Published December 11, 2025 | Version v1
Dataset Open

Italian coastal wave climate dataset — bias-adjusted reanalysis, hindcasts and EURO-CORDEX projections

Authors/Creators

  • 1. University of Naples Federico II
  • 2. ROR icon Sapienza University of Rome
  • 3. ROR icon University of Genoa

Description

Dataset Overview

This dataset provides bias-adjusted wave data for 15 buoy locations along the Italian coastline, together with bias-corrected historical and future wave projections. The dataset includes corrections applied to multiple reanalysis and model sources—ERA5, CMEMS, MeteOcean-UniGe 10 km regular grid, and MeteOcean-UniGe unstructured grid.

The MeteOcean-UniGe 10km regular and unstructured grid are produced by the MeteOcean research group of the University of Genova (www.meteocean.science), providing wave information with different resolution for the Mediterranean Sea using the third-generation wave model Wavewatch III. 

CMEMS dataset: This database contains raw reanalysis data provided by E.U. Copernicus Marine Service Information; https://doi.org/10.48670/mds-00376.
This database contains modified reanalysis data generated using E.U. Copernicus Marine Service Information; https://doi.org/10.48670/mds-00376.

ERA5: This database contains raw reanalysis data provided by Copernicus Climate Change Service; https://doi.org/10.24381/cds.adbb2d47. 
This database contains modified Copernicus Climate Change Service information. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

 

Station ERA5
reanalysis		 ww3-10km
hindcast/projections		 ww3-unst
hindcast		 CMEMS
reanalysis
Lon [°E] Lat [°N] Lon [°E] Lat [°N] Lon [°E] Lat [°N] Lon [°E] Lat [°N]
LA SPEZIA 9.75 44.00 9.89 43.95 9.82 43.93 9.83 43.93
CAPOMELE 8.25 43.75 8.23 43.86 8.18 43.92 8.20 43.93
ALGHERO 8.00 40.50 8.11 40.53 8.00 40.56 8.00 40.52
CROTONE 17.25 39.00 17.28 39.00 17.29 38.95 17.25 39.02
CAGLIARI 9.25 39.00 9.38 39.09 9.45 39.11 9.50 39.10
MAZARA 12.50 37.50 12.44 37.47 12.53 37.52 12.54 37.52
MONOPOLI 17.50 41.00 17.40 40.98 17.41 40.99 17.37 40.97
CIVITAVECCHIA 11.50 42.00 11.67 42.15 11.68 42.14 11.58 42.27
ORTONA 14.50 42.50 14.60 42.42 14.53 42.37 14.54 42.43
ANCONA 13.75 43.75 13.71 43.77 13.70 43.79 13.75 43.85
CETRARO 15.75 39.50 15.87 39.45 15.75 39.50 15.91 39.48
CESENATICO 12.50 44.25 12.56 44.22 12.48 44.22 12.50 44.22
PONZA 12.75 40.75 12.94 40.80 12.95 40.86 12.95 40.89
CATANIA 15.50 38.00 15.25 37.47 15.59 38.10 15.16 37.48
PALERMO 13.25 38.25 13.46 38.19 13.45 38.18 13.33 38.27

 

The bias adjustment is performed, for the significant wave height (Hs), using the DM-seasonal method (Distribution Mapping by seasons) with a mixed distribution approach, employing an extreme-value-tail distribution to improve the representation of storm extremes. The corrected MeteOcean-UniGe 10 km dataset is then used as a reference to correct historical (baseline) and future (RCP8.5) simulations from 21 EURO-CORDEX RCM–GCM combinations.

Additionally, the dataset includes results of a Bivariate Dynamical Optimal Transport Correction (dOTC) applied jointly to significant wave height (Hs) and peak period (Tp) for the MeteOcean-UniGe 10 km grid, together with the corresponding bias-corrected projections for all 21 climate models.

This dataset supports coastal climate-impact studies, wave climate assessment, and long-term hazard projections along the Italian coasts.

