Date of Award

8-1-2021

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Atmospheric and Environmental Sciences

Content Description

1 online resource (xxii, 260 pages) : color illustrations, color maps.

Dissertation/Thesis Chair

Robert Fovell

Committee Members

Justin Minder, David Fitzjarrald, Liming Zhou

Keywords

Airborne Lidar, Gust Factor, Numerical Weather Prediction, Observational Meteorology, Wind Observations, Wind forecasting, Winds, Mesospheric circulation, Boundary layer (Meteorology)

Subject Categories

Atmospheric Sciences | Meteorology

Abstract

Accurate forecasts and reliable observations of surface mean winds and gusts inhabit a vast and essential role in meteorological applications that range from wind energy, atmospheric transport, fire weather, and hazard assessment. This dissertation aims to address and explore known shortfalls in the prediction of mean winds and gusts as well as enhance evaluation and understanding of observed surface wind measurements. A variety of forecasts, methodologies, and observational dataset, many of which have been previously un- or under-utilized, are leveraged to tackle the differing needs of assessing mean winds, gusts, and the surface environment.Detailed verifications of HRRR (version 3 and 4) forecasted mean winds and gusts were performed against ASOS and NYSM observations to assess the persistence and origin of systemic biases found in previous literature. Initial results showed the HRRR has a large degree of skill in forecasting network average wind speed, but also agreed with past works noting a systematic over- and under-prediction of wind speeds at locations with the slowest and fastest wind speeds. Subsetting the verification by assigned landuse category and local time revealed these biases to the be result of narrow and offset forecasted mean wind distributions that fail to capture the tails of the observed distribution at both slow and fast wind speeds. Certain landuse categories such as urban and forested exhibited endemic preferences towards negative and positive biases from shifts in the distribution while all other classifications struggled to properly represent moderate to fast wind speeds (4-8 m/s). Disagreement in the shape of the wind distribution was shown to be worse at night highlighting poor handling of the stable boundary layer. While there were improvements in resolving moderate wind speeds and some landuse changes when verifying HRRRV4 the bulk of these results remain largely the same. With respect to gusts, their complex and turbulent nature often necessitates diagnostic tools to predict gust potential in lieu of information with sufficiently high temporal resolution. The robustness of one of the most well-known gust forecasting tools, the Durst curve, is critically examined and compared to modern observations. ASOS 1-min and NYSM 3-s resolution data were used to construct hourly maximum gusts of a variable duration, t-seconds long, with respect to hourly mean winds and generate gust curves similar to Durst. The resulting gust curves displayed significant disparities with much larger gust factors (GFs) compared to the historic curve but were gradually brought into agreement by filtering observations requiring minimum hourly mean wind speeds and maximum allowable standard deviation of wind direction. This filtering limited the fraction of the usable observation record to incredibly small percentages highlighting the small range of conditions the historic gust curve is actually applicable for. Lastly, the influence of local obstructions on observations of mean winds, gusts, and GF were investigated through the use of airborne lidar data. While lidar data is relatively novel and largely heterogeneous in its configuration, after significant quality control efforts it provides and incredibly detailed and precise snapshot of the environment around surface observations. Comparisons of average GF and obstruction angles calculated from lidar point clouds indicated a strong agreement in the azimuthal variation of observed GF and the maximum obstruction angle in a direction. Composites of both ASOS and NYSM observations revealed that average mean wind speed, gust speed, and GF are all maximized when obstructions are absent or even with the horizon and drop of steeply as maximum obstruction angle deviates from 0⁰. Furthermore, for obstruction angles ASOS and NYSM have in common they were shown to be nearly identical in their observed mean wind, gust, and GF values when factors such as averaging interval and gust duration were kept equal.

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