Articles | Volume 22, issue 5
https://doi.org/10.5194/os-22-2809-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/os-22-2809-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Sep 2026
Research article |
| 14 Sep 2026
| 14 Sep 2026
Evaluation of a coupled regional reanalysis for the Mediterranean region covering the period 1993–2024
Institute of Marine Science (ISMAR), National Research Council (CNR), Rome, Italy
National Research Center for High Performance Computing, Big Data and Quantum Computing (ICSC), Bologna, Italy
Vincenzo de Toma
Institute of Marine Science (ISMAR), National Research Council (CNR), Rome, Italy
National Research Center for High Performance Computing, Big Data and Quantum Computing (ICSC), Bologna, Italy
Institute of Marine Science (ISMAR), National Research Council (CNR), Rome, Italy
National Research Center for High Performance Computing, Big Data and Quantum Computing (ICSC), Bologna, Italy
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Closing the sea‑level budget on annual and longer time scales is a cornerstone of physical oceanography because sea‑level rise is one of the best indicators of climate change, and a closed budget shows we have identified and quantified all major drivers. We examined it from 1993 to 2022, finding an accelerated rise that matched ice melt and warm water until 2015. Afterwards an unexplained gap appears. Better deep‑ocean observations and refined gravity processing are needed to close the budget.
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Short summary
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Scientists use programs, called Earth System Models, to study and predict climate. These models are based on physical theories but can be completed with AI tools. However, combining these tools with traditional models is difficult due to their different nature. Our research introduces a new method that connects these AI tools with existing climate models. We tested this method by integrating it with an ocean model. This work should help scientists explore new ways of making climate predictions.
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Short summary
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Inaccuracies in air–sea heat fluxes severely degrade the accuracy of ocean numerical simulations. Here, we use artificial neural networks to correct air–sea heat fluxes as a function of oceanic and atmospheric state predictors. The correction successfully improves surface and subsurface ocean temperatures beyond the training period and in prediction experiments.
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Present-day sea level rise is not uniform regionally. For better understanding of regional sea level variations, a classical approach is to compare the observed sea level trend patterns with those of the sum of the contributions. If the regional sea level trend budget is not closed, this allows the detection of errors in the observing systems. Our study shows that the trend budget is not closed in the North Atlantic Ocean and identifies errors in Argo-based salinity data as the main suspect.
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This study explores methods to reconstruct diurnal variations in skin sea surface temperature in a model of the Mediterranean Sea. Our new approach, considering chlorophyll concentration, enhances spatial and temporal variations in the warm layer. Comparative analysis shows context-dependent improvements. The proposed "chlorophyll-interactive" method brings the surface net total heat flux closer to zero annually, despite a net heat loss from the ocean to the atmosphere.
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Cited articles
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., and Arkin, P.: The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present), J. Hydrometeorol., 4, 1147–1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003.
Aydogdu, A., Miraglio, P., Escudier, R., Clementi, E., and Masina, S.: The dynamical role of upper layer salinity in the Mediterranean Sea, in: 7th edition of the Copernicus Ocean State Report (OSR7), edited by: von Schuckmann, K., Moreira, L., Le Traon, P.-Y., Grégoire, M., Marcos, M., Staneva, J., Brasseur, P., Garric, G., Lionello, P., Karstensen, J., and Neukermans, G., Copernicus Publications, State Planet, 1-osr7, 6, https://doi.org/10.5194/sp-1-osr7-6-2023, 2023.
Ballarotta, M., Ubelmann, C., Veillard, P., Prandi, P., Etienne, H., Mulet, S., Faugère, Y., Dibarboure, G., Morrow, R., and Picot, N.: Improved global sea surface height and current maps from remote sensing and in situ observations, Earth Syst. Sci. Data, 15, 295–315, https://doi.org/10.5194/essd-15-295-2023, 2023.
Beranová, R., Huth, R., and Vít, V.: A multidataset analysis of precipitation trends in Europe, J. Hydrometeorol., 26, 1003–1015, https://doi.org/10.1175/JHM-D-24-0114.1, 2025.
