Articles | Volume 12, issue 1
https://doi.org/10.5194/os-12-71-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/os-12-71-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Modeling the ocean and atmosphere during an extreme bora event in northern Adriatic using one-way and two-way atmosphere–ocean coupling
NIB, National Institute of Biology, Marine Biology Station, Piran, Slovenia
P. Smerkol
NIB, National Institute of Biology, Marine Biology Station, Piran, Slovenia
A. Fettich
NIB, National Institute of Biology, Marine Biology Station, Piran, Slovenia
M. Ravdas
UOA, Ocean Physics and Modeling Group, University of Athens,
Athens, Greece
A. Papapostolou
UOA, Ocean Physics and Modeling Group, University of Athens,
Athens, Greece
A. Mantziafou
UOA, Ocean Physics and Modeling Group, University of Athens,
Athens, Greece
B. Strajnar
ARSO, Slovenian Environment Agency, Ljubljana,
Slovenia
J. Cedilnik
ARSO, Slovenian Environment Agency, Ljubljana,
Slovenia
M. Jeromel
ARSO, Slovenian Environment Agency, Ljubljana,
Slovenia
J. Jerman
ARSO, Slovenian Environment Agency, Ljubljana,
Slovenia
S. Petan
ARSO, Slovenian Environment Agency, Ljubljana,
Slovenia
V. Malačič
NIB, National Institute of Biology, Marine Biology Station, Piran, Slovenia
S. Sofianos
UOA, Ocean Physics and Modeling Group, University of Athens,
Athens, Greece
Related authors
Marko Rus, Hrvoje Mihanović, Matjaž Ličer, and Matej Kristan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2068, https://doi.org/10.5194/egusphere-2024-2068, 2024
Short summary
Short summary
HIDRA3 is a novel deep-learning model for predicting sea levels and storm surges, offering significant improvements over previous models and numerical simulations. It utilizes data from multiple tide gauges, enhancing predictions even with limited historical data and during sensor outages. With its advanced architecture, HIDRA3 outperforms the current state-of-the-art models by achieving up to 15 % lower mean absolute error, proving effective for coastal flood forecasting in diverse conditions.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
Short summary
Short summary
We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Marko Rus, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 16, 271–288, https://doi.org/10.5194/gmd-16-271-2023, https://doi.org/10.5194/gmd-16-271-2023, 2023
Short summary
Short summary
We propose a new fast and reliable deep-learning architecture HIDRA2 for sea level and storm surge modeling. HIDRA2 features new feature encoders and a fusion-regression block. We test HIDRA2 on Adriatic storm surges, which depend on an interaction between tides and seiches. We demonstrate that HIDRA2 learns to effectively mimic the timing and amplitude of Adriatic seiches. This is essential for reliable HIDRA2 predictions of total storm surge sea levels.
Nydia Catalina Reyes Suárez, Valentina Tirelli, Laura Ursella, Matjaž Ličer, Massimo Celio, and Vanessa Cardin
Ocean Sci., 18, 1321–1337, https://doi.org/10.5194/os-18-1321-2022, https://doi.org/10.5194/os-18-1321-2022, 2022
Short summary
Short summary
Explaining the dynamics of jellyfish blooms is a challenge for scientists. Biological and meteo-oceanographic data were combined on different timescales to explain the exceptional bloom of the jellyfish Rhizostoma pulmo in the Gulf of Trieste (Adriatic Sea) in April 2021. The bloom was associated with anomalously warm seasonal sea conditions. Then, a strong bora wind event enhanced upwelling and mixing of the water column, causing jellyfish to rise to the surface and accumulate along the coast.
