Articles | Volume 16, issue 16
https://doi.org/10.5194/gmd-16-4811-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-4811-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
24 Aug 2023
Model description paper |
| 24 Aug 2023
| 24 Aug 2023
MESMAR v1: a new regional coupled climate model for downscaling, predictability, and data assimilation studies in the Mediterranean region
Institute of Marine Sciences (ISMAR), National Research Council
(CNR), Rome, Italy
National Research Center for High Performance Computing,
Big Data and Quantum Computing, ICSC, Italy
Yassmin Hesham Essa
Institute of Marine Sciences (ISMAR), National Research Council
(CNR), Rome, Italy
Central Laboratory for Agricultural Climate (CLAC), Agricultural
Research Center (ARC), Cairo, Egypt
Vincenzo de Toma
Institute of Marine Sciences (ISMAR), National Research Council
(CNR), Rome, Italy
Alessandro Anav
National Research Center for High Performance Computing,
Big Data and Quantum Computing, ICSC, Italy
Italian National Agency for New Technologies, Energy and
Sustainable Economic Development (ENEA), Rome, Italy
Gianmaria Sannino
National Research Center for High Performance Computing,
Big Data and Quantum Computing, ICSC, Italy
Italian National Agency for New Technologies, Energy and
Sustainable Economic Development (ENEA), Rome, Italy
Rosalia Santoleri
Institute of Marine Sciences (ISMAR), National Research Council
(CNR), Rome, Italy
Chunxue Yang
Institute of Marine Sciences (ISMAR), National Research Council
(CNR), Rome, Italy
National Research Center for High Performance Computing,
Big Data and Quantum Computing, ICSC, Italy
Related authors
Marie Bouih, Anne Barnoud, Chunxue Yang, Andrea Storto, Alejandro Blazquez, William Llovel, Robin Fraudeau, and Anny Cazenave
EGUsphere, https://doi.org/10.5194/egusphere-2024-3945, https://doi.org/10.5194/egusphere-2024-3945, 2025
This preprint is open for discussion and under review for Ocean Science (OS).
Short summary
Short summary
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 budget is not closed, this allows to detect errors in the observing systems. Our study based on this approach shows the the budget is not closed in the North Atlantic Ocean and identifies as main suspect, errors in Argo-based salinity data.
Andrea Storto, Sergey Frolov, Laura Slivinski, and Chunxue Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-185, https://doi.org/10.5194/gmd-2024-185, 2024
Preprint under review for GMD
Short summary
Short summary
Inaccuracies in air-sea heat fluxes severely downgrade the accuracy of ocean numerical simulations. Here, we use artificial neural networks to correct the 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.
Andrea Storto, Giulia Chierici, Julia Pfeffer, Anne Barnoud, Romain Bourdalle-Badie, Alejandro Blazquez, Davide Cavaliere, Noémie Lalau, Benjamin Coupry, Marie Drevillon, Sebastien Fourest, Gilles Larnicol, and Chunxue Yang
State Planet, 4-osr8, 12, https://doi.org/10.5194/sp-4-osr8-12-2024, https://doi.org/10.5194/sp-4-osr8-12-2024, 2024
Short summary
Short summary
The variability in the manometric sea level (i.e. the sea level mass component) in three ocean basins is investigated in this study using three different methods (reanalyses, gravimetry, and altimetry in combination with in situ observations). We identify the emerging long-term signals, the consistency of the datasets, and the influence of large-scale climate modes on the regional manometric sea level variations at both seasonal and interannual timescales.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
Short summary
Short summary
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.
Eric Jansen, Sam Pimentel, Wang-Hung Tse, Dimitra Denaxa, Gerasimos Korres, Isabelle Mirouze, and Andrea Storto
Ocean Sci., 15, 1023–1032, https://doi.org/10.5194/os-15-1023-2019, https://doi.org/10.5194/os-15-1023-2019, 2019
Short summary
Short summary
The assimilation of satellite SST data into ocean models is complex. The temperature of the thin uppermost layer that is measured by satellites may differ from the much thicker upper layer used in numerical models, leading to biased results. This paper shows how canonical correlation analysis can be used to generate observation operators from existing datasets of model states and corresponding observation values. This type of operator can correct for near-surface effects when assimilating SST.
Gerasimos Korres, Dimitra Denaxa, Eric Jansen, Isabelle Mirouze, Sam Pimentel, Wang-Hung Tse, and Andrea Storto
Ocean Sci. Discuss., https://doi.org/10.5194/os-2018-158, https://doi.org/10.5194/os-2018-158, 2019
Preprint withdrawn
Short summary
Short summary
A statistical-dynamical observation operator (SOSSTA) for satellite SST data assimilation able to account for SST diurnal variability, is formulated and implemented into the POSEIDON forecasting system (Aegean Sea). Model experiments where daytime SST retrievals from the SEVIRI infrared radiometer are introduced into the data assimilation procedure through the application of the observation operator, showed an improvement of the POSEIDON modelling system performance.
Marianne Pietschnig, Michael Mayer, Takamasa Tsubouchi, Andrea Storto, Sebastian Stichelberger, and Leopold Haimberger
Ocean Sci. Discuss., https://doi.org/10.5194/os-2017-98, https://doi.org/10.5194/os-2017-98, 2017
Revised manuscript not accepted
Short summary
Short summary
New estimates of volume and temperature transports into the Arctic Ocean through the four major gateways (Davis, Fram and Bering Strait and the Barents Sea Opening) have recently become available. These estimates are derived from moored observations. In this study, the same transports derived from a recent ocean reanalysis are compared to the observation-based estimates in the straits. In addition, cross-section plots of velocity, temperature and temperature flux density are investigated.
Zhaoyi Wang, Andrea Storto, Nadia Pinardi, Guimei Liu, and Hui Wang
Nat. Hazards Earth Syst. Sci., 17, 17–30, https://doi.org/10.5194/nhess-17-17-2017, https://doi.org/10.5194/nhess-17-17-2017, 2017
Andrea Storto and Simona Masina
Earth Syst. Sci. Data, 8, 679–696, https://doi.org/10.5194/essd-8-679-2016, https://doi.org/10.5194/essd-8-679-2016, 2016
Short summary
Short summary
A large number of applications related to the study of ocean climate require reliable datasets of the main physical variables of the ocean. Ocean reanalyses are a methodology based on the synthesis of information from ocean observations and models, and near-surface atmospheric observations into a dataset in a way as consistent in time as possible. In this paper, we describe and validate an upgraded version of the CMCC global ocean physical reanalysis (1980–present) at 1 / 4° resolution.