Bhargava, K., Kalnay, E., Carton, J. A., and Yang, F.: Estimation of systematic errors in the GFS using analysis increments, J. Geophys. Res.-Atmos., 123, 1626–1637, https://doi.org/10.1002/2017JD027423, 2018.
Brewin, R. J. W., Sathyendranath, S., Jackson, T., Barlow, R., Brotas, V., Airs, R., and Lamont, T.: Influence of light in the mixed-layer on the parameters of a three-component model of phytoplankton size class, Remote Sens. Environ., 168, 437–450, https://doi.org/10.1016/j.rse.2015.07.004, 2015.
Calafat, F. M., Chambers, D. P., and Tsimplis, M. N.: Mechanisms of decadal sea level variability in the eastern North Atlantic and the Mediterranean Sea, J. Geophys. Res.-Oceans, 117, C09022, https://doi.org/10.1029/2012JC008285, 2012.
Camus, P., Haigh, I. D., Nasr, A. A., Wahl, T., Darby, S. E., and Nicholls, R. J.: Regional analysis of multivariate compound coastal flooding potential around Europe and environs: sensitivity analysis and spatial patterns, Nat. Hazards Earth Syst. Sci., 21, 2021–2040, https://doi.org/10.5194/nhess-21-2021-2021, 2021.
Canuto, V. M., Howard, A., Cheng, Y., and Dubovikov, M. S.: Ocean turbulence. Part I: One-point closure model – momentum and heat vertical diffusivities, J. Phys. Oceanogr., 31, 1413–1426, 2001.
Craig, A. P., Valcke, S., and Coquart, L.: Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0, Geosci. Model Dev., 10, 3297–3308, https://doi.org/10.5194/gmd-10-3297-2017, 2017.
Cramer, W., Guiot, J., Fader, M., Garrabou, J., Gattuso, J.-P., Iglesias, A., Lange, M. A., Lionello, P., Llasat, M. C., Paz, S., Peñuelas, J., Snoussi, M., Toreti, A., Tsimplis, M. N., and Xoplaki, E.: Climate change and interconnected risks to sustainable development in the Mediterranean, Nat. Clim. Change, 8, 972–980, https://doi.org/10.1038/s41558-018-0299-2, 2018.
de Figueiredo, D. R., Bento, S., and Condesso de Melo, M. T.: Freshwater quality challenges in southern Europe under an increasingly warmer and drier climate scenario, Water, 17, 1873, https://doi.org/10.3390/w17131873, 2025.
Doury, A., Somot, S., Gadat, S., Ribes, A., and Corre, L.: Regional climate model emulator based on deep learning: concept and first evaluation of a novel hybrid downscaling approach, Clim. Dynam., 60, 1751–1779, https://doi.org/10.1007/s00382-022-06343-9, 2023.
Escudier, R., Clementi, E., Cipollone, A., Pistoia, J., Drudi, M., Grandi, A., Lyubartsev, V., Lecci, R., Aydogdu, A., Delrosso, D., Omar, M., Masina, S., Coppini, G., and Pinardi, N.: A high-resolution reanalysis for the Mediterranean Sea, Front. Earth Sci., 9, 702285, https://doi.org/10.3389/feart.2021.702285, 2021.
Fox-Hughes, P., Su, C.-H., Eizenberg, N., White, C., Steinle, P., Jakob, D., Black, M., Dowdy, A., Brown, A., Nathan, R., and Acharya, S. C.: A review of early severe weather applications of high-resolution regional reanalysis in Australia, Meteorol. Appl., 29, e2087, https://doi.org/10.1002/met.2087, 2022.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Giorgi, F. and Lionello, P.: Climate change projections for the Mediterranean region, Global Planet. Change, 63, 90–104, 2008.
González-Hidalgo, J. C. and Vicente-Serrano, S. M.: Is there a precipitation decline in the Mediterranean region? An assessment based on the scientific literature, Int. J. Climatol., 45, e8918, https://doi.org/10.1002/joc.8918, 2025.
