University of Illinois Urbana-Champaign

Quality control and analysis of an updated wind gust data set in the United States

Pagnanelli, Jr., Michael Joseph

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https://hdl.handle.net/2142/132711

Description

Title
Quality control and analysis of an updated wind gust data set in the United States
Author(s)
Pagnanelli, Jr., Michael Joseph
Issue Date
2025-12-12
Director of Research (if dissertation) or Advisor (if thesis)
Lombardo, Franklin T
Department of Study
Civil & Environmental Eng
Discipline
Civil Engineering
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
  • wind engineering
  • ASOS
  • quality control
  • wind gusts
Abstract
This thesis presents the development of an updated 51-year peak wind gust data set for 679 Automated Surface Observing Systems (ASOS) stations across the Continental United States (CONUS) and explores limitations and implications for long return period wind speed estimation. In total, the data set contains more than 17.9 million peak wind gusts, including nearly double the station-years available compared to the data set used in the current ASCE/SEI 7-22 wind hazard maps. A rigorous quality control methodology was implemented using manual inspection of archived Meteorological Aerodrome Reports (METAR), 1-minute ASOS data, radar data, and surface analysis. In addition, 1-minute data is used to explore how the automated quality algorithm and power outages may impact long return period wind speed estimations. Peak wind speeds are classified into thunderstorm, non-thunderstorm, and tropical and standardized for instrumentation changes. Spatial analysis of annual maximum wind gusts shows the highest thunderstorm and non-thunderstorm wind speeds in the central Great Plains. Trends in median annual maximum wind gusts show a slight increasing trend, however, changes in ASOS averaging time and instrumentation, such as sonic anemometer installation, introduces three distinct eras in the data set. Overall, this work represents the most complete data set ever assembled for CONUS ASOS stations and demonstrates improvements over the previous data set, improving confidence in extreme wind speed estimation for future wind hazard maps.
Graduation Semester
2025-12
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/132711
Copyright and License Information
Copyright 2025 Michael Pagnanelli, Jr.

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