DOI: 10.5281/zenodo.17849682
title: SCOPE-ERA5: Station-Calibrated Outputs for Planning & Engineering-ERA5

description: SCOPE-ERA5 (Station-Calibrated Outputs for Planning & Engineering-ERA5) is a global, observationally calibrated daily resolution version of ERA5 at the location of weather stations. This dataset uses a multivariate bias adjustment method (MBCn; Cannon et al., 2018) to correct key ERA5 thermodynamic variables—such as near-surface air temperature, humidity, pressure—and wind speed based on daily observations from more than 7,100 weather stations around the world. SCOPE-ERA5 was developed by Degree Day LLC, an independent provider of climate risk analytics research (https://www.degreeday.org).

SCOPE-ERA5 provides temporally complete, thermodynamically consistent daily time series that better reflect observed local conditions compared to raw ERA5 at weather station locations. It is designed for use in applications requiring local accuracy, such as engineering design, and energy systems modeling, and other climate risk assessment purposes. Additional technical details are provided in the supporting article: 10.22541/essoar.175130623.32640121/v1

This Zenodo deposit includes both the full SCOPE-ERA5 daily timeseries dataset (restricted) and a subset covering only stations in the United Kingdom (unrestricted). The full dataset is available for non-commercial use. Each station’s data is provided in an individual NetCDF file and includes metadata such as station name, location, elevation, country, and nearest major city. This Zenodo deposit also includes several climatological indicators calculated from SCOPE-ERA5 daily timeseries at the full record of weather stations.

Key Features:



Bias-adjusted ERA5 data using observed daily station records (1979–2024).

Use of a multivariate correction that preserves inter-variable physical relationships. 

Daily timeseris available for >7,100 stations globally

Variables include: temperature (tas, tasmax, tasmin), dew point (dew_point), relative humidity (hurs), specific humidity (huss), wet-bulb temperature (wet_bulb), heat index (heat_index), wind speed (sfcWind), wind chill index (wind_chill), surface pressure (ps), shortwave radiation (rsds), clear sky shortwave radiation (rsdscs), and more.

Format: NetCDF4 and MS Excel; one file per station.


More Details:

The set of available variables differs by weather station, since not all stations recorded each of the six foundational variables (from which other variables were derived) or met the required data completeness thresholds. To balance data quality with spatial coverage, stations were grouped into three hierarchical categories, each representing a different "package" of up to six coincident foundational variables, depending on data completeness and station data homogenization.

Category 1 stations (N = 397) met completeness criteria for dry-bulb temperature alone.Category 2 stations (N = 2,878) additionally included complete records of relative humidity.Category 3 stations (N = 3,840) further required complete 10-meter surface wind speed observations.




Category
Number of Stations
Foundational Variables Available (Field Names)


Category 1
397
Dry-bulb temperature (tas), maximum temperature (tasmax), minimum temperature (tasmin)


Category 2
2,878
Dry-bulb temperature (tas), maximum temperature (tasmax), minimum temperature (tasmin), relative humidity (hurs), surface pressure (ps)


Category 3
3,840
Dry-bulb temperature (tas), maximum temperature (tasmax), minimum temperature (tasmin), relative humidity (hurs), 10-meter surface wind speed (sfcWind), surface pressure (ps)




 

Included Supplemental and Derived Variables:

The table below is an overview of climate variables available in the dataset by category. 




Variable Long Name
Field Name
Units
Dataset Category Availability


Mean Dry-Bulb Temperature
tas
K
1, 2, 3


Maximum Dry-Bulb Temperature
tasmax
K
1, 2, 3


Minimum Dry-Bulb Temperature
tasmin
K
1, 2, 3


Diurnal Dry-Bulb Temperature Range
dtr
K
1, 2, 3


Diurnal Dry-Bulb Temperature Skewness
tasskew
[0‚1]
1, 2, 3


Mean Surface Downwelling Shortwave Radiation
rsds
W m-2
1, 2, 3


Mean Surface Pressure
ps
Pa
2, 3


Mean Relative Humidity
hurs
[0‚1]
2, 3


Minimum Relative Humidity
hursmin
[0‚1]
2, 3


Maximum Relative Humidity
hursmax
[0‚1]
2, 3


Mean Dew Point Temperature
dew_point
K
2, 3


Mean Specific Humidity
huss
[0‚1]
2, 3


Mean Wet-Bulb Temperature
wet_bulb
K
2, 3


Maximum Wet-Bulb Temperature
wet_bulb_max
K
2, 3


Mean NWS Heat Index Temperature
heat_index
°C
2, 3


Maximum NWS Heat Index Temperature
heat_index_max
°C
2, 3


Mean 10-m Surface Wind Speed
sfcWind
m/s
3


Mean Wind Chill
wind_chill
°C
3




The included *.csv files provide metadata for weather stations used in the dataset (subset and full dataset). Each row corresponds to a unique station, and the columns are defined as follows:





Station_ID: Unique identifier assigned to each station in the dataset (typically a concatenation of WMO and WBAN codes if available).