Paolo Oddo, Andrea Storto, Srdjan Dobricic, Aniello Russo, Craig Lewis, Reiner Onken, and Emanuel Coelho
Ocean Sci., 12, 1137–1153, https://doi.org/10.5194/os-12-1137-2016, https://doi.org/10.5194/os-12-1137-2016, 2016
Doroteaciro Iovino, Simona Masina, Andrea Storto, Andrea Cipollone, and Vladimir N. Stepanov
Geosci. Model Dev., 9, 2665–2684, https://doi.org/10.5194/gmd-9-2665-2016, https://doi.org/10.5194/gmd-9-2665-2016, 2016
Short summary
Short summary
An 11-year simulation of a global eddying ocean (1/16) configuration is presented. Model performance is evaluated against observations and a twin 1/4 configuration. The model realistically represents the variability at upper and intermediate depths, the position and strength of the surface circulation, and exchanges of mass through key passages. Sea ice properties are close to satellite observations. This simulation constitutes the groundwork for future applications to short range ocean forecasting.
L. Visinelli, S. Masina, M. Vichi, and A. Storto
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-5399-2014, https://doi.org/10.5194/bgd-11-5399-2014, 2014
Revised manuscript not accepted
Marie Bouih, Anne Barnoud, Chunxue Yang, Andrea Storto, Alejandro Blazquez, William Llovel, Robin Fraudeau, and Anny Cazenave
EGUsphere, https://doi.org/10.5194/egusphere-2024-3945, https://doi.org/10.5194/egusphere-2024-3945, 2025
This preprint is open for discussion and under review for Ocean Science (OS).
Short summary
Short summary
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 budget is not closed, this allows to detect errors in the observing systems. Our study based on this approach shows the the budget is not closed in the North Atlantic Ocean and identifies as main suspect, errors in Argo-based salinity data.
Andrea Storto, Sergey Frolov, Laura Slivinski, and Chunxue Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-185, https://doi.org/10.5194/gmd-2024-185, 2024
Preprint under review for GMD
Short summary
Short summary
Inaccuracies in air-sea heat fluxes severely downgrade the accuracy of ocean numerical simulations. Here, we use artificial neural networks to correct the 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.
Andrea Storto, Giulia Chierici, Julia Pfeffer, Anne Barnoud, Romain Bourdalle-Badie, Alejandro Blazquez, Davide Cavaliere, Noémie Lalau, Benjamin Coupry, Marie Drevillon, Sebastien Fourest, Gilles Larnicol, and Chunxue Yang
State Planet, 4-osr8, 12, https://doi.org/10.5194/sp-4-osr8-12-2024, https://doi.org/10.5194/sp-4-osr8-12-2024, 2024
Short summary
Short summary
The variability in the manometric sea level (i.e. the sea level mass component) in three ocean basins is investigated in this study using three different methods (reanalyses, gravimetry, and altimetry in combination with in situ observations). We identify the emerging long-term signals, the consistency of the datasets, and the influence of large-scale climate modes on the regional manometric sea level variations at both seasonal and interannual timescales.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Jonathan Baker, Clément Bricaud, Romain Bourdalle-Badie, Lluis Castrillo, Lijing Cheng, Frederic Chevallier, Daniele Ciani, Alvaro de Pascual-Collar, Vincenzo De Toma, Marie Drevillon, Claudia Fanelli, Gilles Garric, Marion Gehlen, Rianne Giesen, Kevin Hodges, Doroteaciro Iovino, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Thomas Lavergne, Simona Masina, Ronan McAdam, Audrey Minière, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Ad Stoffelen, Sulian Thual, Simon Van Gennip, Pierre Veillard, Chunxue Yang, and Hao Zuo
State Planet, 4-osr8, 1, https://doi.org/10.5194/sp-4-osr8-1-2024, https://doi.org/10.5194/sp-4-osr8-1-2024, 2024
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Ali Aydogdu, Lluis Castrillo, Daniele Ciani, Andrea Cipollone, Emanuela Clementi, Gianpiero Cossarini, Alvaro de Pascual-Collar, Vincenzo De Toma, Marion Gehlen, Rianne Giesen, Marie Drevillon, Claudia Fanelli, Kevin Hodges, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Priidik Lagemaa, Vidar Lien, Leonardo Lima, Vladyslav Lyubartsev, Ilja Maljutenko, Simona Masina, Ronan McAdam, Pietro Miraglio, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Urmas Raudsepp, Roshin Raj, Ad Stoffelen, Simon Van Gennip, Pierre Veillard, and Chunxue Yang
State Planet, 4-osr8, 2, https://doi.org/10.5194/sp-4-osr8-2-2024, https://doi.org/10.5194/sp-4-osr8-2-2024, 2024
Marco Chericoni, Giorgia Fosser, Emmanouil Flaounas, Gianmaria Sannino, and Alessandro Anav
EGUsphere, https://doi.org/10.5194/egusphere-2024-2829, https://doi.org/10.5194/egusphere-2024-2829, 2024
Short summary
Short summary
This study explores how sea surface energy influences both the atmosphere and ocean at various vertical levels during extreme Mediterranean cyclones. It focuses on cyclones' precipitation and wind speed response, as well as on ocean temperature variation. The analysis shows the effectiveness of the Regional Coupled Model in coherently representing the thermodynamic processes associated with extreme cyclones across both the atmosphere and the ocean.
Mohamed Hamitouche, Giorgia Fosser, Alessandro Anav, Cenlin He, and Tzu-Shun Lin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-264, https://doi.org/10.5194/hess-2024-264, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
This study evaluates how different methods of simulating runoff impact river flow predictions globally. By comparing seven approaches within the Noah-MP land surface model, we found significant differences in accuracy, with some methods underestimating or overestimating runoff. The results are crucial for improving water resource management and flood prediction. Our work highlights the need for precise modeling to better prepare for climate-related challenges.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
Short summary
Short summary
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.
Davide Zanchettin, Sara Bruni, Fabio Raicich, Piero Lionello, Fanny Adloff, Alexey Androsov, Fabrizio Antonioli, Vincenzo Artale, Eugenio Carminati, Christian Ferrarin, Vera Fofonova, Robert J. Nicholls, Sara Rubinetti, Angelo Rubino, Gianmaria Sannino, Giorgio Spada, Rémi Thiéblemont, Michael Tsimplis, Georg Umgiesser, Stefano Vignudelli, Guy Wöppelmann, and Susanna Zerbini
Nat. Hazards Earth Syst. Sci., 21, 2643–2678, https://doi.org/10.5194/nhess-21-2643-2021, https://doi.org/10.5194/nhess-21-2643-2021, 2021
Short summary
Short summary
Relative sea level in Venice rose by about 2.5 mm/year in the past 150 years due to the combined effect of subsidence and mean sea-level rise. We estimate the likely range of mean sea-level rise in Venice by 2100 due to climate changes to be between about 10 and 110 cm, with an improbable yet possible high-end scenario of about 170 cm. Projections of subsidence are not available, but historical evidence demonstrates that they can increase the hazard posed by climatically induced sea-level rise.
