David's Abstract:
The Influence of Thunderstorm Type on Extreme Near-Surface Wind Speeds
The wind speed used for wind load design in the United States is based on a binary approach where the probability distributions of non-thunderstorm and thunderstorm wind speeds are analyzed independently in a mixed distribution. However, thunderstorm wind speeds are generated from multiple thunderstorm morphologies, which have somewhat different physical mechanisms for generating these winds. These differences likely result in different physical properties (e.g., wind profiles) at the surface. In an effort to bridge the gap between wind engineering and atmospheric sciences, this study seeks to determine 1) how thunderstorm morphology impacts the wind speeds used by the American Society of Civil Engineers and 2) how the wind engineering relevant characteristics differ between thunderstorm morphologies.
The first objective is to determine if the individual thunderstorm morphology should be considered separately when predicting extreme winds for wind design loading. Using data from the Automated Surface Observing System (ASOS) and radar data from the National Weather Service (NWS) in Iowa between 1996 and 2022, independent thunderstorm events that produced measured peak wind speeds > 58 mph were classified as being generated from single-cell, multicellular, or supercell thunderstorms. This was done using a subjective classification scheme that utilizes radar reflectivity and Doppler velocity GIFs. The categorized events were combined into a single superstation, checked for independence, and then an extreme value analysis was done on each thunderstorm morphology. Multicellular storms dominate the extreme wind climatology in Iowa, suggesting that thunderstorm morphology should be considered for wind load design.
The second objective is to determine how wind characteristics important for wind design loading (e.g., gust factor and turbulence intensity) differ by thunderstorm morphology. Using the ASOS stations and radar data in Iowa, Illinois, and Indiana, independent thunderstorm events with peak wind speeds > 45 mph were classified as multicellular organized, multicellular unorganized, or cellular using a mostly objective classification scheme. The one-minute ASOS records were then used, and wind characteristics such as turbulence intensity and gust factor were calculated. A Mann-Whitney U test found statistically significant differences between thunderstorm categories for multiple wind characteristics, including the turbulence intensity. These findings underscore the need for additional engineering-centric research on thunderstorm winds.
Katie's Abstract:
An analysis of the surface moisture flux in the Argentinian Cordoba Region using the 2018-2019 RELAMPAGO field campaign data
Northern Argentina is a region of substantial global agricultural activity, however, data on the land-atmosphere interactions has remained sparse leaving gaps in estimation and modeling the water-energy balance. Near surface land-atmosphere interactions can be difficult to capture accurately using popular remote sensing techniques, however, obtaining ground measurements is time, labor, and economically intensive. Issues with representing the fluxes is further compounded by the data being both spatially and temporally sparse, leaving considerable room for errors and gaps in understanding. The RELAMPAGO field campaign of 2018 in Argentina collected nearly a year of surface meteorological data using 15 stations, seven of which have eddy covariance flux measurements to measure moisture-energy and momentum fluxes. Given the timeline and the high spatial density of the towers in a single agricultural region, the data offers an unprecedented opportunity to investigate the water-energy flux balance for the region. Using this spatially dense data, daily evapotranspiration values were calculated. Two methods were compared: Eddy Covariance measurement which are treated as closest to the true values and the FAO Penman-Monteith method. The FAO Penman-Monteith method estimates ET utilizing more basic meteorological variables that are easier to obtain than those from Eddy Covariance instruments and basic energy balance principles. Values from the direct Eddy Covariance fluxes measurements and the widely accepted FAO Penman-Monteith equation are calculated and compared with the percent errors quantified. It was found that for the locations where direct comparison was possible, most of the FAO Penman-Monteith ET estimates were within 20% of those values calculated with the Eddy Covariance measurements.