Begoña Pérez Gómez, Ivica Vilibić, Jadranka Šepić, Iva Međugorac, Matjaž Ličer, Laurent Testut, Claire Fraboul, Marta Marcos, Hassen Abdellaoui, Enrique Álvarez Fanjul, Darko Barbalić, Benjamín Casas, Antonio Castaño-Tierno, Srđan Čupić, Aldo Drago, María Angeles Fraile, Daniele A. Galliano, Adam Gauci, Branislav Gloginja, Víctor Martín Guijarro, Maja Jeromel, Marcos Larrad Revuelto, Ayah Lazar, Ibrahim Haktan Keskin, Igor Medvedev, Abdelkader Menassri, Mohamed Aïssa Meslem, Hrvoje Mihanović, Sara Morucci, Dragos Niculescu, José Manuel Quijano de Benito, Josep Pascual, Atanas Palazov, Marco Picone, Fabio Raicich, Mohamed Said, Jordi Salat, Erdinc Sezen, Mehmet Simav, Georgios Sylaios, Elena Tel, Joaquín Tintoré, Klodian Zaimi, and George Zodiatis
Ocean Sci., 18, 997–1053, https://doi.org/10.5194/os-18-997-2022, https://doi.org/10.5194/os-18-997-2022, 2022
Short summary
Short summary
This description and mapping of coastal sea level monitoring networks in the Mediterranean and Black seas reveals the existence of 240 presently operational tide gauges. Information is provided about the type of sensor, time sampling, data availability, and ancillary measurements. An assessment of the fit-for-purpose status of the network is also included, along with recommendations to mitigate existing bottlenecks and improve the network, in a context of sea level rise and increasing extremes.
Emma Reyes, Eva Aguiar, Michele Bendoni, Maristella Berta, Carlo Brandini, Alejandro Cáceres-Euse, Fulvio Capodici, Vanessa Cardin, Daniela Cianelli, Giuseppe Ciraolo, Lorenzo Corgnati, Vlado Dadić, Bartolomeo Doronzo, Aldo Drago, Dylan Dumas, Pierpaolo Falco, Maria Fattorini, Maria J. Fernandes, Adam Gauci, Roberto Gómez, Annalisa Griffa, Charles-Antoine Guérin, Ismael Hernández-Carrasco, Jaime Hernández-Lasheras, Matjaž Ličer, Pablo Lorente, Marcello G. Magaldi, Carlo Mantovani, Hrvoje Mihanović, Anne Molcard, Baptiste Mourre, Adèle Révelard, Catalina Reyes-Suárez, Simona Saviano, Roberta Sciascia, Stefano Taddei, Joaquín Tintoré, Yaron Toledo, Marco Uttieri, Ivica Vilibić, Enrico Zambianchi, and Alejandro Orfila
Ocean Sci., 18, 797–837, https://doi.org/10.5194/os-18-797-2022, https://doi.org/10.5194/os-18-797-2022, 2022
Short summary
Short summary
This work reviews the existing advanced and emerging scientific and societal applications using HFR data, developed to address the major challenges identified in Mediterranean coastal waters organized around three main topics: maritime safety, extreme hazards and environmental transport processes. It also includes a discussion and preliminary assessment of the capabilities of existing HFR applications, finally providing a set of recommendations towards setting out future prospects.
Pablo Lorente, Eva Aguiar, Michele Bendoni, Maristella Berta, Carlo Brandini, Alejandro Cáceres-Euse, Fulvio Capodici, Daniela Cianelli, Giuseppe Ciraolo, Lorenzo Corgnati, Vlado Dadić, Bartolomeo Doronzo, Aldo Drago, Dylan Dumas, Pierpaolo Falco, Maria Fattorini, Adam Gauci, Roberto Gómez, Annalisa Griffa, Charles-Antoine Guérin, Ismael Hernández-Carrasco, Jaime Hernández-Lasheras, Matjaž Ličer, Marcello G. Magaldi, Carlo Mantovani, Hrvoje Mihanović, Anne Molcard, Baptiste Mourre, Alejandro Orfila, Adèle Révelard, Emma Reyes, Jorge Sánchez, Simona Saviano, Roberta Sciascia, Stefano Taddei, Joaquín Tintoré, Yaron Toledo, Laura Ursella, Marco Uttieri, Ivica Vilibić, Enrico Zambianchi, and Vanessa Cardin
Ocean Sci., 18, 761–795, https://doi.org/10.5194/os-18-761-2022, https://doi.org/10.5194/os-18-761-2022, 2022
Short summary
Short summary
High-frequency radar (HFR) is a land-based remote sensing technology that can provide maps of the surface circulation over broad coastal areas, along with wave and wind information. The main goal of this work is to showcase the current status of the Mediterranean HFR network as well as present and future applications of this sensor for societal benefit such as search and rescue operations, safe vessel navigation, tracking of marine pollutants, and the monitoring of extreme events.