Alessandro Anav, Adriana Carillo, Massimiliano Palma, Maria Vittoria Struglia, Ufuk Utku Turuncoglu, and Gianmaria Sannino
Geosci. Model Dev., 14, 4159–4185, https://doi.org/10.5194/gmd-14-4159-2021, https://doi.org/10.5194/gmd-14-4159-2021, 2021
Short summary
Short summary
The Mediterranean Basin is a complex region, characterized by the presence of pronounced topography and a complex land–sea distribution including a considerable number of islands and straits; these features generate strong local atmosphere–sea interactions.
Regional Earth system models have been developed and used to study both present and future Mediterranean climate systems. The main aims of this paper are to present and evaluate the newly developed regional Earth system model ENEA-REG.
Jasdeep Singh Anand, Alessandro Anav, Marcello Vitale, Daniele Peano, Nadine Unger, Xu Yue, Robert J. Parker, and Hartmut Boesch
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-125, https://doi.org/10.5194/bg-2021-125, 2021
Publication in BG not foreseen
Short summary
Short summary
Ozone damages plants, which prevents them from absorbing CO2 from the atmosphere. This poses a potential threat to preventing dangerous climate change. In this work, satellite observations of forest cover, ozone, climate, and growing season are combined with an empirical model to estimate the carbon lost due to ozone exposure over Europe. The estimated carbon losses agree well with prior modelled estimates, showing for the first time that satellites can be used to better understand this effect.
Eric Jansen, Sam Pimentel, Wang-Hung Tse, Dimitra Denaxa, Gerasimos Korres, Isabelle Mirouze, and Andrea Storto
Ocean Sci., 15, 1023–1032, https://doi.org/10.5194/os-15-1023-2019, https://doi.org/10.5194/os-15-1023-2019, 2019
Short summary
Short summary
The assimilation of satellite SST data into ocean models is complex. The temperature of the thin uppermost layer that is measured by satellites may differ from the much thicker upper layer used in numerical models, leading to biased results. This paper shows how canonical correlation analysis can be used to generate observation operators from existing datasets of model states and corresponding observation values. This type of operator can correct for near-surface effects when assimilating SST.
Winfried Hoke, Tina Swierczynski, Peter Braesicke, Karin Lochte, Len Shaffrey, Martin Drews, Hilppa Gregow, Ralf Ludwig, Jan Even Øie Nilsen, Elisa Palazzi, Gianmaria Sannino, Lars Henrik Smedsrud, and ECRA network
Adv. Geosci., 46, 1–10, https://doi.org/10.5194/adgeo-46-1-2019, https://doi.org/10.5194/adgeo-46-1-2019, 2019
Short summary
Short summary
The European Climate Research Alliance is a bottom-up association of European research institutions helping to facilitate the development of climate change research, combining the capacities of national research institutions and inducing closer ties between existing national research initiatives, projects and infrastructures. This article briefly introduces the network's structure and organisation, as well as project management issues and prospects.
Gerasimos Korres, Dimitra Denaxa, Eric Jansen, Isabelle Mirouze, Sam Pimentel, Wang-Hung Tse, and Andrea Storto
Ocean Sci. Discuss., https://doi.org/10.5194/os-2018-158, https://doi.org/10.5194/os-2018-158, 2019
Preprint withdrawn
Short summary
Short summary
A statistical-dynamical observation operator (SOSSTA) for satellite SST data assimilation able to account for SST diurnal variability, is formulated and implemented into the POSEIDON forecasting system (Aegean Sea). Model experiments where daytime SST retrievals from the SEVIRI infrared radiometer are introduced into the data assimilation procedure through the application of the observation operator, showed an improvement of the POSEIDON modelling system performance.
Antonio Sanchez-Roman, Gabriel Jorda, Gianmaria Sannino, and Damia Gomis
Ocean Sci., 14, 1547–1566, https://doi.org/10.5194/os-14-1547-2018, https://doi.org/10.5194/os-14-1547-2018, 2018
Short summary
Short summary
We explore the vertical transfers of heat, salt and mass between the inflowing and outflowing layers at the Strait of Gibraltar by using a 3-D model with very high spatial resolution that allows for a realistic representation of the exchange. Results show a significant transformation of the water mass properties along their path through the strait, mainly induced by the recirculation of water between layers, while mixing seems to have little influence on the heat and salt exchanged.
Alessandro Anav, Chiara Proietti, Laurent Menut, Stefano Carnicelli, Alessandra De Marco, and Elena Paoletti
Atmos. Chem. Phys., 18, 5747–5763, https://doi.org/10.5194/acp-18-5747-2018, https://doi.org/10.5194/acp-18-5747-2018, 2018
Short summary
Short summary
Soil moisture and water stress play a pivotal role in regulating stomatal behaviour of plants; however, the role of water availability is often neglected in atmospheric chemistry modelling studies.
We show how dry deposition significantly declines when soil moisture is used to regulate the stomatal opening, mainly in semi-arid environments. Despite the fact that dry deposition occurs from the top of canopy to ground level, it affects the concentration of gases remaining in the lower atmosphere.
Marianne Pietschnig, Michael Mayer, Takamasa Tsubouchi, Andrea Storto, Sebastian Stichelberger, and Leopold Haimberger
Ocean Sci. Discuss., https://doi.org/10.5194/os-2017-98, https://doi.org/10.5194/os-2017-98, 2017
Revised manuscript not accepted
Short summary
Short summary
New estimates of volume and temperature transports into the Arctic Ocean through the four major gateways (Davis, Fram and Bering Strait and the Barents Sea Opening) have recently become available. These estimates are derived from moored observations. In this study, the same transports derived from a recent ocean reanalysis are compared to the observation-based estimates in the straits. In addition, cross-section plots of velocity, temperature and temperature flux density are investigated.
Pierre Sicard, Alessandro Anav, Alessandra De Marco, and Elena Paoletti
Atmos. Chem. Phys., 17, 12177–12196, https://doi.org/10.5194/acp-17-12177-2017, https://doi.org/10.5194/acp-17-12177-2017, 2017
Short summary
Short summary
A few issues about surface ozone, e.g. a better understanding of spatial changes and a better assessment of ozone impacts worldwide, are still challenging. To overcome these issues, this study assessed, for the first time, the spatial and temporal changes in the projected potential ozone impacts on carbon assimilation of vegetation at global scale, by comparing the ozone potential injury at present with that expected at the end of the 21st century from different global chemistry models.
Gianpiero Cossarini, Stefano Querin, Cosimo Solidoro, Gianmaria Sannino, Paolo Lazzari, Valeria Di Biagio, and Giorgio Bolzon
Geosci. Model Dev., 10, 1423–1445, https://doi.org/10.5194/gmd-10-1423-2017, https://doi.org/10.5194/gmd-10-1423-2017, 2017
Short summary
Short summary
The BFMCOUPLER (v1.0) is a coupling scheme that links the MITgcm and BFM models for ocean biogeochemistry simulations. The online coupling is based on an open-source code characterizd by a modular structure. Modularity preserves the potentials of the two models, allowing for a sustainable programming effort to handle future evolutions in the two codes. The BFMCOUPLER code is released along with an idealized problem (a cyclonic gyre in a mid-latitude closed basin).