Data Structure

The dataset is provided as a collection of ZIP archives, each containing text files (.txt) corresponding to the processed time series.

All ZIP files follow the structure:

<data>_<model>.zip

Where:

<data>

  • raw

  • bias-adj-Hs-DMseasonal

  • bias-adj-Hs_Tp-dOTC

<model>

  • CMEMS

  • ERA5

  • hindcast_MeteOcean-UniGe-ww3-10km

  • hindcast_MeteOcean-UniGe-ww3-unst

  • projections_MeteOcean-UniGe-ww3-10km

 

Raw data ZIP archives

  • raw_ERA5.zip

  • raw_CMEMS.zip

  • raw_hindcast_MeteOcean-UniGe-ww3-10km.zip

  • raw_hindcast_MeteOcean-UniGe-ww3-unst.zip

  • raw_projections_MeteOcean-UniGe-ww3-10km.zip

 

Each hindcast ZIP contains 15 .txt files, one per buoy location. The projections ZIP contains two folders:

baseline-1970-2005/
rcp85-2006-2100/

Each folder contains 315 .txt files (= 15 locations × 21 RCM–GCM models).

 

DM-seasonal bias-adjusted (Hs) ZIP archives

  • bias-adj-Hs-DMseasonal_CMEMS.zip

  • bias-adj-Hs-DMseasonal_ERA5.zip

  • bias-adj-Hs-DMseasonal_hindcast_MeteOcean-UniGe-ww3-10km.zip

  • bias-adj-Hs-DMseasonal_hindcast_MeteOcean-UniGe-ww3-unst.zip

  • bias-adj-Hs-DMseasonal_projections_MeteOcean-UniGe-ww3-10km.zip

Hindcast ZIPs: 15 .txt files. Projections ZIP: two folders (baseline, rcp85), each with 315 .txt files

 

dOTC bivariate Hs–Tp ZIP archives

  • bias-adj-Hs_Tp-dOTC_hindcast_MeteOcean-UniGe-ww3-10km.zip

  • bias-adj-Hs_Tp-dOTC_projections_MeteOcean-UniGe-ww3-10km.zip

Hindcast: 15 .txt files. Projections: two folders, each with 315 .txt files

 

File format description

Each .txt file includes:

  • a header listing variables, units, and metadata

  • time series of:

    • timestamps

    • Hs (DM-seasonal and dOTC)

    • Tp (dOTC only)

    • additional variables for raw data (e.g., mean wave period and wave direction)

Files

bias-adj-Hs-DMseasonal_CMEMS.zip

Files (3.7 GB)

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md5:9ca4a17d9276c8af5e7673e43bc7b36d
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Additional details

Funding

European Union
RETURN Extended Partnership, funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005)
Ministero dell'università e della ricerca
FOCUSMed project - Young Researchers Seal of Excellence grant

References

  • Besio, G., Mentaschi, L., and Mazzino, A.: Wave energy resource assessment in the Mediterranean Sea on the basis of a 35-year hindcast,450 Energy, 94, 50–63, https://doi.org/10.1016/j.energy.2015.10.044, 2016.
  • Lira-Loarca, A., Cáceres-Euse, A., De-Leo, F., and Besio, G.: Wave modeling with unstructured mesh for hindcast, forecast and wave hazard applications in the Mediterranean Sea, Applied Ocean Research, 122, 103 118, https://doi.org/https://doi.org/10.1016/j.apor.2022.103118, 2022. 63
  • De Leo, F., Besio, G., and Mentaschi, L.: Trends and variability of ocean waves under RCP8.5 emission scenario in the Mediterranean Sea, Ocean Dynamics, 71, https://doi.org/10.1007/s10236-020-01419-8, 2021.
  • Lira Loarca, A., Berg, P., Baquerizo, A., and Besio, G.: On the role of wave climate temporal variability in bias correction of GCM-RCM wave simulations, Climate Dynamics, 61, 3541–3568, 2023