Articles | Volume 19, issue 3
https://doi.org/10.5194/os-19-559-2023
© 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/os-19-559-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 May 2023
Research article |
| 10 May 2023
| 10 May 2023
Modelling the barotropic sea level in the Mediterranean Sea using data assimilation
Institute of Marine Sciences, National Research Council,
Castello 2737/F, 30122 Venice, Italy
Christian Ferrarin
Institute of Marine Sciences, National Research Council,
Castello 2737/F, 30122 Venice, Italy
Georg Umgiesser
Institute of Marine Sciences, National Research Council,
Castello 2737/F, 30122 Venice, Italy
Klaipėda University, Coastal Research and Planning Institute,
H. Manto 84, 92294 Klaipėda, Lithuania
Andrea Bonometto
Italian Institute for Environmental Protection and Research,
S. Marco, 4665, 30122 Venice, Italy
Elisa Coraci
Italian Institute for Environmental Protection and Research,
S. Marco, 4665, 30122 Venice, Italy
Related authors
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
Short summary
Short summary
We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Christian Ferrarin, Florian Pantillon, Silvio Davolio, Marco Bajo, Mario Marcello Miglietta, Elenio Avolio, Diego S. Carrió, Ioannis Pytharoulis, Claudio Sanchez, Platon Patlakas, Juan Jesús González-Alemán, and Emmanouil Flaounas
Nat. Hazards Earth Syst. Sci., 23, 2273–2287, https://doi.org/10.5194/nhess-23-2273-2023, https://doi.org/10.5194/nhess-23-2273-2023, 2023
Short summary
Short summary
The combined use of meteorological and ocean models enabled the analysis of extreme sea conditions driven by Medicane Ianos, which hit the western coast of Greece on 18 September 2020, flooding and damaging the coast. The large spread associated with the ensemble highlighted the high model uncertainty in simulating such an extreme weather event. The different simulations have been used for outlining hazard scenarios that represent a fundamental component of the coastal risk assessment.
Georg Umgiesser, Marco Bajo, Christian Ferrarin, Andrea Cucco, Piero Lionello, Davide Zanchettin, Alvise Papa, Alessandro Tosoni, Maurizio Ferla, Elisa Coraci, Sara Morucci, Franco Crosato, Andrea Bonometto, Andrea Valentini, Mirko Orlić, Ivan D. Haigh, Jacob Woge Nielsen, Xavier Bertin, André Bustorff Fortunato, Begoña Pérez Gómez, Enrique Alvarez Fanjul, Denis Paradis, Didier Jourdan, Audrey Pasquet, Baptiste Mourre, Joaquín Tintoré, and Robert J. Nicholls
Nat. Hazards Earth Syst. Sci., 21, 2679–2704, https://doi.org/10.5194/nhess-21-2679-2021, https://doi.org/10.5194/nhess-21-2679-2021, 2021
Short summary
Short summary
The city of Venice relies crucially on a good storm surge forecast to protect its population and cultural heritage. In this paper, we provide a state-of-the-art review of storm surge forecasting, starting from examples in Europe and focusing on the Adriatic Sea and the Lagoon of Venice. We discuss the physics of storm surge, as well as the particular aspects of Venice and new techniques in storm surge modeling. We also give recommendations on what a future forecasting system should look like.
Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 14, 645–659, https://doi.org/10.5194/gmd-14-645-2021, https://doi.org/10.5194/gmd-14-645-2021, 2021
Short summary
Short summary
The problem of the optimization of ocean monitoring networks is tackled through the implementation of data assimilation techniques in a numerical model. The methodology has been applied to the tide gauge network in the Lagoon of Venice (Italy). The data assimilation methods allow identifying the minimum number of stations and their distribution that correctly represent the lagoon's dynamics. The methodology is easily exportable to other environments and can be extended to other variables.