Zhaoyi Wang, Andrea Storto, Nadia Pinardi, Guimei Liu, and Hui Wang
Nat. Hazards Earth Syst. Sci., 17, 17–30, https://doi.org/10.5194/nhess-17-17-2017, https://doi.org/10.5194/nhess-17-17-2017, 2017
Andrea Storto and Simona Masina
Earth Syst. Sci. Data, 8, 679–696, https://doi.org/10.5194/essd-8-679-2016, https://doi.org/10.5194/essd-8-679-2016, 2016
Short summary
Short summary
A large number of applications related to the study of ocean climate require reliable datasets of the main physical variables of the ocean. Ocean reanalyses are a methodology based on the synthesis of information from ocean observations and models, and near-surface atmospheric observations into a dataset in a way as consistent in time as possible. In this paper, we describe and validate an upgraded version of the CMCC global ocean physical reanalysis (1980–present) at 1 / 4° resolution.
Paolo Oddo, Andrea Storto, Srdjan Dobricic, Aniello Russo, Craig Lewis, Reiner Onken, and Emanuel Coelho
Ocean Sci., 12, 1137–1153, https://doi.org/10.5194/os-12-1137-2016, https://doi.org/10.5194/os-12-1137-2016, 2016
Doroteaciro Iovino, Simona Masina, Andrea Storto, Andrea Cipollone, and Vladimir N. Stepanov
Geosci. Model Dev., 9, 2665–2684, https://doi.org/10.5194/gmd-9-2665-2016, https://doi.org/10.5194/gmd-9-2665-2016, 2016
Short summary
Short summary
An 11-year simulation of a global eddying ocean (1/16) configuration is presented. Model performance is evaluated against observations and a twin 1/4 configuration. The model realistically represents the variability at upper and intermediate depths, the position and strength of the surface circulation, and exchanges of mass through key passages. Sea ice properties are close to satellite observations. This simulation constitutes the groundwork for future applications to short range ocean forecasting.
W. J. McKiver, G. Sannino, F. Braga, and D. Bellafiore
Ocean Sci., 12, 51–69, https://doi.org/10.5194/os-12-51-2016, https://doi.org/10.5194/os-12-51-2016, 2016
Short summary
Short summary
First modeling work comparing SHYFEM and MITgcm performance in the north Adriatic Sea; the treatment of heat/mass fluxes at the surface affects the models skill to reproduce coastal processes; high resolution is needed close to the coast, while lower resolution in the offshore is adequate to capture the dense water event; correct river discharges and temperature are vital for the reproduction of estuarine dynamics; non-hydrostatic processes do not influence the dense water formation.
L. Visinelli, S. Masina, M. Vichi, and A. Storto
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-5399-2014, https://doi.org/10.5194/bgd-11-5399-2014, 2014
Revised manuscript not accepted
Related subject area
Climate and Earth system modeling
Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
Subsurface hydrological controls on the short-term effects of hurricanes on nitrate–nitrogen runoff loading: a case study of Hurricane Ida using the Energy Exascale Earth System Model (E3SM) Land Model (v2.1)
CARIB12: a regional Community Earth System Model/Modular Ocean Model 6 configuration of the Caribbean Sea
Architectural insights into and training methodology optimization of Pangu-Weather
Evaluation of global fire simulations in CMIP6 Earth system models
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections
ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature
The need for carbon-emissions-driven climate projections in CMIP7
Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
Modeling Commercial-Scale CO2 Storage in the Gas Hydrate Stability Zone with PFLOTRAN v6.0
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0
Using feature importance as exploratory data analysis tool on earth system models
CropSuite – A comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – The ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2
Applying double cropping and interactive irrigation in the North China Plain using WRF4.5
The sea ice component of GC5: coupling SI3 to HadGEM3 using conductive fluxes
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
HyPhAICC v1.0: a hybrid physics–AI approach for probability fields advection shown through an application to cloud cover nowcasting
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
A non-intrusive, multi-scale, and flexible coupling interface in WRF
T&C-CROP: Representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5): Model formulation and validation
Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)
The Earth Science Box Modeling Toolkit (ESBMTK)
High Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
Baseline Climate Variables for Earth System Modelling
The DOE E3SM Version 2.1: Overview and Assessment of the Impacts of Parameterized Ocean Submesoscales
Evaluation of atmospheric rivers in reanalyses and climate models in a new metrics framework
Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic
HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0
Updating the radiation infrastructure in MESSy (based on MESSy version 2.55)
An urban module coupled with the Variable Infiltration Capacity model to improve hydrothermal simulations in urban systems
Bayesian hierarchical model for bias-correcting climate models
Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4
Reduced floating-point precision in regional climate simulations: an ensemble-based statistical verification
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
Short summary
Short summary
Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
Short summary
Short summary
Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
Short summary
Short summary
A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
Short summary
Short summary
Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
Short summary
Short summary
This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
Short summary
Short summary
We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
Short summary
Short summary
Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
Short summary
Short summary
Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
Short summary
Short summary
We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
Short summary
Short summary
We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
Short summary
Short summary
Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
Short summary
Short summary
We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
Short summary
Short summary
When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
Short summary
Short summary
We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
Short summary
Short summary
We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
Short summary
Short summary
The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
Short summary
Short summary
We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
Short summary
Short summary
In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
Short summary
Short summary
This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
Short summary
Short summary
We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
Short summary
Short summary
In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-162, https://doi.org/10.5194/gmd-2024-162, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most dangerous effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a sub-sea CO2 injection.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
Short summary
Short summary
This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
Short summary
Short summary
Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-133, https://doi.org/10.5194/gmd-2024-133, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
EGUsphere, https://doi.org/10.5194/egusphere-2024-2526, https://doi.org/10.5194/egusphere-2024-2526, 2024
Short summary
Short summary
CropSuite is a fuzzy-logic based high resolution open-source crop suitability model considering the impact of climate variability. We apply CropSuite for 48 important staple and cash crops at 1 km spatial resolution for Africa. We find that climate variability significantly impacts on suitable areas, but also affects optimal sowing dates, and multiple cropping potentials. The results provide information that can be used for climate impact assessments, adaptation and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-135, https://doi.org/10.5194/gmd-2024-135, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
The Icosahedral Nonhydrostatic (ICON) Model Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++ and Python) and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
Short summary
Short summary
In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
Short summary
Short summary
Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
Short summary
Short summary
This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
Short summary
Short summary
We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
Short summary
Short summary
This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
Short summary
Short summary
The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-140, https://doi.org/10.5194/gmd-2024-140, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This article details a new feature we implemented in the most popular regional atmospheric model (WRF). This feature allows data to be exchanged between WRF and any other model (e.g. an ocean model) using the coupling library Ocean-Atmosphere-Sea-Ice-Soil – Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
EGUsphere, https://doi.org/10.5194/egusphere-2024-2072, https://doi.org/10.5194/egusphere-2024-2072, 2024
Short summary
Short summary
We outline and validate developments to the pre-existing process-based model T&C to better represent cropland processes. Foreseen applications of T&C-CROP include hydrological and carbon storage implications of land-use transitions involving crop, forest, and pasture conversion, as well as studies on optimal irrigation and fertilization under a changing climate.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
Short summary
Short summary
A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Ulrich Georg Wortmann, Tina Tsan, Mahrukh Niazi, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
EGUsphere, https://doi.org/10.5194/egusphere-2024-1864, https://doi.org/10.5194/egusphere-2024-1864, 2024
Short summary
Short summary
The Earth Science Box Modeling Toolkit (ESBMTK) is a Python library designed to separate model description from numerical implementation. This approach results in well-documented, easily readable, and maintainable model code, allowing students and researchers to concentrate on conceptual challenges rather than mathematical intricacies.