Good, S. A., Martin, M. J., and Rayner, N. A.: EN4: quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates, J. Geophys. Res.-Oceans, 118, 6704–6716, https://doi.org/10.1002/2013JC009067, 2013.
Hagemann, S. and Dümenil Gates, L.: Validation of the hydrological cycle of ECMWF and NCEP reanalyses using the MPI hydrological discharge model, J. Geophys. Res.-Atmos., 106, 17901–17917, https://doi.org/10.1029/2000JD900568, 2001.
Hagemann, S. and Ho-Hagemann, H. T. M.: The Hydrological Discharge Model – a river runoff component for offline and coupled model applications (5.1.0), Zenodo [code], https://doi.org/10.5281/zenodo.5707587, 2021.
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D., and New, M.: A European daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006, J. Geophys. Res.-Atmos., 113, D20119, https://doi.org/10.1029/2008JD010201, 2008.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hertig, E. and Tramblay, Y.: Regional downscaling of Mediterranean droughts under past and future climatic conditions, Global Planet. Change, 151, 36–48, https://doi.org/10.1016/j.gloplacha.2016.10.015, 2017.
Hoerling, M., Eischeid, J., Perlwitz, J., Quan, X., Zhang, T., and Pegion, P.: On the increased frequency of Mediterranean drought, J. Climate, 25, 2146–2161, https://doi.org/10.1175/JCLI-D-11-00296.1, 2012.
Jousset, S., Mulet, S., Greiner, E., Wilkin, J., Vidar, L., Chafik, L., Raj, R., Bonaduce, A., Picot, N., and Dibarboure, G.: New global mean dynamic topography CNES-CLS-22 combining drifters, hydrography profiles and high frequency radar data, Earth Syst. Sci. Data, 18, 2285–2303, https://doi.org/10.5194/essd-18-2285-2026, 2026.
Juza, M., Fernández-Mora, À., and Tintoré, J.: Sub-regional marine heat waves in the Mediterranean Sea from observations: long-term surface changes, sub-surface and coastal responses, Front. Mar. Sci., 9, 785771, https://doi.org/10.3389/fmars.2022.785771, 2022.
Kourafalou, V. H. and Barbopoulos, K.: High resolution simulations on the North Aegean Sea seasonal circulation, Ann. Geophys., 21, 251–265, https://doi.org/10.5194/angeo-21-251-2003, 2003.
Laloyaux, P., de Boisseson, E., Balmaseda, M., Bidlot, J.-R., Broennimann, S., Buizza, R, Dalhgren, P., Dee, D., Haimberger, L., Hersbach, H., Kosaka, Y., Martin, M., Poli, P., Rayner, N., Rustemeier, E., and Schepers, D.: CERA-20C: A coupled reanalysis of the twentieth century, J. Adv. Model. Earth Syst., 10, 1172–1195, https://doi.org/10.1029/2018MS001273, 2018.
Lellouche, J.-M., Greiner, E., Bourdallé-Badie, R., Garric, G., Melet, A., Drévillon, M., Bricaud, C., Hamon, M., Le Galloudec, O., Regnier, C., Candela, T., Testut, C.-E., Gasparin, F., Ruggiero, G., Benkiran, M., Drillet, Y., and Le Traon, P.-Y.: The Copernicus global 1/12∘ oceanic and sea ice GLORYS12 reanalysis, Front. Earth Sci., 9, 698876, https://doi.org/10.3389/feart.2021.698876, 2021.
Lhotka, O., Bešťáková, Z., and Kyselý, J.: Prolongation of compound dry–hot seasons over Europe under climate change scenarios, Earth's Future, 11, e2023EF003557, https://doi.org/10.1029/2023EF003557, 2023.
Lionello, P. and Scarascia, L.: The relation between climate change in the Mediterranean region and global warming, Reg. Environ. Change, 18, 1481–1493, https://doi.org/10.1007/s10113-018-1290-1, 2018.