Lojze Žust, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 14, 2057–2074, https://doi.org/10.5194/gmd-14-2057-2021, https://doi.org/10.5194/gmd-14-2057-2021, 2021
Short summary
Short summary
Adriatic basin sea level modelling is a challenging problem due to the interplay between terrain, weather, tides and seiches. Current state-of-the-art numerical models (e.g. NEMO) require large computational resources to produce reliable forecasts. In this study we propose HIDRA, a novel deep learning approach for sea level modeling, which drastically reduces the numerical cost while demonstrating predictive capabilities comparable to that of the NEMO model, outperforming it in many instances.
Matjaž Ličer, Solène Estival, Catalina Reyes-Suarez, Davide Deponte, and Anja Fettich
Nat. Hazards Earth Syst. Sci., 20, 2335–2349, https://doi.org/10.5194/nhess-20-2335-2020, https://doi.org/10.5194/nhess-20-2335-2020, 2020
Short summary
Short summary
In 2018 windsurfer’s mast broke about 1 km offshore during a scirocco storm in the northern Adriatic. He was drifting in severe conditions until he eventually beached alive and well in Sistiana (Italy) 24 h later. We conducted an interview with the survivor to reconstruct his trajectory. We simulate his trajectory in several ways and estimate the optimal search-and-rescue area for a civil rescue response. Properly calibrated virtual drifter properties are key to reliable rescue area forecasting.
Alexander Barth, Aida Alvera-Azcárate, Matjaz Licer, and Jean-Marie Beckers
Geosci. Model Dev., 13, 1609–1622, https://doi.org/10.5194/gmd-13-1609-2020, https://doi.org/10.5194/gmd-13-1609-2020, 2020
Short summary
Short summary
DINCAE is a method for reconstructing missing data in satellite datasets using a neural network. Satellite observations working in the optical and infrared bands are affected by clouds, which obscure part of the ocean underneath. In this paper, a neural network with the structure of a convolutional auto-encoder is developed to reconstruct the missing data based on the available cloud-free pixels in satellite images.
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.
Marko Rus, Hrvoje Mihanović, Matjaž Ličer, and Matej Kristan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2068, https://doi.org/10.5194/egusphere-2024-2068, 2024
Short summary
Short summary
HIDRA3 is a novel deep-learning model for predicting sea levels and storm surges, offering significant improvements over previous models and numerical simulations. It utilizes data from multiple tide gauges, enhancing predictions even with limited historical data and during sensor outages. With its advanced architecture, HIDRA3 outperforms the current state-of-the-art models by achieving up to 15 % lower mean absolute error, proving effective for coastal flood forecasting in diverse conditions.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
Short summary
Short summary
We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Peter Smerkol, Vito Švagelj, Anton Zgonc, and Benedikt Strajnar
EGUsphere, https://doi.org/10.5194/egusphere-2023-1182, https://doi.org/10.5194/egusphere-2023-1182, 2023
Preprint withdrawn
Short summary
Short summary
Meteorological radars measure precipitation and radial winds, but a trade-off exists between the coverage and the Nyquist interval where wind is unambiguously determined. The goal of this paper is to extend the usability of wind measurements using the torus mapping dealiasing algorithm. Validation against radiosonde and aircraft observations, and short-range model forecasts shows a stable performance and good quality of resulting winds, suggesting implementation at the European scale.
Marko Rus, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 16, 271–288, https://doi.org/10.5194/gmd-16-271-2023, https://doi.org/10.5194/gmd-16-271-2023, 2023
Short summary
Short summary
We propose a new fast and reliable deep-learning architecture HIDRA2 for sea level and storm surge modeling. HIDRA2 features new feature encoders and a fusion-regression block. We test HIDRA2 on Adriatic storm surges, which depend on an interaction between tides and seiches. We demonstrate that HIDRA2 learns to effectively mimic the timing and amplitude of Adriatic seiches. This is essential for reliable HIDRA2 predictions of total storm surge sea levels.
Nydia Catalina Reyes Suárez, Valentina Tirelli, Laura Ursella, Matjaž Ličer, Massimo Celio, and Vanessa Cardin
Ocean Sci., 18, 1321–1337, https://doi.org/10.5194/os-18-1321-2022, https://doi.org/10.5194/os-18-1321-2022, 2022
Short summary
Short summary
Explaining the dynamics of jellyfish blooms is a challenge for scientists. Biological and meteo-oceanographic data were combined on different timescales to explain the exceptional bloom of the jellyfish Rhizostoma pulmo in the Gulf of Trieste (Adriatic Sea) in April 2021. The bloom was associated with anomalously warm seasonal sea conditions. Then, a strong bora wind event enhanced upwelling and mixing of the water column, causing jellyfish to rise to the surface and accumulate along the coast.