Malcolm John Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
EGUsphere, https://doi.org/10.5194/egusphere-2024-2582, https://doi.org/10.5194/egusphere-2024-2582, 2024
Short summary
Short summary
HighResMIP2 is a model intercomparison project focussing on high resolution global climate models, that is those with grid spacings of 25 km or less in atmosphere and ocean, using simulations of decades to a century or so in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present day and future projections, and to build links with other communities to provide more robust climate information.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
Short summary
Short summary
We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Martin Juckes, Karl E. Taylor, Fabrizio Antonio, David Brayshaw, Carlo Buontempo, Jian Cao, Paul J. Durack, Michio Kawamiya, Hyungjun Kim, Tomas Lovato, Chloe Mackallah, Matthew Mizielinski, Alessandra Nuzzo, Martina Stockhause, Daniele Visioni, Jeremy Walton, Briony Turner, Eleanor O’Rourke, and Beth Dingley
EGUsphere, https://doi.org/10.5194/egusphere-2024-2363, https://doi.org/10.5194/egusphere-2024-2363, 2024
Short summary
Short summary
The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 132 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most heavily used variables from Earth System Models, based on an assessment of data publication and download records from the largest archive of global climate projects.
Katherine Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golez, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautum Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordonez
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-149, https://doi.org/10.5194/gmd-2024-149, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer biases reduction in temperature, salinity, and sea-ice extent in the North Atlantic, a small strengthening of the Atlantic Meridional Overturning Circulation, and improvements in many atmospheric climatological variables.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis O'Brien
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-142, https://doi.org/10.5194/gmd-2024-142, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
1. A metrics package designed for easy analysis of AR characteristics and statistics is presented. 2. The tool is efficient for diagnosing systematic AR bias in climate models, and useful for evaluating new AR characteristics in model simulations. 3. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the north and south Atlantic (south Pacific and Indian Ocean).
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
Short summary
Short summary
A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
Short summary
Short summary
Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
Short summary
Short summary
Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
Short summary
Short summary
We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
Short summary
Short summary
Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
Short summary
Short summary
Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
Short summary
Short summary
The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
Short summary
Short summary
We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
Cited articles
Akhtar, N., Brauch, J., Dobler, A., Béranger, K., and Ahrens, B.: Medicanes in an ocean–atmosphere coupled regional climate model, Nat. Hazards Earth Syst. Sci., 14, 2189–2201, https://doi.org/10.5194/nhess-14-2189-2014, 2014.
Akhtar, N., Brauch, J., and Ahrens, B.: Climate modeling over the Mediterranean Sea:
impact of resolution and ocean coupling, Clim. Dynam., 51, 933–948, 2018.
Anav, A., Carillo, A., Palma, M., Struglia, M. V., Turuncoglu, U. U., and Sannino, G.: The ENEA-REG system (v1.0), a multi-component regional Earth system model: sensitivity to different atmospheric components over the Med-CORDEX (Coordinated Regional Climate Downscaling Experiment) region, Geosci. Model Dev., 14, 4159–4185, https://doi.org/10.5194/gmd-14-4159-2021, 2021.
Artale, V., Calmanti, S., Carillo, A., Dell'Aquila, A., Herrmann, M., Pisacane, G., Ruti, P. M., Sannino, G., Struglia, M. V., Giorgi, F., Bi, X., Pal, J. S., Rauscher, S., and The PROTHEUS Group: An atmosphere–ocean regional
climate model for the Mediterranean area: assessment of a present climate
simulation, Clim. Dynam., 35, 721–740,
https://doi.org/10.1007/s00382-009-0691-8, 2010.
Astraldi, M., Balopoulos, S., Candela, J., Font, J., Gacic, M., Gasparini, G. P., Manca, B.,
Theocharis, A., and Tintore, J.: The role of straits and channels in understanding
the characteristics of Mediterranean circulation, Prog. Oceanogr.,
44, 65–108, 1999.
Bourdalle-Badie, R. and Treguier, A. M.: A climatology of run-off for the global
ocean-ice model ORCA025, report MOO-RP-425-365-MER, Mercator-Ocean:
Toulouse, France, 8 pp., https://www.drakkar-ocean.eu/publications/reports/runoff-mercator-06.pdf (last access: 14 August 2023), 2006.
Brewin, R. J. W., Sathyendranath, S., Müller, D., Brockmann, C.,
Deschamps, P.-Y., Devred, E., Doerffer, R., Fomferra, N., Franz, B., Grant, M.,
Groom, S., Horseman, A., Hu, C., Krasemann, H, Lee, Z. P., Maritorena, S.,
Mélin, F., Peters, M., Platt, T., Regner, P., Smyth, T., Steinmetz, F.,
Swinton, J., Werdell, J., and White, G. N.: The Ocean Colour Climate Change
Initiative: III. A round-robin comparison on in-water bio-optical
algorithms, Remote Sens. Environ., 162, 271–294,
https://doi.org/10.1016/j.rse.2013.09.016, 2015.
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.
Cassola, F., Ferrari, F., Mazzino, A., and Miglietta, M. M.: The role of the sea on the flash floods events over Liguria,
Geoph. Res. Lett., 43, 3534–3542, 2016.
Cavicchia, L. and von Storch, H.: The simulation of medicanes in a
high-resolution regional climate model, Clim. Dynam., 39, 2273–2290,
https://doi.org/10.1007/s00382-011-1220-0, 2012.
Cavicchia, L., von Storch, H., and Gualdi, S.: Mediterranean Tropical-Like
Cyclones in Present and Future Climate, J. Climate, 27, 7493–7501,
https://doi.org/10.1175/JCLI-D-14-00339.1, 2014.
Choi, S.-J. and Lee, D.-K.: Impact of spectral nudging on the downscaling
of tropical cyclones in regional climate simulations, Adv. Atmos. Sci., 33,
730–742, https://doi.org/10.1007/s00376-016-5061-y, 2016.
Cornes, R., van der Schrier, G., van den Besselaar, E. J. M., and Jones, P. D.: An
Ensemble Version of the E-OBS Temperature and Precipitation Datasets, J.