Christian Ferrarin, Andrea Valentini, Martin Vodopivec, Dijana Klaric, Giovanni Massaro, Marco Bajo, Francesca De Pascalis, Amedeo Fadini, Michol Ghezzo, Stefano Menegon, Lidia Bressan, Silvia Unguendoli, Anja Fettich, Jure Jerman, Matjaz̆ Ličer, Lidija Fustar, Alvise Papa, and Enrico Carraro
Nat. Hazards Earth Syst. Sci., 20, 73–93, https://doi.org/10.5194/nhess-20-73-2020, https://doi.org/10.5194/nhess-20-73-2020, 2020
Short summary
Short summary
Here we present a shared and interoperable system to allow a better exchange of and elaboration on information related to sea storms among countries. The proposed integrated web system (IWS) is a combination of a common data system for sharing ocean observations and forecasts, a multi-model ensemble system, a geoportal, and interactive geo-visualization tools. This study describes the application of the developed system to the exceptional storm event of 29 October 2018.
Roderik S. W. van de Wal, Angélique Melet, Debora Bellafiore, Michalis Vousdoukas, Paula Camus, Christian Ferrarin, Gualbert Oude Essink, Ivan D. Haigh, Piero Lionello, Arjen Luijendijk, Alexandra Toimil, and Joanna Staneva
State Planet Discuss., https://doi.org/10.5194/sp-2023-38, https://doi.org/10.5194/sp-2023-38, 2023
Revised manuscript under review for SP
Short summary
Short summary
Sea level rise has major impacts in Europe which vary from place to place and in time depending on the source of the impacts. Flooding, erosion and saltwater intrusion lead via different pathways to various consequences in coastal regions across Europe. It causes damage to assets, environment and people for all three categories of impacts discussed in this paper. The paper provides an overview of the various impacts in Europe.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
Short summary
Short summary
We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Christian Ferrarin, Florian Pantillon, Silvio Davolio, Marco Bajo, Mario Marcello Miglietta, Elenio Avolio, Diego S. Carrió, Ioannis Pytharoulis, Claudio Sanchez, Platon Patlakas, Juan Jesús González-Alemán, and Emmanouil Flaounas
Nat. Hazards Earth Syst. Sci., 23, 2273–2287, https://doi.org/10.5194/nhess-23-2273-2023, https://doi.org/10.5194/nhess-23-2273-2023, 2023
Short summary
Short summary
The combined use of meteorological and ocean models enabled the analysis of extreme sea conditions driven by Medicane Ianos, which hit the western coast of Greece on 18 September 2020, flooding and damaging the coast. The large spread associated with the ensemble highlighted the high model uncertainty in simulating such an extreme weather event. The different simulations have been used for outlining hazard scenarios that represent a fundamental component of the coastal risk assessment.
Manuel Aghito, Loris Calgaro, Knut-Frode Dagestad, Christian Ferrarin, Antonio Marcomini, Øyvind Breivik, and Lars Robert Hole
Geosci. Model Dev., 16, 2477–2494, https://doi.org/10.5194/gmd-16-2477-2023, https://doi.org/10.5194/gmd-16-2477-2023, 2023
Short summary
Short summary
The newly developed ChemicalDrift model can simulate the transport and fate of chemicals in the ocean and in coastal regions. The model combines ocean physics, including transport due to currents, turbulence due to surface winds and the sinking of particles to the sea floor, with ocean chemistry, such as the partitioning, the degradation and the evaporation of chemicals. The model will be utilized for risk assessment of ocean and sea-floor contamination from pollutants emitted from shipping.
Damiano Baldan, Elisa Coraci, Franco Crosato, Maurizio Ferla, Andrea Bonometto, and Sara Morucci
Nat. Hazards Earth Syst. Sci., 22, 3663–3677, https://doi.org/10.5194/nhess-22-3663-2022, https://doi.org/10.5194/nhess-22-3663-2022, 2022
Short summary
Short summary
Extreme-event analysis is widely used to provide information for the design of coastal protection structures. Non-stationarity due to sea level rise can affect such estimates. Using different methods on a long time series of sea level data, we show that estimates of the magnitude of extreme events in the future can be inexact due to relative sea level rise. Thus, considering non-stationarity is important when analyzing extreme-sea-level events.
