Journal article
Addendum to Wind speed trends over the contiguous United States (vol 115, D10103, 2010)
Journal of geophysical research. Atmospheres, Vol.115, D10103
05/19/2010
DOI: 10.1029/2009JD013281
Abstract
An earlier paper (Pryor et al., 2009) reports linear trends for annual percentiles of 10 m wind speeds from across the United States based on ordinary linear regression applied without consideration of temporal autocorrelation. Herein we show significant temporal autocorrelation in annual metrics from approximately half of all surface and upper air wind speed time series and present analyses that indicate at least some fraction of the temporal autocorrelation at the annual time scale may be due to the influence of persistent low-frequency climate modes as manifest in teleconnection indices. Treatment of the temporal autocorrelation slightly reduces the number of stations for which linear trends in 10 m wind speeds are deemed significant but does not alter the trend magnitudes relative to those presented by Pryor et al. ( 2009). Analyses conducted accounting for the autocorrelation indicate 55% of annual 50th percentile 10 m wind speed time series, and 45% of 90th percentile annual 10 m wind speed time series derived from the National Climate Data Center DS3505 data set exhibit significant downward trends over the period 1973-2005. These trends are consistent with previously reported declines in pan evaporation but are not present in 10 m wind speeds from reanalysis products or upper air wind speeds from the radiosonde network.
Details
- Title: Subtitle
- Addendum to Wind speed trends over the contiguous United States (vol 115, D10103, 2010)
- Creators
- S. C. Pryor - Indiana UniversityJ. Ledolter - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of geophysical research. Atmospheres, Vol.115, D10103
- DOI
- 10.1029/2009JD013281
- ISSN
- 2169-897X
- eISSN
- 2169-8996
- Publisher
- Amer Geophysical Union
- Number of pages
- 7
- Grant note
- 0828655 / Directorate For Engineering; National Science Foundation (NSF); NSF - Directorate for Engineering (ENG)
- Language
- English
- Date published
- 05/19/2010
- Academic Unit
- Statistics and Actuarial Science; Business Analytics
- Record Identifier
- 9984380477402771
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