Begoña Pérez Gómez, Ivica Vilibić, Jadranka Šepić, Iva Međugorac, Matjaž Ličer, Laurent Testut, Claire Fraboul, Marta Marcos, Hassen Abdellaoui, Enrique Álvarez Fanjul, Darko Barbalić, Benjamín Casas, Antonio Castaño-Tierno, Srđan Čupić, Aldo Drago, María Angeles Fraile, Daniele A. Galliano, Adam Gauci, Branislav Gloginja, Víctor Martín Guijarro, Maja Jeromel, Marcos Larrad Revuelto, Ayah Lazar, Ibrahim Haktan Keskin, Igor Medvedev, Abdelkader Menassri, Mohamed Aïssa Meslem, Hrvoje Mihanović, Sara Morucci, Dragos Niculescu, José Manuel Quijano de Benito, Josep Pascual, Atanas Palazov, Marco Picone, Fabio Raicich, Mohamed Said, Jordi Salat, Erdinc Sezen, Mehmet Simav, Georgios Sylaios, Elena Tel, Joaquín Tintoré, Klodian Zaimi, and George Zodiatis
Ocean Sci., 18, 997–1053, https://doi.org/10.5194/os-18-997-2022, https://doi.org/10.5194/os-18-997-2022, 2022
Short summary
Short summary
This description and mapping of coastal sea level monitoring networks in the Mediterranean and Black seas reveals the existence of 240 presently operational tide gauges. Information is provided about the type of sensor, time sampling, data availability, and ancillary measurements. An assessment of the fit-for-purpose status of the network is also included, along with recommendations to mitigate existing bottlenecks and improve the network, in a context of sea level rise and increasing extremes.
Emma Reyes, Eva Aguiar, Michele Bendoni, Maristella Berta, Carlo Brandini, Alejandro Cáceres-Euse, Fulvio Capodici, Vanessa Cardin, Daniela Cianelli, Giuseppe Ciraolo, Lorenzo Corgnati, Vlado Dadić, Bartolomeo Doronzo, Aldo Drago, Dylan Dumas, Pierpaolo Falco, Maria Fattorini, Maria J. Fernandes, Adam Gauci, Roberto Gómez, Annalisa Griffa, Charles-Antoine Guérin, Ismael Hernández-Carrasco, Jaime Hernández-Lasheras, Matjaž Ličer, Pablo Lorente, Marcello G. Magaldi, Carlo Mantovani, Hrvoje Mihanović, Anne Molcard, Baptiste Mourre, Adèle Révelard, Catalina Reyes-Suárez, Simona Saviano, Roberta Sciascia, Stefano Taddei, Joaquín Tintoré, Yaron Toledo, Marco Uttieri, Ivica Vilibić, Enrico Zambianchi, and Alejandro Orfila
Ocean Sci., 18, 797–837, https://doi.org/10.5194/os-18-797-2022, https://doi.org/10.5194/os-18-797-2022, 2022
Short summary
Short summary
This work reviews the existing advanced and emerging scientific and societal applications using HFR data, developed to address the major challenges identified in Mediterranean coastal waters organized around three main topics: maritime safety, extreme hazards and environmental transport processes. It also includes a discussion and preliminary assessment of the capabilities of existing HFR applications, finally providing a set of recommendations towards setting out future prospects.
Pablo Lorente, Eva Aguiar, Michele Bendoni, Maristella Berta, Carlo Brandini, Alejandro Cáceres-Euse, Fulvio Capodici, Daniela Cianelli, Giuseppe Ciraolo, Lorenzo Corgnati, Vlado Dadić, Bartolomeo Doronzo, Aldo Drago, Dylan Dumas, Pierpaolo Falco, Maria Fattorini, Adam Gauci, Roberto Gómez, Annalisa Griffa, Charles-Antoine Guérin, Ismael Hernández-Carrasco, Jaime Hernández-Lasheras, Matjaž Ličer, Marcello G. Magaldi, Carlo Mantovani, Hrvoje Mihanović, Anne Molcard, Baptiste Mourre, Alejandro Orfila, Adèle Révelard, Emma Reyes, Jorge Sánchez, Simona Saviano, Roberta Sciascia, Stefano Taddei, Joaquín Tintoré, Yaron Toledo, Laura Ursella, Marco Uttieri, Ivica Vilibić, Enrico Zambianchi, and Vanessa Cardin
Ocean Sci., 18, 761–795, https://doi.org/10.5194/os-18-761-2022, https://doi.org/10.5194/os-18-761-2022, 2022
Short summary
Short summary
High-frequency radar (HFR) is a land-based remote sensing technology that can provide maps of the surface circulation over broad coastal areas, along with wave and wind information. The main goal of this work is to showcase the current status of the Mediterranean HFR network as well as present and future applications of this sensor for societal benefit such as search and rescue operations, safe vessel navigation, tracking of marine pollutants, and the monitoring of extreme events.