Julius Schlumberger, Christian Ferrarin, Sebastiaan N. Jonkman, Manuel Andres Diaz Loaiza, Alessandro Antonini, and Sandra Fatorić
Nat. Hazards Earth Syst. Sci., 22, 2381–2400, https://doi.org/10.5194/nhess-22-2381-2022, https://doi.org/10.5194/nhess-22-2381-2022, 2022
Short summary
Short summary
Flooding has serious impacts on the old town of Venice. This paper presents a framework combining a flood model with a flood-impact model to support improving protection against future floods in Venice despite the recently built MOSE barrier. Applying the framework to seven plausible flood scenarios, it was found that individual protection has a significant damage-mediating effect if the MOSE barrier does not operate as anticipated. Contingency planning thus remains important in Venice.
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.
Piero Lionello, David Barriopedro, Christian Ferrarin, Robert J. Nicholls, Mirko Orlić, Fabio Raicich, Marco Reale, Georg Umgiesser, Michalis Vousdoukas, and Davide Zanchettin
Nat. Hazards Earth Syst. Sci., 21, 2705–2731, https://doi.org/10.5194/nhess-21-2705-2021, https://doi.org/10.5194/nhess-21-2705-2021, 2021
Short summary
Short summary
In this review we describe the factors leading to the extreme water heights producing the floods of Venice. We discuss the different contributions, their relative importance, and the resulting compound events. We highlight the role of relative sea level rise and the observed past and very likely future increase in extreme water heights, showing that they might be up to 160 % higher at the end of the 21st century than presently.
Georg Umgiesser, Marco Bajo, Christian Ferrarin, Andrea Cucco, Piero Lionello, Davide Zanchettin, Alvise Papa, Alessandro Tosoni, Maurizio Ferla, Elisa Coraci, Sara Morucci, Franco Crosato, Andrea Bonometto, Andrea Valentini, Mirko Orlić, Ivan D. Haigh, Jacob Woge Nielsen, Xavier Bertin, André Bustorff Fortunato, Begoña Pérez Gómez, Enrique Alvarez Fanjul, Denis Paradis, Didier Jourdan, Audrey Pasquet, Baptiste Mourre, Joaquín Tintoré, and Robert J. Nicholls
Nat. Hazards Earth Syst. Sci., 21, 2679–2704, https://doi.org/10.5194/nhess-21-2679-2021, https://doi.org/10.5194/nhess-21-2679-2021, 2021
Short summary
Short summary
The city of Venice relies crucially on a good storm surge forecast to protect its population and cultural heritage. In this paper, we provide a state-of-the-art review of storm surge forecasting, starting from examples in Europe and focusing on the Adriatic Sea and the Lagoon of Venice. We discuss the physics of storm surge, as well as the particular aspects of Venice and new techniques in storm surge modeling. We also give recommendations on what a future forecasting system should look like.
Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 14, 645–659, https://doi.org/10.5194/gmd-14-645-2021, https://doi.org/10.5194/gmd-14-645-2021, 2021
Short summary
Short summary
The problem of the optimization of ocean monitoring networks is tackled through the implementation of data assimilation techniques in a numerical model. The methodology has been applied to the tide gauge network in the Lagoon of Venice (Italy). The data assimilation methods allow identifying the minimum number of stations and their distribution that correctly represent the lagoon's dynamics. The methodology is easily exportable to other environments and can be extended to other variables.
Christian Ferrarin, Andrea Valentini, Martin Vodopivec, Dijana Klaric, Giovanni Massaro, Marco Bajo, Francesca De Pascalis, Amedeo Fadini, Michol Ghezzo, Stefano Menegon, Lidia Bressan, Silvia Unguendoli, Anja Fettich, Jure Jerman, Matjaz̆ Ličer, Lidija Fustar, Alvise Papa, and Enrico Carraro
Nat. Hazards Earth Syst. Sci., 20, 73–93, https://doi.org/10.5194/nhess-20-73-2020, https://doi.org/10.5194/nhess-20-73-2020, 2020
Short summary
Short summary
Here we present a shared and interoperable system to allow a better exchange of and elaboration on information related to sea storms among countries. The proposed integrated web system (IWS) is a combination of a common data system for sharing ocean observations and forecasts, a multi-model ensemble system, a geoportal, and interactive geo-visualization tools. This study describes the application of the developed system to the exceptional storm event of 29 October 2018.
