This Extreme Thermal Event Library provides comprehensive records of heat wave and cold snap events from 1980 to 2019, aggregated at the North American Electric Reliability Corporation (NERC) subregion level for the conterminous United States. A map of NERC subregions with county-level mean temperatures is included in the file 'NERC_subregions_with_mean_temperature.tif'.

The heat wave and cold snap events were identified using temperature data simulated by the Thermodynamic Global Warming (TGW) model. The raw TGW hourly temperature data (at a 12-km resolution) was aggregated to the county level using spatial averaging within county boundaries. Daily mean, maximum, and minimum temperatures were then derived from the hourly surface air temperature data for each county. Subsequently, the county-level daily temperatures were spatially aggregated to the NERC subregion level using three distinct spatial aggregation methods:

1. Simple Mean (SM): A simple average of county-level temperatures.
2. Area-Weighted Mean (MWA): Weighted by the area of each county.
3. Population-Weighted Mean (MWP): Weighted by the population of each county.

The database includes separate zipped files for each spatial aggregation method:

• "heat_wave_library_NERC_average.zip" and "cold_snap_library_NERC_average.zip" contain events based on the SM method.
• "heat_wave_library_NERC_average_area.zip" and "cold_snap_library_NERC_average_area.zip" contain events based on the MWA method.
• "heat_wave_library_NERC_average_pop.zip" and "cold_snap_library_NERC_average_pop.zip" contain events based on the MWP method.

Each zipped file includes 12 event libraries, corresponding to 12 different event definitions. Details about these definitions are provided in the file 'Event definitions.docx'.

Event Library Structure

Each row in an event library represents one detected thermal event. The columns in the library are defined as follows:

• start_date: Start date of the event.
• end_date: End date of the event.
• centroid_date: The centroid date, calculated as the midpoint between the start and end dates.
• highest_temperature / lowest_temperature: The highest daily maximum temperature (for heat waves) or lowest daily minimum temperature (for cold snaps), in Kelvin.
• duration: Duration of the event in days.
• NERC_ID: Identifier for the NERC subregion.
• spatial_coverage: The spatial coverage of the event within the NERC subregion, expressed as the percentage of counties experiencing the event relative to the total number of counties in the subregion.

Description

This dataset contains hourly data on the traffic volume for westbound I-94, a major interstate highway in the US that connects Minneapolis and St Paul, Minnesota. The data was collected by the Minnesota Department of Transportation (MnDOT) from 2012 to 2018 at a station roughly midway between the two cities.

Key Features

• holiday: a categorical variable that indicates whether the date is a US national holiday or a regional holiday (such as the Minnesota State Fair).
• temp: a numeric variable that shows the average temperature in kelvin.
• rain_1h: a numeric variable that shows the amount of rain in mm that occurred in the hour.
• snow_1h: a numeric variable that shows the amount of snow in mm that occurred in the hour.
• clouds_all: a numeric variable that shows the percentage of cloud cover.
• weather_main: a categorical variable that gives a short textual description of the current weather (such as Clear, Clouds, Rain, etc.).
• weather_description: a categorical variable that gives a longer textual description of the current weather (such as light rain, overcast clouds, etc.).
• date_time: a datetime variable that shows the hour of the data collected in local CST time.
• traffic_volume: a numeric variable that shows the hourly I-94 reported westbound traffic volume.

Potential Use Cases

The dataset can be used for regression tasks to predict the traffic volume based on the weather and holiday features. It can also be used for exploratory data analysis to understand the patterns and trends of traffic volume over time and across different conditions.