Konstantinos Kampouris, Vassilios Vervatis, John Karagiorgos, and Sarantis Sofianos
Ocean Sci., 17, 919–934, https://doi.org/10.5194/os-17-919-2021, https://doi.org/10.5194/os-17-919-2021, 2021
Short summary
Short summary
The wind is a source of uncertainty in oil spill modeling. We performed oil spill ensemble simulations using an atmospheric ensemble to quantify this uncertainty. We investigate the reliability of oil spill ensemble prediction used as an important forecasting tool to better plan mitigation procedures in the event of an oil spill.
Lojze Žust, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 14, 2057–2074, https://doi.org/10.5194/gmd-14-2057-2021, https://doi.org/10.5194/gmd-14-2057-2021, 2021
Short summary
Short summary
Adriatic basin sea level modelling is a challenging problem due to the interplay between terrain, weather, tides and seiches. Current state-of-the-art numerical models (e.g. NEMO) require large computational resources to produce reliable forecasts. In this study we propose HIDRA, a novel deep learning approach for sea level modeling, which drastically reduces the numerical cost while demonstrating predictive capabilities comparable to that of the NEMO model, outperforming it in many instances.
Matjaž Ličer, Solène Estival, Catalina Reyes-Suarez, Davide Deponte, and Anja Fettich
Nat. Hazards Earth Syst. Sci., 20, 2335–2349, https://doi.org/10.5194/nhess-20-2335-2020, https://doi.org/10.5194/nhess-20-2335-2020, 2020
Short summary
Short summary
In 2018 windsurfer’s mast broke about 1 km offshore during a scirocco storm in the northern Adriatic. He was drifting in severe conditions until he eventually beached alive and well in Sistiana (Italy) 24 h later. We conducted an interview with the survivor to reconstruct his trajectory. We simulate his trajectory in several ways and estimate the optimal search-and-rescue area for a civil rescue response. Properly calibrated virtual drifter properties are key to reliable rescue area forecasting.
Natalia Stamataki, Yannis Hatzonikolakis, Kostas Tsiaras, Catherine Tsangaris, George Petihakis, Sarantis Sofianos, and George Triantafyllou
Ocean Sci., 16, 927–949, https://doi.org/10.5194/os-16-927-2020, https://doi.org/10.5194/os-16-927-2020, 2020
Short summary
Short summary
This study examines the accumulation of microplastics on wild and cultured mussels through a dynamic energy budget model, resulting in a comparable contamination level but different cleaning time for the mussels. Our main findings highlight that microplastics contamination is strongly dependent on the variability of specific environmental aspects and improve the knowledge of the transport and accumulation of microplastics in the mussels, enlightening future work on a biomagnification scenario.
Alexander Barth, Aida Alvera-Azcárate, Matjaz Licer, and Jean-Marie Beckers
Geosci. Model Dev., 13, 1609–1622, https://doi.org/10.5194/gmd-13-1609-2020, https://doi.org/10.5194/gmd-13-1609-2020, 2020
Short summary
Short summary
DINCAE is a method for reconstructing missing data in satellite datasets using a neural network. Satellite observations working in the optical and infrared bands are affected by clouds, which obscure part of the ocean underneath. In this paper, a neural network with the structure of a convolutional auto-encoder is developed to reconstruct the missing data based on the available cloud-free pixels in satellite images.
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.