Georg Umgiesser, Petras Zemlys, Ali Erturk, Arturas Razinkova-Baziukas, Jovita Mėžinė, and Christian Ferrarin
Ocean Sci., 12, 391–402, https://doi.org/10.5194/os-12-391-2016, https://doi.org/10.5194/os-12-391-2016, 2016
Short summary
Short summary
The paper explores the importance of physical forcing on the exchange mechanisms and the renewal time in the Curonian Lagoon over 10 years. The influence of ice cover on the exchange rates has been explored. Finally, the influence of water level fluctuations and river discharge has been studied. It has been found that ice cover is surprisingly not very important for changes in renewal time. The single most important factor is river discharge.
S. Mariani, M. Casaioli, E. Coraci, and P. Malguzzi
Nat. Hazards Earth Syst. Sci., 15, 1–24, https://doi.org/10.5194/nhess-15-1-2015, https://doi.org/10.5194/nhess-15-1-2015, 2015
Short summary
Short summary
In the HyMeX framework, an intercomparison study of two different configurations of the ISPRA hydro-meteo-marine forecasting system (SIMM) has been performed to assess the forecast skill in predicting high precipitations and very intense storm surges over the northern Adriatic Sea (acqua alta). The results show an objective added value of the use of high-resolution meteorological models, and they suggest the opportunity to develop a time-lagged multi-model ensemble for the acqua alta prediction.
P. Zemlys, C. Ferrarin, G. Umgiesser, S. Gulbinskas, and D. Bellafiore
Ocean Sci., 9, 573–584, https://doi.org/10.5194/os-9-573-2013, https://doi.org/10.5194/os-9-573-2013, 2013
C. Ferrarin, M. Ghezzo, G. Umgiesser, D. Tagliapietra, E. Camatti, L. Zaggia, and A. Sarretta
Hydrol. Earth Syst. Sci., 17, 1733–1748, https://doi.org/10.5194/hess-17-1733-2013, https://doi.org/10.5194/hess-17-1733-2013, 2013
Cited articles
Bajo, M.: Improving storm surge forecast in Venice with a unidimensional
Kalman filter, Estuar. Coast. Shelf Sci., 239, 106773,
https://doi.org/10.1016/j.ecss.2020.106773, 2020. a
Bajo, M.: SHYFEM model with EnKF, Zenodo [code], https://doi.org/10.5281/zenodo.7886239, 2023. a
Bajo, M. and Umgiesser, G.: Storm surge forecast through a combination of
dynamic and neural network models, Ocean Model., 33, 1–9,
https://doi.org/10.1016/j.ocemod.2009.12.007, 2010. a
Bajo, M., Zampato, L., Umgiesser, G., Cucco, A., and Canestrelli, P.: A finite
element operational model for storm surge prediction in Venice, Estuar.
Coast. Shelf Sci., 75, 236–249,
https://doi.org/10.1016/j.ecss.2007.02.025, 2007. a
Bajo, M., Biasio, F. D., Umgiesser, G., Vignudelli, S., and Zecchetto, S.:
Impact of using scatterometer and altimeter data on storm surge forecasting,
Ocean Model., 113, 85–94, https://doi.org/10.1016/j.ocemod.2017.03.014, 2017. a, b, c
Bajo, M., Međugorac, I., Umgiesser, G., and Orlić, M.: Storm surge and
seiche modelling in the Adriatic Sea and the impact of data assimilation,
Q. J. Roy. Meteor. Soc., 145, 2070–2084,
https://doi.org/10.1002/qj.3544, 2019. a, b, c
Barbariol, F., Pezzutto, P., Davison, S., Bertotti, L., Cavaleri, L., Papa, A.,
Favaro, M., Sambo, E., and Benetazzo, A.: Wind-wave forecasting in enclosed
basins using statistically downscaled global wind forcing, Front.
