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Advances in Meteorology
Volume 2016 (2016), Article ID 2020379, 15 pages
Research Article

An Observational and Model Characterization of Vertical Structure of Wind Fields over Eastern United States: A Case Study of Sterling, Virginia

1Atmospheric Science Program, Beltsville Center for Climate System Observation, Howard University, 2355 6TH Street NW, Washington, DC 20059, USA
2Department of Physics, Joint Center for Earth Systems Technology (JCET), University of Maryland, Baltimore Campus, 1000 Hilltop Circle, Room 424, Baltimore, MD 21228, USA
3College of Online and Continuing Education, Southern New Hampshire University, 33 South Commercial Street, Manchester, NH 03101, USA

Received 7 June 2015; Revised 30 September 2015; Accepted 30 September 2015

Academic Editor: Luis Gimeno

Copyright © 2016 Sium Gebremariam et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The performance of twenty GCMs that participated in the Coupled Model Intercomparison Phase 5 (CMIP5) is evaluated at Sterling, Virginia, by comparing model outputs with radiosonde observational dataset and reanalysis dataset. We evaluated CMIP5 models in their ability to simulate wind climatology, seasonal cycle, interannual variability, and trends at the pressure levels from 850 hPa to 30 hPa. We also addressed the question of the number of years required to detect statistically significant wind trends using radiosonde wind measurements. Our results show that CMIP5 models and reanalysis successfully reproduced the observed climatological annual mean zonal wind and wind speed vertical distribution. They also capture the observed seasonal zonal, meridional, and wind speed vertical distribution with stronger (weaker) wind during the winter (summer) season. However, there is some disagreement in the magnitude of vertical profiles among CMIP5 models, reanalysis, and radiosonde observation. Overall, the number of years to obtain statistically significant trend decreases with increasing pressure level except for upper troposphere. Although the vertical profile of interannual variability of CMIP5 models and reanalysis agree with the radiosonde observation, the wind trend is not statistically significant. This indicates that detection of trends on local scale is challenging because of small signal-to-noise ratio problems.