Liu, C., Liang, X., and Yu, L.: Salinity trends and mass balances in the Mediterranean Sea: revisit the role of air–sea freshwater fluxes and oceanic exchange, Ocean Sci., 21, 2069–2083, https://doi.org/10.5194/os-21-2069-2025, 2025.
Madec, G. and the NEMO System Team: NEMO Ocean Engine. In Notes du Pôle de modélisation de l'Institut Pierre-Simon Laplace (IPSL) (Version v3.6-patch, Issue 27), Zenodo, https://doi.org/10.5281/zenodo.3248739, 2017.
Marcos, M. and Tsimplis, M. N.: Coastal sea level trends in southern Europe, Geophys. J. Int., 175, 70–82, https://doi.org/10.1111/j.1365-246X.2008.03892.x, 2008.
Margirier, F., Testor, P., Heslop, E., Mallil, K., Bosse, A., Houpert, L., Mortier, L., Bouin, M. N., Coppola, L., D'Ortenzio, F., Durrieu de Madron, X., Mourre, B., Prieur, L., Raimbault, P., and Taillandier, V.: Abrupt warming and salinification of intermediate waters interplays with decline of deep convection in the Northwestern Mediterranean Sea, Sci. Rep., 10, 20923, https://doi.org/0.1038/s41598-020-77859-5, 2020.
Marti, O., Nguyen, S., Braconnot, P., Valcke, S., Lemarié, F., and Blayo, E.: A Schwarz iterative method to evaluate ocean–atmosphere coupling schemes: implementation and diagnostics in IPSL-CM6-SW-VLR, Geosci. Model Dev., 14, 2959–2975, https://doi.org/10.5194/gmd-14-2959-2021, 2021.
MedECC: Climate and Environmental Change in the Mediterranean Basin – Current Situation and Risks for the Future, First Mediterranean Assessment Report, Union for the Mediterranean, Plan Bleu, UNEP/MAP, Marseille, France, 632 pp., Zenodo [data set], https://doi.org/10.5281/zenodo.4768833, 2020.
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for geophysical fluid problems, Rev. Geophys., 20, 851–875, https://doi.org/10.1029/RG020i004p00851, 1982.
Morel, A. and Maritorena, S.: Bio-optical properties of oceanic waters: a reappraisal, J. Geophys. Res.-Oceans, 106, 7163–7180, https://doi.org/10.1029/2000JC000319, 2001.
Nakanishi, M. and Niino, H.: An improved Mellor–Yamada level-3 model: its numerical stability and application to a regional prediction of advection fog, Bound.-Lay. Meteorol., 119, 397–407, https://doi.org/10.1007/s10546-005-9030-8, 2006.
Pinardi, N. and Masetti, E.: Variability of the large scale general circulation of the Mediterranean Sea from observations and modelling: A review, Palaeogeogr. Palaeocl. Palaeoecol., 158, 153–173, https://doi.org/10.1016/S0031-0182(00)00048-1, 2000.
Pisano, A., Nardelli, B. B., Tronconi, C., and Santoleri, R.: The new Mediterranean optimally interpolated pathfinder AVHRR SST Dataset (1982–2012), Remote Sens. Environ., 176, 107–116, https://doi.org/10.1016/j.rse.2016.01.019, 2016.
Pisano, A., Marullo, S., Artale, V., Falcini, F., Yang, C., Leonelli, F. E., Santoleri, R., and Buongiorno Nardelli, B.: New evidence of mediterranean climate change and variability from sea surface temperature observations, Remote Sens., 12, 132, https://doi.org/10.3390/rs12010132, 2020.
Pujol, M.-I., Dupuy, S., Vergara, O., Sánchez Román, A., Faugère, Y., Prandi, P., Dabat, M.-L., Dagneaux, Q., Lievin, M., Cadier, E., Dibarboure, G., and Picot, N.: Refining the resolution of DUACS along-track Level-3 sea level altimetry products, Remote Sens., 15, 793, https://doi.org/10.3390/rs15030793, 2023.