Mar. Sci., 9, 1002786, https://doi.org/10.3389/fmars.2022.1002786, 2022. a
Bertin, X., Li, K., Roland, A., Zhang, Y. J., Breilh, J. F., and Chaumillon,
E.: A modeling-based analysis of the flooding associated with Xynthia,
central Bay of Biscay, Coast. Engin., 94, 80–89,
https://doi.org/10.1016/j.coastaleng.2014.08.013, 2014. a
Birol, F., Fuller, N., Lyard, F., Cancet, M., Niño, F., Delebecque, C.,
Fleury, S., Toublanc, F., Melet, A., Saraceno, M., and Léger, F.: Coastal
applications from nadir altimetry: Example of the X-TRACK regional products,
Adv. Space Res., 59, 936–953,
https://doi.org/10.1016/j.asr.2016.11.005, 2017. a, b
Byrne, D., Horsburgh, K., and Williams, J.: Variational data assimilation of
sea surface height into a regional storm surge model: Benefits and
limitations, J. Oper. Oceanogr., 16, 1–14,
https://doi.org/10.1080/1755876X.2021.1884405, 2021. a, b
Carrassi, A., Bocquet, M., Bertino, L., and Evensen, G.: Data assimilation in
the geosciences: An overview of methods, issues, and perspectives, Wiley
Interdisciplinary Reviews, Climate Change, 9, e535, https://doi.org/10.1002/wcc.535,
2018. a, b
Carrère, L. and Lyard, F.: Modeling the barotropic response of the global
ocean to atmospheric wind and pressure forcing – comparisons with
observations, Geophys. Res. Lett., 30, 1275,
https://doi.org/10.1029/2002GL016473, 2003. a
Cavaleri, L., Bajo, M., Barbariol, F., Bastianini, M., Benetazzo, A., Bertotti,
L., Chiggiato, J., Davolio, S., Ferrarin, C., Magnusson, L., Papa, A.,
Pezzutto, P., Pomaro, A., and Umgiesser, G.: The October 29, 2018 storm in
Northern Italy – An exceptional event and its modeling, Prog.
Oceanogr., 178, 102178,
https://doi.org/10.1016/j.pocean.2019.102178, 2019. a, b
Cerovecki, I., Orlić, M., and Hendershott, M. C.: Adriatic seiche decay and
energy loss to the Mediterranean, Deep-Sea Res. Pt. I, 44, 2007–2029, https://doi.org/10.1016/S0967-0637(97)00056-3, 1997. a
Clementi, E., Aydogdu, A., Goglio, A., Pistoia, J., Escudier, R., Drudi, M.,
Grandi, A., Mariani, A., Lyubartsev, V., Lecci, R., Cretí, S., Coppini, G.,
Masina, S., and Pinardi, N.: Mediterranean Sea Physical Analysis and
Forecast (CMEMS MED-Currents, EAS6 system) (Version 1),
https://doi.org/10.25423/CMCC/, 2021. a
Evensen, G.: Sequential data assimilation with a nonlinear quasi-geostrophic
model using Monte Carlo methods to forecast error statistics, J.