Geophys. Res.-Atmos., 123, 9391–9409, https://doi.org/10.1029/2017JD028200, 2018.
Cos, J., Doblas-Reyes, F., Jury, M., Marcos, R., Bretonnière, P.-A., and Samsó, M.: The Mediterranean climate change hotspot in the CMIP5 and CMIP6 projections, Earth Syst. Dynam., 13, 321–340, https://doi.org/10.5194/esd-13-321-2022, 2022.
Craig, A., 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.
Dai, A. and Trenberth, K. E.: Estimates of freshwater discharge from
continents: Latitudinal and seasonal variations, J. Hydrometeorol.,
3, 660–687, 2002.
Davies, H. C. and Turner, R. E.: Updating prediction models by dynamical
relaxation: An examination of the technique, Q. J. Roy. Meteor. Soc.,
103, 225–245, 1977.
Davin, E. L., Maisonnave, E., and Seneviratne, S. I.: Is land surface processes
representation a possible weak link in current Regional Climate Models?,
Environ. Res. Lett., 11, 1–8, https://doi.org/10.1088/1748-9326/11/7/074027,
2016.
Duffourg, F. and Ducrocq, V.: Origin of the moisture feeding the Heavy Precipitating Systems over Southeastern France, Nat. Hazards Earth Syst. Sci., 11, 1163–1178, https://doi.org/10.5194/nhess-11-1163-2011, 2011.
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.
Feser, F., Rockel, B., von Storch, H., Winterfeldt, J., and Zahn, M.: Regional
Climate Models Add Value to Global Model Data: A Review and Selected
Examples, B. Am. Meteorol. Soc., 92, 1181–1192,
https://doi.org/10.1175/2011BAMS3061.1, 2011.
Fita, L., Polcher, J., Giannaros, T. M., Lorenz, T., Milovac, J., Sofiadis, G., Katragkou, E., and Bastin, S.: CORDEX-WRF v1.3: development of a module for the Weather Research and Forecasting (WRF) model to support the CORDEX community, Geosci. Model Dev., 12, 1029–1066, https://doi.org/10.5194/gmd-12-1029-2019, 2019.
Flaounas, E., Davolio, S., Raveh-Rubin, S., Pantillon, F., Miglietta, M. M.,
Gaertner, M. A., Hatzaki, M., Homar, V., Khodayar, S., Korres, G., Kotroni,
V., Kushta, J., Reale, M., and Ricard, D.: Mediterranean cyclones: current
knowledge and open questions on dynamics, prediction, climatology and
impacts, Weather Clim. Dynam., 3, 173–208,
https://doi.org/10.5194/wcd-3-173-2022, 2022.
Flather, R. A.: A Storm Surge Prediction Model for the Northern Bay of
Bengal with Application to the Cyclone Disaster in April 1991, J. Phys.
Oceanogr., 24, 172–190, https://doi.org/10.1175/1520-0485(1994)024<0172:ASSPMF>2.0.CO;2, 1994.
Foley, A. M.: Uncertainty in regional climate modelling: A review, Prog.
Phys. Geogr.-Earth and Environment, 34, 647–670,
https://doi.org/10.1177/0309133310375654, 2010.
Giorgi, F.: Regional Dynamical Downscaling. Oxford Research Encyclopedia of
Climate Science,
https://oxfordre.com/climatescience/view/10.1093/acrefore/9780190228620.001.0001/acrefore-9780190228620-e-784 (last access: 22 June 2023),
2020.
Giorgi, F.: Thirty years of regional climate modeling: Where are we and
where are we going next?, J. Geophys. Res.-Atmos., 124,
5696–5723, https://doi.org/10.1029/2018JD030094, 2019.
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.
Grell, G. A. and Freitas, S. R.: A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling, Atmos. Chem. Phys., 14, 5233–5250, https://doi.org/10.5194/acp-14-5233-2014, 2014.
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.
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., 106, 1503–1510, 2001.
Hagemann, S., Stacke, T., and Ho-Hagemann, H.: High resolution discharge
simulations over Europe and the Baltic Sea catchment, Front. Earth Sci.,
8, 12, https://doi.org/10.3389/feart.2020.00012, 2020.
Harzallah, A., Jordà, G., Dubois, C., Sannino, G., Carillo, A., Li, L., Arsouze, T., Cavicchia, L., Beuvier, J., and Akhtar, N.: Long term evolution of heat
budget in the Mediterranean Sea from Med-CORDEX forced and coupled
simulations, Clim. Dynam., 51, 1145–1165,
https://doi.org/10.1007/s00382-016-3363-5, 2018.
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. R. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hirons, L. C., Klingaman, N. P., and Woolnough, S. J.: The impact of air
sea interactions on the representation of tropical precipitation extremes.
J. Adv. Model. Earth Sy., 10, 550559,
https://doi.org/10.1002/2017MS001252, 2018.
Ho-Hagemann, H. T. M., Hagemann, S., Grayek, S., Petrik, R., Rockel, B.,
Staneva, J., Feser, F., and Schrum, C.: Internal variability in the regional
coupled system model GCOAST-AHOI, Atmos., 11, 227,
https://doi.org/10.3390/atmos11030227, 2020.
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S.
A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases:
Calculations with the AER radiative transfer models, J. Geophys. Res., 113,
D13103, https://doi.org/10.1029/2008JD009944, 2008.
Iona, A., Theodorou, A., Sofianos, S., Watelet, S., Troupin, C., and Beckers, J.-M.: Mediterranean Sea climatic indices: monitoring long-term variability and climate changes, Earth Syst. Sci. Data, 10, 1829–1842, https://doi.org/10.5194/essd-10-1829-2018, 2018.
Janjić, Z. I.: The Step-Mountain Eta Coordinate Model: Further
Developments of the Convection, Viscous Sublayer, and Turbulence Closure
Schemes, Mon. Weather Rev., 122, 927–945, https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2, 1994.
Jordà, G., Von Schuckmann, K., Josey, S. A., Caniaux, G., García-Lafuente, J., Sammartino, S., Özsoy, E., Polcher, J., Notarstefano, G., Poulain, P.-M., Adloff, F., Salat, J., Naranjo, C., Schroeder, K., Chiggiato, J., Sannino, G., and Macías, D.: The Mediterranean Sea Heat
and Mass Budgets: Estimates, Uncertainties and Perspectives, Prog. Oceanogr.,
156, 174–208, https://doi.org/10.1016/j.pocean.2017.07.001, 2017.
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.
Lebeaupin Brossier, C. and Drobinski, P.: Numerical high-resolution air-sea
coupling over the Gulf of Lions during two Tramontane/Mistral events, J.
Geophys. Res., 114, D10110, https://doi.org/10.1029/2008JD011601, 2009.
