Browsing by Author "Ellis, Andrew W."

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    Analysis of Model Thermal Profile Forecasts Associated with Winter Mixed Precipitation within the United States Mid-Atlantic Region
    Ellis, Andrew W.; Keighton, Stephen, I; Zick, Stephanie E.; Shearer, Andrew S.; Hockenbury, Casey E.; Silverman, Anita (National Weather Association, 2022-03-04)
    Winter mixed-precipitation events across the mid-Atlantic region of the United States from 2013-2014 through 2018-2019 were used to analyze common short-term model forecasts of vertical atmospheric thermal structure. Using saturated forecast soundings of the North American Mesoscale (NAM), higher-resolution nested NAM (NAMnest), and the Rapid Refresh models-corresponding with observed warm-nose precipitation events (WNPEs)-several thermal metrics formed the basis of the analysis of observed and forecast soundings. including Bourgouin positive and negative areas. While the three models accurately forecast the general thermal structure well during WNPEs, a warm bias is evident within each. Well forecast are maximum and minimum temperatures within the warm nose and surface-based cold layer, respectively, but the cold layer is commonly too thin for each of the models, and the warm nose is regularly too thick, particularly within NAM and NAMnest forecasts. Forecasts of a cold layer that is too shallow tend to coincide with observations of stronger synoptic-scale upward motion, a deeper cold surface-based layer, and a higher isentropic surface. Forecasts of a warm nose that is too thick tend to coincide with observations of weaker upward motion, a shallower cold surface-based layer, and a lower isentropic surface across the region. Two-thirds of precipitation-type estimates from model soundings agreed with those derived from observed soundings, with the remaining third predominantly representing a warm bias in precipitation type.
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    A Hybrid Dataset of Historical Cool-Season Lake Effects From the Eastern Great Lakes of North America
    Ellis, Andrew W.; Suriano, Zachary J. (Frontiers, 2022-02-21)
    The moistening of cold air passing over the Great Lakes of North America has a profound impact on the cool season climate of regions downwind, from relatively benign air mass modification to highly-impactful snowfall events. The importance of lake effects has led to the development of varying techniques for systematically identifying lake-effect days. The results of two such methods are merged here to yield a more thorough record of lake-effect days for the eastern Great Lakes. Comparative analysis of the data sets illustrates the different objectives of the two methodologies, where one identifies days with a synoptic setup conducive to lake-effect snowfall, and the other identifies days with lake-effect modification of the overlying air mass. A smaller population of "absolute" lake-effect days are those identified by both methods, while a larger population of "hybrid" lake-effect days are absolute days plus those identified by one method but not the other. For a 51-year study period ending with the 2014-15 cool season, the absolute data set yields a mean of about 15 lake-effect days per year, or 8% of the November through April season, while the hybrid data set yields a mean of 56 lake-effect days per year, or 31% of the season. The frequencies of absolute, air mass modification-defined, and hybrid lake-effect days decreased through the study period, with days within the hybrid data set declining at a statistically significant rate of 2.8 days per decade, although most obviously from the late 1970s through the early 2000s. The result is a general drying of the cool-season lake-effect hydroclimate. The merged data set offers a more thorough historical record of days available for atmospheric and hydroclimatic study of the lake-effect phenomenon within the eastern Great Lakes region.
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    Perceptions and realities of hydroclimatic change affecting Guyanese rice farming
    Mahdu, Omchand; Ellis, Andrew W. (Elsevier, 2021-07-21)
    This study explores small farmers’ perceptions of changes in climate across Guyana’s riceproducing regions. Qualitative, primary data were collected from a random sample of 189 small farmers, supplemented with 28 key informants, from across Guyana’s five main riceproducing regions. The most prevalent perception related to precipitation among farmers is an increase in rainfall year-round (56%), while for informants, it is an increase in rainfall intensity (81%). When considering the atmospheric conditions of temperature and humidity, farmers (88%) and informants (96%) overwhelmingly perceive warmer conditions. Considering weather and climate volatility, farmers (72%) and informants (82%) most prevalently perceive an increase in excess rainfall/flooding, but secondly, farmers (58%) and informants (71%) communicated a perceived increase in drought. Secondary quantitative hydroclimate data support the perception of a wetter climate, and to some degree, increased hydroclimatic volatility. Precipitation is critical to rice cultivation, and the data sets, combined, signal a wetter Guyanese climate, which has major economic implications for small farmers, the broader rice industry, and the economy of Guyana. However, granularity in farmers’ perceptions suggests a need for more detailed hydroclimate monitoring across Guyana. Thus, strengthening the Guyanese Hydrometeorological Service to support improved spatial and temporal monitoring and collection of primary weather data would be a wise investment in short- and long-term climate mitigation efforts.