Vassilios D. Vervatis, Pierre De Mey-Frémaux, Nadia Ayoub, Sarantis Sofianos, Charles-Emmanuel Testut, Marios Kailas, John Karagiorgos, and Malek Ghantous
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-31, https://doi.org/10.5194/gmd-2019-31, 2019
Revised manuscript not accepted
Short summary
Short summary
Our contributions were specifically targeted at the generation of ensembles, in particular (but not solely) for high-resolution ocean configurations including regional and coastal physics and biogeochemistry. The most important paradigm of this work was to adopt a balanced approach building ocean biogeochemical model ensembles and testing their relevance against observational networks monitoring upper-ocean properties, in the sense of nonzero joint probabilities.
Athanasia Iona, Athanasios Theodorou, Sarantis Sofianos, Sylvain Watelet, Charles Troupin, and Jean-Marie Beckers
Earth Syst. Sci. Data, 10, 1829–1842, https://doi.org/10.5194/essd-10-1829-2018, https://doi.org/10.5194/essd-10-1829-2018, 2018
Short summary
Short summary
The paper introduces a new product composed of a set of climatic indices from 1950 to 2015 for the Mediterranean Sea. It is produced from a high-resolution decadal climatology of temperature and salinity on a 1/8 degree regular grid based on the SeaDataNet V2 historical data collection. The climatic indices can contribute to the studies of the long-term variability of the Mediterranean Sea and the better understanding of the complex response of the region to the ongoing global climate change.
Francesco Marcello Falcieri, Lakshmi Kantha, Alvise Benetazzo, Andrea Bergamasco, Davide Bonaldo, Francesco Barbariol, Vlado Malačič, Mauro Sclavo, and Sandro Carniel
Ocean Sci., 12, 433–449, https://doi.org/10.5194/os-12-433-2016, https://doi.org/10.5194/os-12-433-2016, 2016
Short summary
Short summary
Between January 30th and February 4th we collected the first turbulence observations in the Gulf of Trieste under different wind forcing and water column structure. The vertical profiles of the turbulence kinetic energy dissipation rates showed that the presence near the sea floor of different water masses, inflowing from the open sea, can prevent the complete mixing of the water column. This dumping effect is enhanced when these masses present higher suspended sediment concentrations.
P. Malanotte-Rizzoli, V. Artale, G. L. Borzelli-Eusebi, S. Brenner, A. Crise, M. Gacic, N. Kress, S. Marullo, M. Ribera d'Alcalà, S. Sofianos, T. Tanhua, A. Theocharis, M. Alvarez, Y. Ashkenazy, A. Bergamasco, V. Cardin, S. Carniel, G. Civitarese, F. D'Ortenzio, J. Font, E. Garcia-Ladona, J. M. Garcia-Lafuente, A. Gogou, M. Gregoire, D. Hainbucher, H. Kontoyannis, V. Kovacevic, E. Kraskapoulou, G. Kroskos, A. Incarbona, M. G. Mazzocchi, M. Orlic, E. Ozsoy, A. Pascual, P.-M. Poulain, W. Roether, A. Rubino, K. Schroeder, J. Siokou-Frangou, E. Souvermezoglou, M. Sprovieri, J. Tintoré, and G. Triantafyllou
Ocean Sci., 10, 281–322, https://doi.org/10.5194/os-10-281-2014, https://doi.org/10.5194/os-10-281-2014, 2014
R. Hamdi, D. Degrauwe, A. Duerinckx, J. Cedilnik, V. Costa, T. Dalkilic, K. Essaouini, M. Jerczynki, F. Kocaman, L. Kullmann, J.-F. Mahfouf, F. Meier, M. Sassi, S. Schneider, F. Váňa, and P. Termonia
Geosci. Model Dev., 7, 23–39, https://doi.org/10.5194/gmd-7-23-2014, https://doi.org/10.5194/gmd-7-23-2014, 2014
Related subject area
Approach: Numerical Models | Depth range: Shelf-sea depth | Geographical range: Mediterranean Sea | Phenomena: Temperature, Salinity and Density Fields
Validation of an ocean shelf model for the prediction of mixed-layer properties in the Mediterranean Sea west of Sardinia
Reiner Onken
Ocean Sci., 13, 235–257, https://doi.org/10.5194/os-13-235-2017, https://doi.org/10.5194/os-13-235-2017, 2017
Short summary
Short summary
A numerical ocean circulation model has been employed to explore the
sensitivity of the forecast skill of mixed-layer properties to the
initial conditions, boundary conditions, and vertical mixing
parameterisations. All forecasts were validated against observations
which were taken in June 2014 to the west of Sardinia.