Geogr. Res., 99, 10143–10162, 1994. a
Evensen, G.: The Ensemble Kalman Filter: theoretical formulation and
practical implementation, Ocean Dynam., 53, 343–367,
https://doi.org/10.1007/s10236-003-0036-9, 2003. a, b
Evensen, G.: Sampling strategies and square root analysis schemes for the
EnKF, Ocean Dynam., 54, 539–560, https://doi.org/10.1007/s10236-004-0099-2, 2004. a, b
Evensen, G.: Spurious correlations, localization, and inflation,
Springer Berlin Heidelberg, Berlin, Heidelberg, 237–253,
https://doi.org/10.1007/978-3-642-03711-5_15, 2009a. a, b
Evensen, G.: The ensemble Kalman filter for combined state and parameter
estimation, IEEE Control Syst. Mag., 29, 83–104,
https://doi.org/10.1109/MCS.2009.932223, 2009b. a
Fernández-Montblanc, T., Vousdoukas, M., Ciavola, P., Voukouvalas, E.,
Mentaschi, L., Breyiannis, G., Feyen, L., and Salamon, P.: Towards robust
pan-European storm surge forecasting, Ocean Model., 133, 129–144,
https://doi.org/10.1016/j.ocemod.2018.12.001, 2019. a
Ferrarin, C., Roland, A., Bajo, M., Umgiesser, G., Cucco, A., Davolio, S.,
Buzzi, A., Malguzzi, P., and Drofa, O.: Tide-surge-wave modelling and
forecasting in the Mediterranean Sea with focus on the Italian coast, Ocean
Model., 61, 38–48, https://doi.org/10.1016/j.ocemod.2012.10.003,
2013. a
Ferrarin, C., Bellafiore, D., Sannino, G., Bajo, M., and Umgiesser, G.: Tidal
dynamics in the inter-connected Mediterranean, Marmara, Black and Azov seas,
Prog. Oceanogr., 161, 102–115,
https://doi.org/10.1016/j.pocean.2018.02.006, 2018. a, b
Ferrarin, C., Bajo, M., Benetazzo, A., Cavaleri, L., Chiggiato, J., Davison,
S., Davolio, S., Lionello, P., Orlić, M., and Umgiesser, G.: Local and
large-scale controls of the exceptional Venice floods of November 2019,
Prog. Oceanogr., 197, 102628,
https://doi.org/10.1016/j.pocean.2021.102628, 2021. a, b, c, d, e
Flowerdew, J., Horsburgh, K., Wilson, C., and Mylne, K.: Development and
evaluation of an ensemble forecasting system for coastal storm surges,
Q. J. Roy. Meteor. Soc., 136, 1444–1456,
https://doi.org/10.1002/qj.648, 2010. a
Gaspari, G. and Cohn, S. E.: Construction of correlation functions in two and
three dimensions, Q. J. Roy. Meteor. Soc.,
125, 723–757, https://doi.org/10.1002/qj.49712555417, 1999. a
Hersbach, H.: Sea Surface Roughness and Drag Coefficient as Functions of
Neutral Wind Speed, J. Phys. Oceanogr., 41, 247–251,
https://doi.org/10.1175/2010JPO4567.1, 2011. a
Horsburgh, K., Haigh, I., Williams, J., De Dominicis, M., Wolf, J.,
Inayatillah, A., and Byrne, D.: “Grey swan” storm surges pose a greater
coastal flood hazard than climate change, Ocean Dynam., 71, 715–730,
https://doi.org/10.1007/s10236-021-01453-0, 2021. a
Järvinen, H. and Undén, P.: Observation screening and background
quality control in the ECMWF 3D-Var data assimilation system, ECMWF Technical Memoranda, 236, 33 pp.,
https://doi.org/10.21957/lyd3q81, 1997. a
Kalnay, E.: Atmospheric Modeling, Data Assimilation and Predictability,
Cambridge University Press, https://doi.org/10.1017/CBO9780511802270, 2002. a
Kepert, J. D.: On ensemble representation of the observation-error covariance
in the Ensemble Kalman Filter, Ocean Dynam., 54, 561–569,
https://doi.org/10.1007/s10236-004-0104-9, 2004. a
Lyard, F. H., Allain, D. J., Cancet, M., Carrère, L., and Picot, N.: FES2014 global ocean tide atlas: design and performance, Ocean Sci., 17, 615–649, https://doi.org/10.5194/os-17-615-2021, 2021. a
Mariani, S., Casaioli, M., Coraci, E., and Malguzzi, P.: A new high-resolution BOLAM-MOLOCH suite for the SIMM forecasting system: assessment over two HyMeX intense observation periods, Nat. Hazards Earth Syst. Sci., 15, 1–24, https://doi.org/10.5194/nhess-15-1-2015, 2015. a
Međugorac, I., Pasarić, M., Pasarić, Z., and Orlić, M.: Two recent
storm-surge episodes in the Adriatic, Int. J. Safet.