Ridal, M., Bazile, E., Le Moigne, P., Randriamampianina, R., Schimanke, S., Andrae, U., Berggren, L., Brousseau, P., Dahlgren, P., Edvinsson, L., El-Said, A., Glinton, M., Hagelin, S., Hopsch, S., Isaksson, L., Medeiros, P., Olsson, E., Unden, P., and Wang, Z.: CERRA, the Copernicus European Regional Reanalysis system, Q. J. Roy. Meteorol. Soc., 150, 3385–3411, https://doi.org/10.1002/qj.4764, 2024.
Ruti, P. M., Somot, S., Giorgi, F., Dubois, C., Flaounas, E., Obermann, A., Dell'Aquila, A., Pisacane, G., Harzallah, A., Lombardi, E., Ahrens, B., Akhtar, N., Alias, A., Arsouze, T., Aznar, R., Bastin, S., Bartholy, J., Béranger, K., Beuvier, J., Bouffies-Cloché, S., Brauch, J., Cabos, W., Calmanti, S., Calvet, J.-C., Carillo, A., Conte, D., Coppola, E., Djurdjevic, V., Drobinski, P., Elizalde-Arellano, A., Gaertner, M., Galàn, P., Gallardo, C., Gualdi, S., Goncalves, M., Jorba, O., Jordà, G., L'Heveder, B., Lebeaupin-Brossier, C., Li, L., Liguori, G., Lionello, P., Maciàs, D., Nabat, P., Önol, B., Raikovic, B., Ramage, K., Sevault, F., Sannino, G., Struglia, M. V., Sanna, A., Torma, C., and Vervatis, V.: Med-CORDEX Initiative for Mediterranean climate studies, B. Am. Meteorol. Soc., 97, 1187–1208, https://doi.org/10.1175/BAMS-D-14-00176.1, 2016.
Sammartino, M., Aronica, S., Santoleri, R., and Buongiorno Nardelli, B.: Retrieving Mediterranean Sea Surface Salinity Distribution and Interannual Trends from Multi-Sensor Satellite and In Situ Data, Remote Sens., 14, 2502, https://doi.org/10.3390/rs14102502, 2022.
Schüller, V., Lemarié, F., Birken, P., and Blayo, E.: Quantifying coupling errors in atmosphere–ocean–sea-ice models: a study of iterative and non-iterative approaches in the EC-Earth AOSCM, Geosci. Model Dev., 18, 9167–9187, https://doi.org/10.5194/gmd-18-9167-2025, 2025.
Senatore, A., Davolio, S., Furnari, L., and Mendicino, G.: Reconstructing flood events in Mediterranean coastal areas using different reanalyses and high-resolution meteorological models, J. Hydrometeorol., 21, 1865–1887, https://doi.org/10.1175/JHM-D-19-0270.1, 2020.
Senatore, A., Furnari, L., Nikravesh, G., Castagna, J., and Mendicino, G.: Increasing daily precipitation extremes despite declining annual totals in southern Europe: a modeling study on the effects of Mediterranean Sea warming, Hydrol. Earth Syst. Sci., 30, 2913–2930, https://doi.org/10.5194/hess-30-2913-2026, 2026.
Skamarock, W. C., Klemp, J. B., Dudhia, M. G., Gill, D.O., Liu, Z., Berner, J., Wang, W., Powers, J. O., Duda, M., Barker, D., and Huang, X.-Y.: A description of the Advanced Research WRF model version 4.3.3, NCAR Tech. Note, NCAR, https://doi.org/10.5065/1dfh-6p97, 2021.
Skliris, N., Zika, J. D., Herold, L., Josey, S. A., and Marsh, R.: Mediterranean Sea water budget long-term trend inferred from salinity observations, Clim. Dynam., 51, 2857–2876, https://doi.org/10.1007/s00382-017-4053-7, 2018.
