Reanalysis (CFSR) data from 1979 to 2011. The mean 80-m wind exhibits strong seasonality and large spatial variability, with higher (lower) wind speeds in the winter (summer), and higher (lower) speeds over much of the Midwest and U.S. Northeast (U.S. West and Southeast). Trends are also variable spatially, with more upward trends in areas of the Great Plains and IntermountainWest of the United States and more downward trends elsewhere. The leading EOF mode, which accounts for 20 % (summer) to 33 % (winter) of the total variance and represents in-phase variations across the United States, responds mainly to the North Atlantic Oscillation (NAO) in summer and El Niño–SouthernOscillation (ENSO) in the other seasons. The dominant variation pattern can be explained by a southerly/southwesterly (westerly) anomaly over the U.S. East (U.S. West) as a result of the anomalous mean sea level pressure (MSLP) pattern. The second EOF mode, which explains about 15%of the total variance and shows a seesaw pattern, is mainly related to the springtime Arctic Oscillation (AO), the summertime recurrent circumglobal teleconnection (CGT), the autumn Pacific decadal oscillation (PDO), and the winter El Niño Modoki. The anomalous jet stream and MSLP patterns associated with these indices are responsible for the wind variation. 1.
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author Lejiang Yu
Shiyuan Zhong
Xindi Bian
Warren
E. Heilman
spellingShingle Lejiang Yu
Shiyuan Zhong
Xindi Bian
Warren
E. Heilman
Temporal and Spatial Variability of Wind Resources in the United States as Derived from the Climate Forecast System Reanalysis
author_facet Lejiang Yu
Shiyuan Zhong
Xindi Bian
Warren
E. Heilman
author_sort Lejiang Yu
title Temporal and Spatial Variability of Wind Resources in the United States as Derived from the Climate Forecast System Reanalysis
title_short Temporal and Spatial Variability of Wind Resources in the United States as Derived from the Climate Forecast System Reanalysis
title_full Temporal and Spatial Variability of Wind Resources in the United States as Derived from the Climate Forecast System Reanalysis
title_fullStr Temporal and Spatial Variability of Wind Resources in the United States as Derived from the Climate Forecast System Reanalysis
title_full_unstemmed Temporal and Spatial Variability of Wind Resources in the United States as Derived from the Climate Forecast System Reanalysis
title_sort temporal and spatial variability of wind resources in the united states as derived from the climate forecast system reanalysis
publishDate 2014
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.682.5657
http://www.fs.fed.us/nrs/pubs/jrnl/2015/nrs_2015_yu_001.pdf
geographic Arctic
Pacific
geographic_facet Arctic
Pacific
genre Arctic
North Atlantic
North Atlantic oscillation
genre_facet Arctic
North Atlantic
North Atlantic oscillation
op_source http://www.fs.fed.us/nrs/pubs/jrnl/2015/nrs_2015_yu_001.pdf
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.682.5657
http://www.fs.fed.us/nrs/pubs/jrnl/2015/nrs_2015_yu_001.pdf
op_rights Metadata may be used without restrictions as long as the oai identifier remains attached to it.
_version_ 1766340831788138496