Select the state of interest, then the county or counties of interest. You may select up to five unique counties to compare.
Introduction
This tool provides annual county-level data and trends for unique minimum temperature (Tmin) variables across the conterminous United States from 1951–near present. The tool was developed to complement our Temperature Trends Dashboard (https://scipprisa.shinyapps.io/SCIPP_temp_dash/) but focuses on minimum temperatures, which, for many regions, are changing more than local average (Tavg) and maximum (Tmax) temperature. This tool uses a gridded dataset (nClimGrid-Daily) because gridded fields tend to be more representative of spatial patterns and produce more accurate regional or county averages when aggregated spatially.
Features
There are four variables to choose from that are all annually summarized at the county level. First, Freeze Days represents the count of days where the county-wide minimum temperature was at or below 32°F (0°C). Second, the Coldest Minimum Temperature , which represents the single coldest county-wide minimum temperature annually (this variable occurs during winter). Third, the Warmest Minimum Temperature represents the single warmest average county-wide minimum temperature annually (this variable occurs during summer). Finally, a user-defined Minimum Temperature Threshold enables users to select a minimum temperature and view the count of days a particular county experienced greater than or equal or lesser than or equal to the selected unique threshold each year. For example, if a user selects the "greater than equal to" condition and chooses 65°F and then clicks on East Baton Rouge Parish, Louisiana, a time series will be produced showing the annual count of days the county-wide average minimum temperature was at or above 65°F. For more information on the variables, data, and methods, please visit our Documentation Tab.
Instructions
To get started, click on the tool tab and then select the state of interest, then the county or counties of interest. You may select up to five unique counties to compare, which do not have to be within the same state. Below the time series plot, you can export an image or the annual data. To clear the plot, select the “Clear Plot” option below the “Download Image” and “Download CSV” buttons.
Source Data
Minimum temperature data are from nClimGrid-Daily (Durre et al., 2022). nClimGrid-D is a gridded dataset created by combining four station-based networks (Cooperative Observer Network (COOP), Automated Surface Observing Systems (ASOS), Snow Telemetry (SNOTEL), and Remote Automatic Weather Stations (RAWS)) with a resolution of approximately 0.0417° (nominally 5 km) and was designed for climate monitoring (Durre et al., 2022) by the National Centers for Environmental Information (NCEI). For more information on how nClimGrid-Daily is derived, please see Durre et al. (2022).
County-level shapefiles were obtained from the U.S. Census Bureau via the U.S. County Boundary Shapefile dataset (TIGER/Line; U.S. Census Bureau, 2022).
Durre, I., Arguez, A., Schreck III, C.J., Squires, M.F. and Vose, R.S., 2022. Daily high-resolution temperature and precipitation fields for the contiguous United States from 1951 to present. Journal of Atmospheric and Oceanic Technology, 39(12), pp.1837-1855.
TIGER/Line Shapefiles, (machinereadable data files) / prepared by the U.S. Census Bureau, 2021. https://www2.census.gov/geo/tiger/TIGER2021/COUNTY/
Methodology
To create unique, county-level time series, the County Boundary Shapefile was converted from vector format to grid, matching the size and extent of nClimGrid-D. County boundaries often extended into areas where nClimGrid-D data were unavailable, such as the areas over large bodies of water. When converting the County Boundary shapefile to a grid, areas where nClimGrid-D data did not exist were ignored. For example, county time series around the Great Lakes (e.g., Ottawa County, MI), whose border extends over water in the Census Bureau’s shapefile, only represent non-water portions of the county. Areas where the resulting grid cell overlapped more than one county were assigned to the county in which the center of the grid cell was located. Data was processed in Python using the ArcPy module for geospatial analysis and the Pandas module for tabular analysis. All annual time series span January 1st to December 31st for each year.
To test for trends in the above-mentioned series, Ordinary Least Square (OLS) regression is used. OLS regression provides parameter estimates that quantify how variables change during a period when the independent variable is time (year). Each parameter estimate is multiplied by ten to show the average rate of change per decade over the period of record (1951-near present).
Freeze Days
For a freeze day to occur within a county, ≥ 50% of the grid cells within a county were required to have a Tmin ≤ 0°C. All days within each year where ≥ 50% of the cells within a county experienced Tmin ≤ 0°C were summed to produce an annual time series.
Coldest and Warmest Minimum Temperature
The average county-wide coldest Tmin and warmest Tmin was calculated by averaging all cells within a county each day between January 1st and December 31st and extracting the single coldest daily Tmin and single warmest daily Tmin for every year for each county. The coldest minimum temperature represents the lowest average minimum temperature annually and generally occurs during winter. Conversely, the warmest minimum temperature represents the highest average minimum temperature annually and generally occurs during summer.
Minimum Temperature Threshold
This feature enables the user to input a unique minimum temperature (°F) and view the number of days per year greater than or equal to or lesser than equal to that threshold. This variable represents the count of days above or below a county-wide minimum temperature (average of all pixels within a county), different from freeze days and the coldest/warmest minimum temperature variables. First, select the "greater than or equal to" or "lesser than or equal to" condition and then choose the unique minimum temperature of interest. Note, that you can use the arrows in the “Enter Tmin Threshold (°F)” box to change the temperature as well. Next, select the county or counties of interest to view the annual time series.
Caveats
Gridded data like nClimGrid-Daily are not synonymous with station-based data. For example, station-based data are highly localized and do not represent areas well beyond their location. This is a key difference between this tool and our Temperature Trends Dashboard Tool. Additionally, station-based data generally have more variability (higher and lower extremes) than a grid. Grids are spatially averaged, which reduces variability. Tests were conducted to ascertain the strength of the association between stations within counties and derived county time series developed in this tool. Results showed, for most counties, a high degree of association; however, larger differences were found between stations west of the Rocky Mountains and stations near unique features (e.g., water bodies, topographic features, etc.). Please see Durre et al. (2022) for a more detailed explanation of potential differences between station and gridded data.