Soukissian, T. H., Karathanasi, F., and Axaopoulos, P.: Offshore renewable energy in the Mediterranean Sea: a review of the resource, existing projects and prospects, Renew. Energy, 179, 1225–1241, https://doi.org/10.1016/j.renene.2021.07.109, 2021.
Storto, A.: Variational quality control of hydrographic profile data with non-Gaussian errors for global ocean variational data assimilation systems, Ocean Model., 104, 226–241, https://doi.org/10.1016/j.ocemod.2016.06.011, 2016.
Storto, A. and Yang, C.: Acceleration of the ocean warming from 1961 to 2022 unveiled by large-ensemble reanalyses, Nat. Commun., 15, 545, https://doi.org/10.1038/s41467-024-44749-7, 2024.
Storto, A., Dobricic, S., Masina, S., and Di Pietro, P.: Assimilating along-track altimetric observations through local hydrostatic adjustment in a global ocean variational assimilation system, Mon. Weather Rev., 139, 738–754, https://doi.org/10.1175/2010MWR3350.1, 2011.
Storto, A., Oddo, P., Cipollone, A., Mirouze, I., and Lemieux-Dudon, B.: Extending an oceanographic variational scheme to allow for affordable hybrid and four-dimensional data assimilation, Ocean Model., 128, 67–86, https://doi.org/10.1016/j.ocemod.2018.06.005, 2018.
Storto, A., Alvera-Azcárate, A., Balmaseda, M. A., Barth, A., Chevallier, M., Counillon, F., Domingues, C. M., Drevillon, M., Drillet, Y., Forget, G., Garric, G., Haines, K., Hernandez, F., Iovino, D., Jackson, L. C., Lellouche, J.-M., Masina, S., Mayer, M., Oke, P. R., Penny, S. G., Peterson, K. A., Yang, C. and Zuo, H.: Ocean reanalyses: recent advances and unsolved challenges, Front. Mar. Sci., 6, 418, https://doi.org/10.3389/fmars.2019.00418, 2019a.
Storto, A., Masina, S., Simoncelli, S., Iovino, D., Cipollone, A., Drevillon, M., Drillet, Y., von Schuckman, K., Parent, L., Garric, G., Greiner, E., Desportes, C., Zuo, H., Balmaseda, M. A., and Peterson, K. A.: The added value of the multi-system spread information for ocean heat content and steric sea level investigations in the CMEMS GREP ensemble reanalysis product, Clim. Dynam., 53, 287–312, https://doi.org/10.1007/s00382-018-4585-5, 2019b.
Storto, A., Hesham Essa, Y., de Toma, V., Anav, A., Sannino, G., Santoleri, R., and Yang, C.: MESMAR v1: a new regional coupled climate model for downscaling, predictability, and data assimilation studies in the Mediterranean region, Geosci. Model Dev., 16, 4811–4833, https://doi.org/10.5194/gmd-16-4811-2023, 2023a.
Storto, A., Hesham Essa, Y., de Toma, V., Anav, A., Sannino, G., Santoleri, R., and Yang, C.: MESMAR v1: A new regional coupled climate model for downscaling, predictability, and data assimilation studies in the Mediterranean region, Coupled model code (1.0), Zenodo [code], https://doi.org/10.5281/zenodo.7898938, 2023b.
Storto, A., Chierici, G., Pfeffer, J., Barnoud, A., Bourdalle-Badie, R., Blazquez, A., Cavaliere, D., Lalau, N., Coupry, B., Drevillon, M., Fourest, S., Larnicol, G., and Yang, C.: Variability in manometric sea level from reanalyses and observation-based products over the Arctic and North Atlantic oceans and the Mediterranean Sea, in: 8th edition of the Copernicus Ocean State Report (OSR8), edited by: von Schuckmann, K., Moreira, L., Grégoire, M., Marcos, M., Staneva, J., Brasseur, P., Garric, G., Lionello, P., Karstensen, J., and Neukermans, G., Copernicus Publications, State Planet, 4-osr8, 12, https://doi.org/10.5194/sp-4-osr8-12-2024, 2024.