Secur. Eng., 6, 589 – 596, https://doi.org/10.2495/SAFE-V6-N3-589-596, 2016. a
Pérez, B., Fanjul, E. A., Pérez, S., De Alfonso, M., and Vela, J.: Use
of tide gauge data in operational oceanography and sea level hazard warning
systems, J. Operat. Oceanogr., 6, 1–18,
https://doi.org/10.1080/1755876X.2013.11020147, 2013. a
Proudman, J.: The Effects on the Sea of Changes in Atmospheric Pressure,
Geophys. J. Int., 2, 197–209,
https://doi.org/10.1111/j.1365-246X.1929.tb05408.x, 1929. a
Pugh, D. T.: Tides, surges and mean sea-level (reprinted with corrections),
Chichester, UK. John Wiley & Sons, Ltd., 486 pp., ISBN: 047191505X, 1996. a
Roland, A., Cucco, A., Ferrarin, C., Hsu, T.-W., Liau, J.-M., Ou, S.-H.,
Umgiesser, G., and Zanke, U.: On the development and verification of a 2-D
coupled wave-current model on unstructured meshes, J. Mar.
Syst., 78, S244–S254, https://doi.org/10.1016/j.jmarsys.2009.01.026, 2009. a
Sakov, P., Counillon, F., Bertino, L., Lisæter, K. A., Oke, P. R., and Korablev, A.: TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic, Ocean Sci., 8, 633–656, https://doi.org/10.5194/os-8-633-2012, 2012. a
Scicchitano, G., Scardino, G., Monaco, C., Piscitelli, A., Milella, M., De
Giosa, F., and Mastronuzzi, G.: Comparing impact effects of common storms
and Medicanes along the coast of south-eastern Sicily, Mar. Geol., 439, 106556,
https://doi.org/10.1016/j.margeo.2021.106556, 2021. a
Smagorinsky, J.: General circulation experiments with the primitive equations:
I. the basic experiment, Mon. Weather Rev., 91, 99–164,
https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2, 1963. a
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. a
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res.-Atmos., 106, 7183–7192,
https://doi.org/10.1029/2000JD900719, 2001. a
Tsimplis, M. N., Proctor, R., and Flather, R. A.: A two-dimensional tidal
model for the Mediterranean Sea, J. Geophys. Res.-Ocean.,
100, 16223–16239, https://doi.org/10.1029/95JC01671, 1995. a
Umgiesser, G., Melaku Canu, D., Cucco,
A., and Solidoro, C.: A finite element model for the Venice Lagoon, Development, set up,
calibration and validation, J. Mar. Syst., 51, 123–145, ISSN
0924-7963, doi10.1016/j.jmarsys.2004.05.009, 2004. a
Vilibić, I.: The role of the fundamental seiche in the Adriatic coastal
floods, Cont. Shelf Res., 26, 206–216,
https://doi.org/10.1016/j.csr.2005.11.001, 2006. a
Vilibić, I., Domijan, N., and Cupic, S.: Wind versus air pressure seiche
triggering in the Middle Adriatic coastal waters, J. Mar. Syst.,
57, 189–200, https://doi.org/10.1016/j.jmarsys.2005.04.007, 2005. a
Šepić, J., Pasarić, M., Međugorac, I., Vilibić, I., Karlović,
M., and Mlinar, M.: Climatology and process-oriented analysis of the
Adriatic sea level extremes, Prog. Oceanogr., 209, 102908,
https://doi.org/10.1016/j.pocean.2022.102908, 2022. a, b
Welch, P.: The use of fast Fourier transform for the estimation of power
spectra: A method based on time averaging over short, modified periodograms,
IEEE T. Audio Speech., 15, 70–73,
https://doi.org/10.1109/TAU.1967.1161901, 1967. a
Short summary
This work uses a hydrodynamic model which assimilates in situ data to reproduce tides, surges, and seiches in the Mediterranean basin. Furthermore, we study the periods of the barotropic modes of the Mediterranean and Adriatic basins. This research aims to improve the forecasting and reanalysis for operational warning and climatological studies. It aims also to reach a better knowledge of these sea level components in this area.
This work uses a hydrodynamic model which assimilates in situ data to reproduce tides, surges,...