Category: Station category based on data completeness and availability (e.g., Category 1, 2, or 3), indicating which variables are available and meet quality criteria.




Lat: Latitude of the station in decimal degrees (positive for North, negative for South).




Lon: Longitude of the station in decimal degrees (positive for East, negative for West).




Elevation: Elevation of the station above mean sea level in meters.




WMO: World Meteorological Organization station ID, if available.




WBAN: U.S. Weather Bureau Army Navy (WBAN) station code, if available.




Station Name: Official station name, typically corresponding to the reporting airport, city, or region.




Country: Country where the station is located.




Province: State, province, or administrative region (if applicable).




City: Nearest city or urban center (if applicable).




County: County or district (if applicable).




Continent: Continent on which the station is located (e.g., North America, Asia).




Subregion: More specific geographic region within the continent (e.g., Southeast Asia, Western Europe).




Train_start: First year of the 20-year period used for bias adjustment training at the station.




Train_end: Last year of the 20-year training period.



 

Climatological Indicators

Several climatological indicators have been derived from the daily data from SCOPE-ERA5. These are described below and are available for download in this repository.

Energy-related Indicators




Field Name
Description




cdd_10c, cdd_18c



Cooling Degree Days with base 10°C (50°F) and 18.3°C (65°F); a proxy for cooling energy demand.





hdd_10c, hdd_18c



Heating Degree Days with base 10°C (50°F) and 18.3°C (65°F); a proxy for heating energy demand.





 

Heat-related Indicators




Field Name
Description




hw_thresh_day



Daytime heatwave threshold [the larger of: the 90th percentile of daily maximum temperature over climatological warmest 2 months (1985-2014) or 30°C (86°F)].





hw_thresh_night



Nighttime heatwave threshold [the larger of: the 90th percentile of daily minimum temperature over climatological warmest 2 months (1985-2014) or 20°C (68°F)].





hw_freq_day, hw_freq_night

Annual count of heatwave events, defined as periods of at least three consecutive days exceeding the threshold.




hw_mag_day, hw_mag_night



Maximum intensity of any heatwave per year as measured by the cumulative excess temperatures over the local heatwave threshold





hw_len_day, hw_len_night



Number of days exceeding the heatwave threshold per year (meething both duration and intensity thresholds).





warm_nights_20c, warm_nights_22c



Number of days per year where the daily minimum temperature exceeds 20°C (68°F) and 22°C (72°F).





tx_above90f, tx_above95f



Number of days per year with max temperature above 90°F (32°C) and 95°F (35°C).





hi_days_90f, hi_days_103f, hi_days_125f



Number of days per year with NWS Heat Index in Extreme Caution (>90°F), Danger (>103°F), and Extreme Danger (>125°F) categories.





 

Cold-related Indicators




Field Name
Description




cw_thresh



Coldwave threshold [the lower of: the 15th percentile of daily average temperature over the climatological coldest 2 months (1985-2014) or -10°C (14°F)]





cw_freq



Number of cold wave events per year.





cw_len



Total number of cold wave days per year.





wc_days_m25c, wc_days_m40c



Number of days per year with Wind Chill Index below -25°C (-13°F) and -40°C (-40°F).





tn_below0c



Number of days per year with daily minimum temperature below 0°C (32°F)





ft_freq



Number of freeze-thaw cycles per year (days where daily maximum temperature > 0°C and daily minimum temperature < 0°C)





ft_len



Mean length of freeze-thaw events (consecutive days meeting the freeze-thaw criteria)





 

Wind and Solar-related Indicators




Field Name
Description




windy_days



Number of days per year with daily mean surface wind speed ≥ 10.8 m/s (Beaufort 6 or higher).





calm_days



Number of days per year with daily mean surface wind speed < 2 m/s.





ci_very_cloudy, ci_cloudy, ci_sunny



Number of days per year in clearness index categories: <0.4, 0.4–0.6, >0.6.





Version History:



V1.1-complete (2025-12-07)



Initial Release of the full SCOPE-ERA5 daily timeseries






V1.1-subset (2025-12-07)



Updates:



Added separate tracking of daytime and nighttime heatwaves to capture locations experiencing divergent trends (e.g., increasing nighttime heat stress without corresponding daytime changes)

Fixed calculation error in coldwave and freeze-thaw cycle indicators



Format change: NetCDF (.nc) format discontinued for climatological indictors. All future releases will use Excel (.xlsx) format only for indicators.

Note: UK daily timeseries data unchanged from previous version.






V1.0-subset (2025-06-30)



Initial Release




How to cite the dataset:

Rasmussen, D. J. (2025). SCOPE-ERA5: Station-Calibrated Outputs for Planning & Engineering-ERA5 (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3735533

How to cite the Methodology: 

Rasmussen, D.J. (2025). Multivariate Bias Correction of ERA5 Using in situ Observations for Planning and Engineering. ESSOAr. 10.22541/essoar.175130623.32640121/v1