Smoliak, Brian VSnyder, Peter KTwine, Tracy EMykleby, Phillip MHertel, William FLiess, Stefan2024-10-102024-10-102024-10-10https://hdl.handle.net/11299/265910A. Filename: README.txt Short description: Readme file with detailed information on the datasets B. Filename: Instrument.zip Short description: Direct measurements as Level0 (measurements downloaded as CSV files), Level1 (converted to netCDF format), and Level2 (removing outliers, calculating daily and hourly average values) C. Filename: Grid.zip Short description: Data in netCDF format interpolated to 1-km x 1-km regular grids using kriging and alternatively co-kriging methodsData 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.Attribution-NonCommercial-NoDerivs 3.0 United Stateshttp://creativecommons.org/licenses/by-nc-nd/3.0/us/Urban Heat IslandMinneapolisSaint PaulTwin CitiesClimate ChangeGlobal WarmingKrigingCokrigingUrban canopy temperatureDatasethttps://doi.org/10.13020/r4pc-4x10