Lebeaupin Brossier, C., Drobinski, P., Béranger, K., Bastin, S., and
Orain, F.: Ocean memory effect on the dynamics of coastal heavy
precipitation preceded by a mistral event in the northwestern Mediterranean,
Q. J. Roy. Meteor. Soc., 139, 1583–1597, https://doi.org/10.1002/qj.2049,
2013.
Lebeaupin Brossier, C., Bastin, S., Béranger, K., and Dobrinski, P.:
Regional mesoscale air sea coupling impacts and extreme meteorological
events role on the Mediterranean Sea water budget, Clim. Dynam., 44, 1029,
https://doi.org/10.1007/s00382-014-2252-z, 2015.
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.
Li, M., Zhang, S., Wu, L., Lin, X., Chang, P., Danabasoglu, G., Wei, Z., Yu,
X., Hu, H., Ma, X., Ma, W., Jia, D., Liu, X., Zhao, H., Mao, K., Ma, Y.,
Jiang, Y., Wang, X., Liu, G., and Chen, Y.: A high-resolution Asia-Pacific
regional coupled prediction system with dynamically downscaling coupled data
assimilation, Sci. Bull., 65, 1849–1858,
https://doi.org/10.1016/j.scib.2020.07.022, 2020.
Li, Y. and Toumi, R.: Improved tropical cyclone intensity forecasts by
assimilating coastal surface currents in an idealized study, Geophys.
Res. Lett., 45, 10019–10026, https://doi.org/10.1029/2018GL079677,
2018.
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.
Lionello, P., Martucci, G., and Zampieri, M.: Implementation of a Coupled
Atmosphere-Wave-Ocean Model in the Mediterranean Sea: Sensitivity of the
Short Time Scale Evolution to the Air-Sea Coupling Mechanisms, J.
Atmos. Ocean Sci., 9, 65–95,
https://doi.org/10.1080/1023673031000151421, 2003.
MacDonald, A. M., Candela, J., and Bryden, H. L.: An estimate of the net heat transport
through the Strait of Gibraltar, in: Seasonal and
interannual variability of the Western Mediterranean Sea, edited by: LaViolette, P. E., Coastal Estuarine
Stud. AGU, Washington DC, 13–32, https://doi.org/10.1029/CE046p0013, 1994.
Madec, G. and The NEMO System Team: NEMO Ocean Engine. Note Du Pole De
Modélisation. Paris, France: Institut Pierre-Simon Laplace, Zenodo,
https://doi.org/10.5281/zenodo.3248739, 2017.
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for
geophysical fluid problems, Rev. Geophys., 20, 851–875, 1982.
Mooney, P. A., Mulligan, F. J., and Fealy, R.: Evaluation of the Sensitivity
of the Weather Research and Forecasting Model to Parameterization Schemes
for Regional Climates of Europe over the Period 1990–95, J. Climate, 26,
1002–1017, https://doi.org/10.1175/JCLI-D-11-00676.1, 2013.
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.
Nabat, P., Somot, S., Cassou, C., Mallet, M., Michou, M., Bouniol, D., Decharme, B., Drugé, T., Roehrig, R., and Saint-Martin, D.: Modulation of radiative aerosols effects by atmospheric circulation over the Euro-Mediterranean region, Atmos. Chem. Phys., 20, 8315–8349, https://doi.org/10.5194/acp-20-8315-2020, 2020.
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.
NEMO: https://forge.ipsl.jussieu.fr/nemo/wiki, last access: 14 August 2023.
Niu, G.-Y., Yang, Z.-L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M., and Xia, Y.: The community Noah land surface model with
multiparameterization options (Noah-MP): 1. Model description and evaluation
with local-scale measurements, J. Geophys. Res., 116, D12109,
https://doi.org/10.1029/2010JD015139, 2011.
Omrani, H., Drobinski, P., and Dubos, T.: Using nudging to improve
global-regional dynamic consistency in limited-area climate modeling: What
should we nudge?, Clim. Dynam., 44, 1627–1644, 2015.
Penny, S. G., Akella, S., Balmaseda, M. A., Browne, P., Carton, J. A., Chevallier, M.,
Counillon, F., Domingues, C., Frolov, S., Heimbach, P., Hogan, P., Hoteit, I., Iovino, D.,
Laloyaux, P., Martin, M. J., Masina, S., Moore, A. M., de Rosnay, P., Schepers, D., Sloyan,
B. M., Storto, A., Subramanian, A., Nam, S., Vitart, F., Yang, C., Fujii, Y., Zuo, H., O'Kane,
T., Sandery, P., Moore, T., and Chapman, C. C.: Observational Needs for Improving
Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction, Front.
Mar. Sci., 6, 391, https://doi.org/10.3389/fmars.2019.00391, 2019.
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.
Reale, M., Giorgi, F., Solidoro, C., Di Biagio, V., Di Sante, F., Mariotti, L., Farneti, R., and Sannino, G.: The regional Earth system Model RegCM-ES: Evaluation
of the Mediterranean climate and marine biogeochemistry, J. Adv.
Model. Earth Sy., 12, e2019MS001812,
https://doi.org/10.1029/2019MS001812, 2020.
Reale, M., Cabos Narvaez, W. D., Cavicchia, L., Conte, D., Coppola, E., Flaounas, E., Giorgi, F., Gualdi, S., Hochman, A., Li, L., Lionello, P., Podrascanin, Z., Salon, S., Sanchez-Gomez, E., Scoccimarro, E., Sein, D. V., an Somot, S.: Future projections of
Mediterranean cyclone characteristics using the Med-CORDEX ensemble of
coupled regional climate system models, Clim. Dynam., 58, 2501–2524,
https://doi.org/10.1007/s00382-021-06018-x, 2022a.
Reale, M., Cossarini, G., Lazzari, P., Lovato, T., Bolzon, G., Masina, S., Solidoro, C., and Salon, S.: Acidification, deoxygenation, and nutrient and biomass declines in a warming Mediterranean Sea, Biogeosciences, 19, 4035–4065, https://doi.org/10.5194/bg-19-4035-2022, 2022b.
Ricchi, A., Miglietta, M. M., Barbariol, F., Benetazzo, A., Bergamasco, A.,
Bonaldo, D., Cassardo, C., Falcieri, F. M., Modugno, G., Russo, A., Sclavo,
M., and Carniel, S.: Sensitivity of a Mediterranean Tropical-Like Cyclone to
Different Model Configurations and Coupling Strategies, Atmosphere, 8, 92,
https://doi.org/10.3390/atmos8050092, 2017.
Rockel, B.: The Regional Downscaling Approach: a Brief History and Recent
Advances, Curr. Clim. Change Rep., 1, 22–29,
https://doi.org/10.1007/s40641-014-0001-3, 2015.
Rockel, B., Castro, C. L., Pielke Sr., R. A., von Storch, H., and Lencini, G.:
Dynamical downscaling: Assessment of model system dependent retained and
added variability for two different regional climate models, J. Geophys.
Res., 113, D21107, https://doi.org/10.1029/2007JD009461, 2008.
