Graduate Studies
First Advisor
Liang Chen
Second Advisor
Mark Anderson
Third Advisor
Curtis Walker
Date of this Version
5-2024
Document Type
Article
Citation
A thesis presented to the faculty of the Graduate College at the University of Nebraska in partial fulfillment of requirements for the degree of Master of Science
Major: Earth and Atmospheric sciences
Under the supervision of Professors Liang Chen and Mark R. Anderson
Lincoln, Nebraska, May 2024
Abstract
For the Nebraska Department of Transportation (NDOT), the Nebraska Winter Severity Index (NEWINS) provided an independent framework to calculate a winter season’s severity by categorizing individual winter storms. However, one of the greatest limitations of NEWINS is that it is not predictive. Thus, this study builds on the previously developed NEWINS by creating a predictive winter storm severity index known as NEWINS-Predictive (NEWINS-P). The quantitative precipitation forecast, snow accumulation, ice accumulation, and surface wind speed parameters from the National Digital Forecast Database (NDFD) are used to develop the five components composing the NEWINS-P framework. These components consist of snow severity (NEWINS-S), precipitation type, ice likelihood, blowing snow, and drifting snow likelihood, and attempt to forecast different in-storm and post-storm winter weather hazards over a 72-h duration at a 6-h resolution. The NEWINS-P framework is assessed through spatial forecasts across Nebraska and temporal forecasts at Nebraska airports on select Colorado Low and Alberta Clipper Systems from the 2018-19, 2021-22, and 2022-23 winter seasons. Additionally, spatial and temporal forecast trends are investigated in each system for select components to assess their degree of change. The results show that Colorado Low Systems were forecasted to have a larger areal extent and longevity of winter weather hazards than Alberta Clipper Systems. Furthermore, the Colorado Low Systems produce a higher intensity and spatial coverage of NEWINS-S, more types of precipitation, more icing concerns, and more blowing snow concerns. Post-storm impacts such as drifting snow are not forecasted in most systems as surface wind speeds decrease rapidly following the conclusion of snow accumulation. In all systems analyzed, the forecast trends reveal an increasing intensity of NEWINS-S as the system gets closer in time. Interpretations of the NEWINS-P output can be affected by a systematic artifact within the NDFD that is caused by forecast differences between weather forecast offices. In summary, NEWINS-P is a tool that supports NDOT in its winter maintenance operations for personnel and resource planning in advance of winter storms.
Advisors: Liang Chen and Mark R. Anderson
Comments
Copyright 2024, Thomas Kauzlarich. Used by permission