Thermal comfort indices derived from ERA5 reanalysis
General description
This dataset, also called ERA5-HEAT (Human thErmAL comforT), provides modelled hourly data for a set of indices representing human thermal stress and discomfort in outdoor conditions. The dataset is organised around two main variables, the mean radiant temperature and the universal thermal climate index. These are calculated from environmental parameters (air temperature, humidity, wind speed, radiation) provided by ECMWF ERA5 reanalysis. The dataset is regularly extended with time as ERA5 data become available. The overall size of the dataset is 1.2TB.
A throughout description of the database can be found in:
Di Napoli C, Barnard C, Prudhomme C, Cloke HL and Pappenberger F (2020) ERA5-HEAT: A global gridded historical dataset of human thermal comfort indices from climate reanalysis. Geoscience Data Journal, https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/gdj3.102 |
Thermal comfort indices descriptions
Universal thermal climate index (UTCI): The UTCI is a state-of-the-art indicator that estimates the thermal stress the human body undergoes when exposed to outdoor conditions. The UTCI is an international standard developed by the European Cooperation in Science and Technology (COST) Action 730. It is defined as the air temperature of a reference outdoor environment that would elicit in the human body the same physiological response (sweat production, shivering, skin wettedness, skin blood flow and rectal, mean skin and face temperatures) as the actual environment.[1] Since its creation in 2009 the UTCI has been evaluated across different climate regions, from urban to global scales, as well as deployed as reference variable in weather forecasts and climate projections.
Mean radiant temperature (MRT): The MRT is the uniform temperature of a fictive black-body radiation enclosure which would result in the same net radiation energy exchange with a human subject as the actual, more complex radiation environment (Figure 1). The MRT is an international standard for thermal environment ergonomics according to the International Organization for Standardization.[2] It also a standard for thermal environmental conditions for human occupancy according to the American Society of Heating, Refrigerating and Air-Conditioning Engineers.[3]
Figure 1 Graphical explanation of the mean radiant temperature (MRT). Adapted from [4].
Summary variable table
Variable | Description | UNIT |
Mean radiant temperature | Numerical representation of how human beings experience radiation. It applies to a human subject placed in an outdoor environment and irradiated by solar and thermal radiation both directly and diffusely. | K |
Universal thermal climate index | Numerical representation of the thermal comfort/discomfort perceived by a human subject when exposed to outdoor conditions. It is based on a state-of-the-art model that simulates human body’s physiological responses to air temperature, humidity, wind speed and radiation. | K |
Thermal comfort indices algorithm
The dataset is computed via a sequence of well-defined, computer-automated steps (algorithm, Figure 2). The algorithm takes as input the following ERA5 reanalysis atmospheric variables: air temperature and relative humidity (from dew point temperature) at 2 meters above the ground, wind speed at 10 meters above ground level and radiation fluxes at the Earth’s surface. Radiation fluxes - both solar and thermal - are used to calculate the MRT by taking into account the time period in which modelled radiation is accumulated and the Sun’s position changes.[5] The MRT, air temperature, relative humidity and wind speed are input into a multi-variable equation which has the UTCI as a result.[6] The outputs of the algorithm (products) are hourly reanalysis data of MRT and UTCI at the global scale (except Antarctica).
Figure 2 Workflow of the thermal comfort indices algorithm.
Data Availability
The algorithm generates MRT and UTCI products as soon as reanalysis input data are released.
ERA5 data become available 2 to 3 months behind real time. The thermal comfort indices dataset produced from ERA5 (consolidated dataset) is uploaded into CDS and published every month.
Data Availability for ERA5 is from 19400101 until 2to3 months behind realtime.
The algorithm also produces a dataset from ERA5T. ERA5T is a preliminary dataset for ERA5 made available within five days from real time. The thermal comfort indices dataset produced from ERA5T (intermediate dataset) is updated and released on CDS within the same time period. It is worth remembering that MRT and UTCI products from ERA5T could differ from the corresponding ERA5-derived product when quality checks and consolidation occur.
Available Versions
Version 1.0 was released on 2020-01-15 and continued to provide data to the CDS until a bug as discovered following transition of the code to an alternate location.
Version 1.1 has been provided to overlap with the problematic dataset of Version 1.0.
Both Versions are scientifically identical, however the issue occurred during the translation of Grib to NetCDF for the CDS.
See Known Issues page.
File naming convention
File names are as follows:
PRODUCER_VARIABLE_DATE_Version_Dataset.nc
where:
- Producer: ECMWF
- Variable: UTCI or MRT
- Date: Date of the reanalysis
- Version: Version of the reanalysis
- Dataset:
- con: Consolidated ERA5 Data
- int: Intermediate ERA5 Data (ERA5T)
File Contents
Each file contains 24 timesteps at 0.25 resolution of the variable requested in netcdf4 format.
netcdf ECMWF_utci_20191202_v1.0_int {
dimensions:
time = UNLIMITED ; // (24 currently)
lon = 1440 ;
lat = 601 ;
variables:
double time(time) ;
time:standard_name = "time" ;
time:units = "hours since 2019-12-2 00:00:00" ;
time:calendar = "proleptic_gregorian" ;
time:axis = "T" ;
double lon(lon) ;
lon:standard_name = "longitude" ;
lon:long_name = "longitude" ;
lon:units = "degrees_east" ;
lon:axis = "X" ;
double lat(lat) ;
lat:standard_name = "latitude" ;
lat:long_name = "latitude" ;
lat:units = "degrees_north" ;
lat:axis = "Y" ;
float utci(time, lat, lon) ;
utci:code = 167 ;
utci:table = 128 ;
utci:missing_value = -9.e+33f ;
// global attributes:
:_NCProperties = "version=1|netcdflibversion=4.6.1|hdf5libversion=1.10.3" ;
:CDI = "Climate Data Interface version 1.9.5 (http://mpimet.mpg.de/cdi)" ;
:Conventions = "CF-1.6" ;
:history = "Wed Dec 04 12:53:43 2019: cdo -P 8 -z zip_1 -R -f nc4 -setname,utci -remapnn,lsm.nc utci.20191202.grib utci_20191202_v1.0_int.nc" ;
:institution = "European Centre for Medium-Range Weather Forecasts" ;
:CDO = "Climate Data Operators version 1.9.5 (http://mpimet.mpg.de/cdo)" ;
:cdo_openmp_thread_number = 8 ;
}
[1] Jendritzky G, de Dear R, Havenith G (2012) G. UTCI—Why another thermal index?, International Journal of Biometeorology 56:421. https://doi.org/10.1007/s00484-011-0513-7
[2] ISO 7726. Ergonomics of the thermal environment - Instrument for measuring physical quantities. Geneva, Switzerland: International Organization for Standardization. November 1998
[3] ANSI/ASHRAE Standard 55-2017, Thermal environmental conditions for human occupancy, ISSN 1041-2336
[4] Kántor N and Unger J (2011) The most problematic variable in the course of human-biometeorological comfort assessment — the mean radiant temperature, Central European Journal of Geosciences 3: 90. https://doi.org/10.2478/s13533-011-0010-x
[5] Di Napoli C, Hogan RJ, Pappenberger F (2020) Mean radiant temperature from global-scale numerical weather prediction models, International Journal of Biometeorology, https://doi.org/10.1007/s00484-020-01900-5
[6] Bröde P et al. (2012) Deriving the operational procedure for the Universal Thermal Climate Index (UTCI) International Journal of Biometeorology 56:481. https://doi.org/10.1007/s00484-011-0454-1
