Executive Summary

As of 2022, Wisconsin has a total of 7 counties either partially or fully classified as “nonattainment” for the 2015 ozone National Ambient Air Quality Standards (NAAQS) of 70 ppb. To effectively reduce ozone in Wisconsin nonattainment areas, understanding ozone formation along the Lake Michigan shoreline is critical. Ground-level ozone is produced when ozone precursors (nitrogen oxides [NOx] and volatile organic compounds [VOCs]) react in the presence of sunlight. However, ozone formation chemistry can vary significantly depending on meteorology, precursor concentrations, and precursor composition. Certain species of VOCs are more reactive than others, which can impact the amount of ozone that is able to form as a result. To continue expanding the Wisconsin Department of Natural Resources (DNR) Air Management Program’s understanding of ozone formation in Wisconsin’s ozone nonattainment areas, speciated carbonyl and hydrocarbon VOC samples were collected at the Grafton, Chiwaukee Prairie, and Sheboygan Spaceport monitoring sites across four consecutive ozone seasons spanning 2019-2022. 

Comparison of Ozone Formation Potential (OFP) at Chiwaukee and Sheboygan on strategically selected case study days (June 3rd, 2021, August 5th, 2021, and June 20th, 2022) suggests that formaldehyde and acetaldehyde were the most consistent and significant potential contributors to the high ozone on these days. A considerable fraction of atmospheric formaldehyde is formed from the oxidation of isoprene (an abundant and reactive, biogenically emitted VOC) and other hydrocarbons, but is also directly emitted from a variety of anthropogenic sources, commonly as a byproduct of combustion. Similarly, acetaldehyde is largely produced via oxidation of alkenes (class of VOCs commonly emitted from both biogenic and mobile sources), alkanes, ethanol, isoprene, and other VOCs. Acetaldehyde is also directly emitted from combustion processes, wood-burning, and other anthropogenic sources. Other notable OFP contributors that were observed during this campaign include ethylene, (m, p, and o)-xylenes, toluene, and butene isomers, many of which are primarily emitted from gasoline and diesel combustion.

Abstract

Over the last 50 years, the United States has experienced an increase in severe storm events that produced $1 billion in damages or greater. Much of this loss is attributed to significant tornadoes and hail associated with deep, moist convection. Improving forecasts for these significant events assist in mitigating the impacts of these events. Previous work has identified statistically significant environmental parameters associated with severe thunderstorms, but more research is needed in identifying statistically significant ingredients associated with environments that produce significant tornadoes and hail.

This thesis aims to answer the following question: “Can diagnostics commonly used to forecast for severe convective storms be used as discriminators between severe and significant-severe tornadoes and hail?” Observational and reanalysis-derived proximity soundings were examined for the 1996–2018 period. Severe and significant-severe local storm reports gathered by National Weather Service offices and the Storm Prediction Center were used as a proxy for sounding location and associated hazard magnitude. 

For each sounding, a total of 45 different atmospheric diagnostics were analyzed. Results from statistical testing and Support Vector Classification machine-learning showed that 10–500m bulk wind difference, 10-m–1-km average mixing ratio, and 10-m–1-km SRH were able to discriminate between significant and non-significant tornadoes with a maximum of approximately 36% more skill over a random forecast. Overall skill for tornadic discrimination was primarily associated with kinematic diagnostics, while discrimination for hail showed higher amounts of variability and generally lower skill scores across all diagnostics tested with the SVC algorithm. 

The ICICLE campaign took place between 28 January and 8 March 2019 with an operations center in Rockford, IL. The NRC Convair 580 conducted 25 flights over the upper midwest to deepen their understanding of the mechanisms associated with SLD environments, including initiation, persistence and cessation, as well as operationally-critical transitions between SLD, small-drop and non-icing environments. The aircraft observations were complimented by in-situ observations at 4 super sites in Iowa and Michigan. There were also soundings launched at 4 universities; Iowa State University, Northern Illinois University, University of Illinois, Valparaiso University.  During the campaign, I was the primary radiosonde launch coordinator for Northern Illinois University, performing balloon launches at the request of NCAR. 

Abstract

On July 23rd, 2010, a high-precipitation (HP) supercell produced one of the largest hailstones ever recorded in the U.S. over Vivian, South Dakota. The environment this storm developed in possessed Mean Layer Convective Available Potential Energy (MLCAPE) values maximizing around 4500 Jkg-1, 0-6 km shear values around 50 knots, and produced an intensely strong storm updraft estimated to have reached vertical velocities upwards of 160-180 mph. The lifting mechanisms for initiating convection included a stationary front transitioning into a warm front as a weak low pressure center moved in from the west, together with an outflow boundary traveling southeast, originating from preexisting convection in Northwestern South Dakota. High levels of boundary-layer moisture were observed, with temperatures reaching the low 80s and dewpoint temperatures in the high 60s/low 70s. The reported size of the record-breaking hailstone was 8.0 inches in diameter, 18.625 inches in circumference, and weighed in at 1.9375 pounds. The temporal window of interest spans from 21Z on the 23rd to 00Z on the 24th.

Using the National Center for Atmospheric Research’s Weather Research and Forecasting model (WRF v 3.7), a series of idealized simulations were performed in order to assess the ability of WRF to correctly replicate the supercell that produced this large hail. The model was defined with a 500m special resolution and a 3 second temporal resolution/time step. Variable sensitivities tested include the beginning thermodynamic and wind profiles, as well as the choice of microphysics scheme. A simulation utilizing the Thompson Graupel microphysics scheme using an observation-assimilated version of the Weisman & Klemp idealized initial sounding was chosen for in-depth analysis. 

Results showed extreme differences in updraft strength and structure between the model-generated left-moving (multi-cell) and right-moving (supercell) systems, as well as differences in associated graupel accumulation swaths. The simulated supercell produced a nearly-negligible graupel accumulation swath, proposing minimal amounts of graupel embryo were generated by the simulated supercell. Further analysis in conjunction with prior literature suggested seeder-feeder processes were partly responsible for generation of the 8-inch aggregated hailstone over Vivian, SD. 

Abstract

In June of 2016, two hydroclimate stations were deployed in open and protected wetland ecosystems. One was deployed in a protected wetland near the CMU Biological Station, and the other was deployed in an open wetland on Garden Island. These stations are collecting air temperature (°C), humidity (% Relative Humidity), barometric pressure (kPa), solar radiation (W/m²), precipitation (mm), wind speed (m/s), and wind direction (°), soil temperature (°C), and soil moisture (m³/m³). Separate from the weather stations, there are multiple self-contained Leveloggers and Barologgers, which measure wetland water level, shallow ground water level (m), deep ground water level (m), atmospheric pressure (kPa), and water temperature (°C). These devices, in conjunction, will produce a 3-dimensional flux of ground water and surface water motions. Results from these stations will be compared to airport observations for validation. This is the first step in an ongoing project to assess the impact of weather patterns on the health of these wetland ecosystems.