Published September 29, 2025 | Version 1.0.0
Dataset Open

Atmospheric downward longwave irradiance (flux) calculated using PASTICHE (the PaRaMetriC Atmospheric Spectral Tool for Irradiance Calculation using Hourly ERA5 data)

  • 1. ROR icon Istituto Nazionale di Ottica
  • 2. Istituto Nazionale di Ricerca Metrologica - INRIM

Description

This dataset is theresult of the project 21GRD03 PaRaMetriC, Work Package 2, Task 2.2. PaRaMetriC is a metrological framework for passive radiative cooling technologies developed as a Joint Research Project within the European Partnership on Metrology Programme.

The dataset contains downward longwave irradiance (flux) calculated using  using PASTICHE (the PaRaMetriC Atmospheric Spectral Tool for Irradiance Calculation using Hourly ERA5 data).

PASTICHE uses atmospheric states derived from ERA5 reanalysis (Hersbach, 2023) and computed via RRTM_LW (Mlawer, 1997). Fluxes are calculated over 16 contiguous longwave (infrared) spectral bands from 3–1000 μm wavelength.

ERA5 data points are defined on a regular latitude–longitude grid at 0.25° resolution and 37 fixed pressure levels.

The output fluxes are defined over the time, latitude, longitude, and lw_bands dimensions.

Available datasets

TMY

  • Denver, USA – 9 points (3 lat × 3 lon), 12 months, hourly
  • Las Vegas, USA – 9 points (3 lat × 3 lon), 12 months, hourly
  • Madrid, Spain – 20 points (4 lat × 5 lon), 12 months, hourly
  • Paris, France – 4 points (2 lat × 2 lon), 12 months, hourly
  • Rome, Italy – 4 points (2 lat × 2 lon), 12 months, hourly
  • Turin, Italy – 4 points (2 lat × 2 lon), 12 months, hourly
  • Singapore – 9 points (3 lat × 3 lon), 12 months, hourly
  • Tokyo, Japan – 9 points (3 lat × 3 lon), 12 months, hourly

June, July, August (JJA) 2023

  • Las Vegas, USA – 9 points (3 lat × 3 lon), 3 months (JJA), hourly
  • Madrid, Spain – 20 points (4 lat × 5 lon), 3 months (JJA), hourly
  • Riyadh, Saudi Arabia – 9 points (3 lat × 3 lon), 3 months (JJA), hourly
  • Turin, Italy – 4 points (2 lat × 2 lon), 3 months (JJA), hourly

Continental Europe

  • France – 21 lat × 21 lon (5.25° × 5.25°), 2019–2023, 6-hourly
  • Spain – 21 lat × 21 lon (5.25° × 5.25°), 2019–2023, 6-hourly

Two Days over 35 Years

  • Lleida, Spain – 4 points (2 lat × 2 lon), 31 July & 1 August, 1989–2023, hourly
  • Sesto Fiorentino, Italy – 12 points (3 lat × 4 lon), 31 July & 1 August, 1989–2023, hourly

 

Data Structure

Each NetCDF4 file contains the following calculated variables:

  • sd(time, latitude, longitude, lw_bands) – RRTM-calculated surface downward longwave radiation flux (W·m⁻²)
  • su(time, latitude, longitude, lw_bands) – Surface upward longwave radiation flux (W·m⁻²)
  • sn(time, latitude, longitude, lw_bands) – Surface net longwave radiation flux (W·m⁻²)
  • tu(time, latitude, longitude, lw_bands) – TOA upward longwave radiation flux (W·m⁻²)
  • r(time, latitude, longitude) – Relative humidity calculated from 2 m temperature and dewpoint (%)
 

Note

  • Band 0 contains total infrared flux; bands 1–16 represent spectral subdivisions.
  • Band limits are stored in lw_band_limits (cm⁻¹).

The following fields are copied directly from ERA5:

  • t2m – 2 m temperature
  • skt – Skin temperature
  • cbh – Cloud base height
  • tcc – Total cloud cover (as cloud_area_fraction)
  • tcwv – Total column vertically integrated water vapour
  • u10, v10 – 10 m wind components
  • stl3, stl4 – Soil temperatures at levels 3 and 4
  • avg_sdlwrf, avg_sdlwrfcs – Time-averaged surface downward LW radiation flux (all-sky / clear-sky)
  • avg_sdswrf, avg_sdswrfcs – Time-averaged surface downward SW radiation flux
  • avg_snlwrf, avg_snlwrfcs – Time-averaged surface net LW radiation flux
  • avg_snswrf, avg_snswrfcs – Time-averaged surface net SW radiation flux
  • avg_tnlwrf, avg_tnlwrfcs – Time-averaged TOA net LW radiation flux
 

Warning

  • ERA5 fluxes are accumulated over one hour and normalized by 3600 s. We treat these as instantaneous values centered at t – 0.5 h.
  • ERA5 fluxes correspond to total LW radiation and should be compared to band 0 values from RRTM.
  • NaN values may appear over sea regions or where RRTM fails (e.g., north-west corner of the France dataset); further investigation is ongoing

 

Funding

This work is supported by the European project PaRaMetriC, code 21GRD03. The project 21GRD03 PaRaMetriC received funding from the European Partnership on Metrology, co-financed by the European Union’s Horizon Europe Research and Innovation Programme, and from the Participating States.

Files

wp2_data.zip

Files (880.6 MB)

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Additional details

Software

Repository URL
https://github.com/21grd03-parametric/pastiche/
Programming language
Python

References

  • Mayer, J., Haimberger, L., and Mayer, M.: A quantitative assessment of air–sea heat flux trends from ERA5 since 1950 in the North Atlantic basin, Earth Syst. Dynam., 14, 1085–1105, https://doi.org/10.5194/esd-14-1085-2023, 2023.
  • Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough (1997), Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res., 102(D14), 16663–16682, doi:10.1029/97JD00237.