November 2021 DATA OVERVIEW Global High Resolution Daily Extreme Urban Heat Exposure (UHE-Daily), 1983-2016 Cascade Tuholske, cascade@ciesin.columbia.edu HISTORY Updated Feb 25 2021 by CPT Updated April 21 2021 by CPT Updated Aug 10 2021 by CPT Updated Oct 21 2021 by CPT Final Nov 16 2021 by CPT REFERENCES Reference for methods: Tuholske, C., K. Caylor, C. Funk, A. Verdin, S. Sweeney, K. Grace, P. Peterson, and T. Evans. 2021. Global Urban Population Exposure to Extreme Heat. Proceedings of the National Academy of Sciences 118(41), e2024792118. https://doi.org/10.1073/pnas.2024792118. Reference for data: Tuholske, C., K. Caylor, C. Funk, A. Verdin, S. Sweeney, K. Grace, P. Peterson, and T. Evans. 2021. Global High Resolution Daily Extreme Urban Heat Exposure (UHE-Daily), 1983-2016. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/fq7g-ny13. Accessed DAY MONTH YEAR. Notes: 1. The lat/long coordinates in the .csv and .json files are unprojected WGS84 geographic coordinate system (GCS). 2. The .shp files are projected using EPSG:4326 (WGS84) coordinate reference system (CRS). 3. For more information on GCS versus CRS see: https://www.esri.com/arcgis-blog/products/arcgis-pro/mapping/gcs_vs_pcs/ 4. Columns in the .shp and .csv files that should be lists and/or float in the .json file were converted to strings and will need to be converted back for analysis. -------------------------------------------------------------------------------------------------------------------------------------------------------------------- Each zip file contains the following files following a common naming convention: wbgtmax28* -- One day or longer events where WBGT > 28 C following ISO guidelines wbgtmax30* -- One day or longer events where WBGT > 30 C following ISO guidelines *** This is the data set used in the PNAS paper wbgtmax32* -- One day or longer events where WBGT > 32 C following ISO guidelines himax461* -- One day or longer events where HI > 46.1 C following National Weather Service guidelines himax406_2d* -- Two day or longer events where HI > 40.6 C following National Weather Service guidelines Each of the above have the following extensions as either .json or .csv files (see columns below). *STATS - these are the statistics for each event (e.g. duration, intensity, etc.) *EXP - these are the annual exposure for each event (population X days/year) *TREND_ALL - these are trend coef with all the data *TREND_PDAYS05 - these are trend coef for all date where pdays is sig at 0.05 (e.g. exposure trend) *TREND_HEATP05 - these are trend coef for all date where heat is sig at 0.05 (increase in hot days per year trend) -------------------------------------------------------------------------------------------------------------------------------------------------------------------- Column Names for files: All IDs from ID_HDC_G0 columns can be mapped to the polygons and data from the Global Human Settlement Layer Urban Centers Database (GHS-UCDB) found: https://ghsl.jrc.ec.europa.eu/ghs_stat_ucdb2015mt_r2019a.php *TREND* | These files are the exposure trends (annual rate of change in exposure in person-days per year) --------------------------------------------------------------------------------------------------------- ID_HDC_G0 - CITY ID coef_pdays - slope of exposure increase (person-days per year) p_value_pdays - p value coef_heat - slope of exposure due to heat (person-days per year) p_value_heat - p value coef_pop - slope of exposure due to pop growth (person-days per year) p_value_pop - p value coef_totDays - slope of increase in hot days (e.g. days per year WBGT > 28) p_value_totDays - p value coef_attrib - coef of if the exposure trend is due to population or urban warming (ask me) coef_attrib_norm - normalized above (ask me) CTR_MN_NM - Country Name UC_NM_MN - City name (these are a little janky) GCPNT_LAT - gps lat GCPNT_LON - gpd long region - UN region sub-region - UN sub-region intermediate-region - UN intermediate-region P1983 - Pop 1983 P2016 - Pop 2016 *STATS* | These files are the statistics for each extreme heat event in the data set as defined above ----------------------------------------------------------------------------------------------------- ID_HDC_G0 - CITY ID year - Year duration - how long was the event (days) avg_temp - avg temp of event avg_intensity - avg temp above threshold tot_intensity - total excess heat event_dates - dates of the event (reads as list with json) intensity - intensity of events daily (reads as list with json) tmax - tempatures of events daily (reads as list with json) UID - unique ID for each event (I made these) CTR_MN_NM - Country Name UC_NM_MN - City name (these are a little janky) GCPNT_LAT - gps lat GCPNT_LON - gpd long region - UN region sub-region - UN sub-region intermediate-region - UN intermediate-region P1983 - Pop 1983 P2016 - Pop 2016 *EXP* | These files are the annual exposure metrics (person days per year), e.g. Mumbai 1998 is 100,000 person days ------------------------------------------------------------------------------------------------------------------- ID_HDC_G0 - CITY ID year - YEAR tot_days - Number of days that year event happened P - Population of city that year P1983 - Population in 1983 P2016 - Population in 2016 people_days - Person days (P x tot_days) people_days_heat - Person days due to heat (P1983 x tot_days) people_days_pop - Person days due to pop growth ((P - P1983) x tot_days) CTR_MN_NM - Country Name UC_NM_MN - City name (these are a little janky) GCPNT_LAT - gps lat GCPNT_LON - gpd long region - UN region sub-region - UN sub-region intermediate-region - UN intermediate-region P1983 - Pop 1983 P2016 - Pop 2016