Browsing by Author "Twine, Tracy E"

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    Climate change projections for improved management of infrastructure, industry, and water resources in Minnesota
    (2019-09-15) Noe, Ryan R; Keeler, Bonnie L; Twine, Tracy E; Brauman, Kate A; Mayer, Terin; Rogers, Maggie
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    Dynamically downscaled CMIP5 climate projection data for Minnesota
    (2022-01-25) Liess, Stefan; Twine, Tracy E; Snyder, Peter K; Hutchison, William D; Konar-Steenberg, Gabriel; Keeler, Bonnie L; Brauman, Kate A; liess@umn.edu; Liess, Stefan
    This dataset contains climate projections over Minnesota at 10 km horizontal resolution. Eight CMIP5 global climate models have been dynamically downscaled with the regional WRF model for the periods 1980-1999, 2040-2059, and 2080-2099, with the latter being represented as a moderate (RCP4.5) and also as an extreme "business as usual" scenario (RCP8.5). The projections suggest ongoing warming in all seasons, especially in winter, as well as reduced snow depth and fewer days with snow cover. Significant increases in spring and early summer heavy precipitation events are expected. The other variables in this dataset are daily max. and min. temperatures, relative humidity, latent heat flux (as proxy for evaporation), sensible heat flux, ground heat flux, incoming solar radiation, total radiation, snow depth, and wind speed. Temperatures, precipitation, and snow depth are also available as bias adjusted. Results indicate a climate near the end of the 21st century that is significantly different from what has been observed by the end of the 20th century. Winters and summers are expected to be up to 6C and 4C warmer, respectively, and spring precipitation may increase by more than 1 mm per day over northern Minnesota. Winter snow depth is projected to decrease by more than 12 cm and the number of days per year with snow depth of more than 2.54 cm (one inch) is expected to decrease by up to 55. These results are expected to influence regional decision-making related to agriculture, infrastructure, water resources, and other sectors.
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    Temperature Observations of the Twin Cities Canopy-Layer Urban Heat Island
    (2024-10-10) Smoliak, Brian V; Snyder, Peter K; Twine, Tracy E; Mykleby, Phillip M; Hertel, William F; Liess, Stefan; liess@umn.edu; Liess, Stefan; Department of Soil, Water, and Climate
    Data from a dense urban meteorological network (UMN) are analyzed, revealing the spatial heterogeneity and temporal variability of the Twin Cities (Minneapolis–St. Paul, Minnesota) canopy-layer urban heat island (UHI). Data from individual sensors represent surface air temperature (SAT) across a variety of local climate zones within a 5000-km2 area and span the 3-yr period from 1 August 2011 to 1 August 2014. Irregularly spaced data are interpolated to a uniform 1-km x 1-km grid using two statistical methods: 1) kriging and 2) cokriging with impervious surface area data. The cokriged SAT field exhibits lower bias and lower RMSE than does the kriged SAT field when evaluated against an independent set of observations. Maps, time series, and statistics that are based on the cokriged field are presented to describe the spatial structure and magnitude of the Twin Cities metropolitan area (TCMA) UHI on hourly, daily, and seasonal time scales. The average diurnal variation of the TCMA UHI exhibits distinct seasonal modulation wherein the daily maximum occurs by night during summer and by day during winter. Daily variations in the UHI magnitude are linked to changes in weather patterns. Seasonal variations in the UHI magnitude are discussed in terms of land-atmosphere interactions. To the extent that they more fully resolve the spatial structure of the UHI, dense UMNs are advantageous relative to limited collections of existing urban meteorological observations. Dense UMNs are thus capable of providing valuable information for UHI monitoring and for implementing and evaluating UHI mitigation efforts.