Storto, A., de Toma, V., and Yang, C.: MESMAR-R: A Coupled Regional Reanalysis for the Mediterranean Region Covering the period 1993–2024 (configuration files, monthly mean and daily ocean mean data) (Version 1.1) [Data set], Zenodo [data set], https://doi.org/10.5281/zenodo.22054519, 2026a.
Storto, A., de Toma, V., and Yang, C.: Dataset Open MESMAR-R: A Coupled Regional Reanalysis for the Mediterranean Region Covering the period 1993–2024 (daily min/mean/max for surface atmospheric variables) [Data set], Zenodo [data set], https://doi.org/10.5281/zenodo.22229855, 2026b.
Storto, A., de Toma, V., and Yang, C.: Dataset Open MESMAR-R: A Coupled Regional Reanalysis for the Mediterranean Region Covering the period 1993–2024 (daily mean air–sea fluxes and atmospheric diagnostics) [Data set], Zenodo [data set], https://doi.org/10.5281/zenodo.22232925, 2026c.
Tootoonchi, R., Bordoni, S., and D'Agostino, R.: Revisiting the moisture budget of the Mediterranean region in the ERA5 reanalysis, Weather Clim. Dynam., 6, 245–263, https://doi.org/10.5194/wcd-6-245-2025, 2025.
van der Meer, M., de Roda Husman, S., and Lhermitte, S.: Deep learning regional climate model emulators: a comparison of two downscaling training frameworks, J. Adv. Model. Earth Syst., 15, e2022MS003593, https://doi.org/10.1029/2022MS003593, 2023.
von Schuckmann, K., Palmer, M., Trenberth, K., Cazenave, A., Chambers, D., Champollion, N., Hansen, J., Josey, S. A., Loeb, N., Mathieu, P.-P., Meyssignac, B., and Wild, M.: An imperative to monitor Earth's energy imbalance, Nat. Clim. Change, 6, 138–144, https://doi.org/10.1038/nclimate2876, 2016.
von Schuckmann, K., Storto, A., Simoncelli, S., Raj, R. P., Samuelsen, A., de Pascual Collar, A., Garcia Sotillo, M., Szerkely, T., Mayer, M., Peterson, K. A., Zuo, H., Garric, G., and Monier, M.: Ocean heat content, in Copernicus Marine Service Ocean State Report, J. Operat. Oceanogr., 11, S1–S142, https://doi.org/10.1080/1755876X.2018.1489208, 2018.
WRF: wrf-model, GitHub [code], https://github.com/wrf-model/WRF (last access: 10 September 2026), 2023.
Yepes-Arbós, X., van den Oord, G., Acosta, M. C., and Carver, G. D.: Evaluation and optimisation of the I/O scalability for the next generation of Earth system models: IFS CY43R3 and XIOS 2.0 integration as a case study, Geosci. Model Dev., 15, 379–394, https://doi.org/10.5194/gmd-15-379-2022, 2022.
Zittis, G., Bruggeman, A., and Lelieveld, J.: Revisiting future extreme precipitation trends in the Mediterranean, Weather Clim. Ext., 34, 100380, https://doi.org/10.1016/j.wace.2021.100380, 2021.
Zuo, H., Balmaseda, M. A., Tietsche, S., Mogensen, K., and Mayer, M.: The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: a description of the system and assessment, Ocean Sci., 15, 779–808, https://doi.org/10.5194/os-15-779-2019, 2019.
Short summary
The Mediterranean region is one of the fastest-warming areas on Earth, and understanding its changes is thus crucial. We produced a new reconstruction of the Mediterranean climate for the 1993–2024 period, using a modelling system that combines weather, ocean, and hydrology information with observations. This new reanalysis offers a clearer picture of how the region has been warming, drying, and changing over the past 30 years, supporting better studies of extreme events and climate impacts.
The Mediterranean region is one of the fastest-warming areas on Earth, and understanding its...
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