Rummukainen, M.: Added value in regional climate modeling, Wires Clim. Change,
7, 145–159, https://doi.org/10.1002/wcc.378, 2016.
Rummukainen, M., Rockel, B., Bärring, L., Christensen, J. H., and
Reckermann, M.: Twenty-First-Century Challenges in Regional Climate Modeling,
B. Am. Meteorol. Soc., 96, ES135–ES138,
https://doi.org/10.1175/BAMS-D-14-00214.1, 2015.
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.
Scoccimarro, E., Bellucci, A., Storto, A., Gualdi, S., Masina, S., and
Navarra, A.: Remote sub-surface ocean temperature as a predictor of Atlantic
hurricane activity, P. Natl. Acad. Sci. USA, 115, 11460–11464,
https://doi.org/10.1073/pnas.1810755115, 2018.
Skamarock, W. C., Klemp, J., Dudhia, J., Gill, D. O., Liu, Z., Berner, J., Wang, W., Powers, J. G., Duda, M., Barker, D., and Huang, X.-Y.: A Description of the Advanced Research WRF
Model Version 4.3 (No. NCAR/TN-556+STR),
https://doi.org/10.5065/1dfh-6p97, 2021.
Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling
system (ROMS): a splitexplicit, free-surface,
topography-following-coordinate oceanic model, Ocean Modell., 9,
347–404, 2005.
Soto-Navarro, J., Jordá, G., Amores, A., Cabos, W., Somot, S., Sevault, F., Macías, D., Djurdjevic, V., Sannino, G., Li, L., and Sein, D.: Evolution of Mediterranean Sea water properties under climate
change scenarios in the Med-CORDEX ensemble, Clim. Dynam., 54, 2135–2165,
https://doi.org/10.1007/s00382-019-05105-4, 2020.
Storkey, D., Blaker, A. T., Mathiot, P., Megann, A., Aksenov, Y., Blockley, E. W., Calvert, D., Graham, T., Hewitt, H. T., Hyder, P., Kuhlbrodt, T., Rae, J. G. L., and Sinha, B.: UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions, Geosci. Model Dev., 11, 3187–3213, https://doi.org/10.5194/gmd-11-3187-2018, 2018.
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.: MESMAR v1: A new regional coupled climate model for downscaling, predictability, and data assimilation studies in the Mediterranean region, Article data (1.0), Zenodo [data set], https://doi.org/10.5281/zenodo.7899115, 2023.
Storto, A. and Randriamampianina, R.: Ensemble variational assimilation for
the representation of background error covariances in a high-latitude
regional model, J. Geophys. Res., 115, D17204,
https://doi.org/10.1029/2009JD013111, 2010.
Storto, A., Masina, S., and Dobricic, S.: Estimation and Impact of
Nonuniform Horizontal Correlation Length Scales for Global Ocean Physical
Analyses, J. Atmos. Ocean. Tech., 31, 2330–2349,
https://doi.org/10.1175/JTECH-D-14-00042.1, 2014.
Storto, A., Masina, S., and Navarra, A.: Evaluation of the CMCC
eddy-permitting global ocean physical reanalysis system (C-GLORS,
1982–2012) and its assimilation components, Q. J. Roy. Meteor. Soc., 142,
738–758, https://doi.org/10.1002/qj.2673, 2016.
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, 2018a.
Storto, A., Martin, M. J., Deremble, B., and Masina, S.: Strongly Coupled Data
Assimilation Experiments with Linearized Ocean–Atmosphere Balance
Relationships, Mon. Weather Rev., 146, 1233–1257,
https://doi.org/10.1175/MWR-D-17-0222.1, 2018b.
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, 2019.
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, 2023.
Thompson, G., Field, P. R., Rasmussen, R. M., and Hall, W. D.: Explicit
Forecasts of Winter Precipitation Using an Improved Bulk Microphysics
Scheme. Part II: Implementation of a New Snow Parameterization, Mon.
Weather Rev., 136, 5095–5115, https://doi.org/10.1175/2008MWR2387.1,
2008.
Tsujino, H., Urakawa, S.,
Nakano, H., Small, R. J., Kim, W. M.,
Yeager, S. G., Danabasoglu, G.,
Suzuki, T., Bamber, J. L., Bentsen, M., Böning, C. W.,
Bozec, A., Chassignet, E. P., Curchitser, E., Boeira Dias, F., Durack, P. J.,
Griffies, S. M., Harada, Y., Ilicak, M.,
Josey, S. A., Kobayashi, C., Kobayashi, S., Komuro, Y.,
Large, W. G., Le Sommer, J., Marsland, S. J., Masina, S.,
Scheinert, M., Tomita, H., Valdivieso, M., and Yamazaki, D.: JRA-55 based surface dataset for driving ocean-sea-ice
models (JRA55-do)., Ocean Model., 130, 79–139,
https://doi.org/10.1016/j.ocemod.2018.07.002, 2018.
Umlauf, L. and Burchard, H.: A generic length-scale equation for geophysical
turbulence models, J. Mar. Res., 61, 235–265, 2003.
Vannucchi, V., Taddei, S., Capecchi, V., Bendoni, M., and Brandini, C.: Dynamical
Downscaling of ERA5 Data on the North-Western Mediterranean Sea: From
Atmosphere to High-Resolution Coastal Wave Climate, J. Mar.
Sci. Eng., 9, 208, https://doi.org/10.3390/jmse9020208,
2021.
Wang, M., Du, Y., Qiu, B., Xie, S., and Feng, M.: Dynamics on Seasonal
Variability of EKE Associated with TIWs in the Eastern Equatorial Pacific
Ocean, J. Phys. Oceanogr., 49, 1503–1519,
https://doi.org/10.1175/JPO-D-18-0163.1, 2019.
wrf-model: WRF, GitHub [code], https://github.com/wrf-model/WRF (last access: 14 August 2023.
Wunsch, C. and Stammer, D.: Atmospheric loading and the oceanic “inverted
barometer” effect, Rev. Geophys., 35, 79–107, https://doi.org/10.1029/96RG03037,
1997.
Zeng, X. and Beljaars, A.: A prognostic scheme of sea surface skin
temperature for modeling and data assimilation, Geophys. Res. Lett., 32,
L14605, https://doi.org/10.1029/2005gl023030, 2005.
Zhang, F. and Emanuel, K.: Promises in air-sea fully coupled data
assimilation for future hurricane prediction, Geophys. Res. Lett.,
45, 13173–13177, https://doi.org/10.1029/2018GL080970, 2018.
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
Regional climate models are a fundamental tool for a very large number of applications and are being increasingly used within climate services, together with other complementary approaches. Here, we introduce a new regional coupled model, intended to be later extended to a full Earth system model, for climate investigations within the Mediterranean region, coupled data assimilation experiments, and several downscaling exercises (reanalyses and long-range predictions).
Regional climate models are a fundamental tool for a very large number of applications and are...