Cited articles
Artegiani, A., Bregant, D., Paschini, E., Pinardi, N., Raicich, F., and Russo, A.:
The Adriatic Sea General Circulation I: Air-Sea Interactions and Water Mass Structure, J. Phys. Oceanogr., 27, 1492–1514,
https://doi.org/10.1175/1520-0485(1997)027<1492:TASGCP>2.0.CO;2,
1997.
Benetazzo, A., Bergamasco, A., Bonaldo, D., Falcieria, F. M., Sclavo, M.,
Langone, L., and Carniel, S.: Response of the Adriatic Sea to an intense cold air outbreak: dense water dynamics and wave-induced transport, Prog.
Oceanogr., 128, 115–138, https://doi.org/10.1016/j.pocean.2014.08.015, 2014.
Blumberg, A. F. and Mellor, G. L.: A description of a three-dimensional coastal ocean circulation model, in: Three-Dimensional Coastal Ocean Models,
edited by: Heaps, N., American Geophysical Union, Washington, DC, USA, 1–16,
1987.
Cosoli, S., Ličer, M., Vodopivec, M., and Malačič, V.: Surface circulation in the Gulf of Trieste (northern Adriatic Sea) from radar, model,
and ADCP comparisons, J. Geophys. Res.-Oceans, 118, 6183–6200,
https://doi.org/10.1002/2013JC009261, 2013.
Cushman-Roisin, B., Gačić, M., Poulain, P.-M., and Artegiani, A.: Physical
Oceanography of the Adriatic Sea. Past, Present and Future,
Springer, London, UK, 47–48, 2001.
Davies, H. C.: A lateral boundary formulation for multi-level prediction models, Q. J. Roy. Meteor. Soc., 102, 405–418, 1976.
Donlon, C. J., Martin, M., Stark, J. D., Roberts-Jones, J., Fiedler, E., and Wimmer, W.: The Operational Sea Surface Temperature and Sea Ice Analysis
(OSTIA), Remote Sens. Environ., 116, 140–158,
https://doi.org/10.1016/j.rse.2010.10.017, 2012.
Dorman, C. E., Carniel, S., Cavaleri, L., Sclavo, M., Chiggiato, J.,
Doyle, J., Haack, T., Pullen, J., Grbec, B., Vilibić, I.,
Janeković, I., Lee, C., Malačič, V., Orlić, M., Paschini, E.,
Russo, A., and Signell, R. P.: February 2003 marine atmospheric conditions and the bora over the northern Adriatic, J. Geophys. Res., 111, C03S03,
https://doi.org/10.1029/2005JC003134, 2006.
Eleuterio, D.: A Comparison of Bulk Aerodynamic Methods for Calculating Air-Sea Flux, Master Thesis, Naval Postgraduate School, Monterey, CA, USA, available at:
https://doi.org/http://www.researchgate.net/publication/235119736_A_Comparison_of_Bulk_Aerodynamic_Methods_for_Calculating_Air-Sea_Flux (last access: 14 October 2015), 1998.
Fairall, C. W., Bradley, E. F., Rogers, D. P., Edson, J. B., and Young, G. S.:
Bulk parameterization of air-sea fluxes for Tropical Ocean Global Atmosphere
Coupled-Ocean Atmosphere Response Experiment, J. Geophys. Res., 101,
3747–3764, https://doi.org/10.1029/95JC03205, 1996.
Fischer, C., Montmerle, T., Berre, L., Auger, L., and
Ştefănescu, S. E.: An overview of the variational assimilation in the
ALADIN/France numerical weather-prediction system, Q. J. Roy. Meteor. Soc.,
131, 3477–3492, https://doi.org/10.1256/qj.05.115, 2005.
Gerard, L., Piriou, J.-M., Brožková, R., Geleyn, J.-F., and
Banciu, D.: Cloud and precipitation parameterization in a meso-gamma-scale
operational weather prediction model, Mon. Weather Rev., 137, 3960–3977,
https://doi.org/10.1175/2009MWR2750.1, 2009.
Grisogono, B. and Belušić, D.: A review of recent advances in understanding the meso- and microscale properties of severe Bora wind, Tellus, 61A, 1–16,
https://doi.org/10.1111/j.1600-0870.2008.00369.x, 2009.
Janeković, I., Mihanović, H., Vilibić, I., and Tudor, M.: Extreme
cooling and dense water formation estimates in open and coastal regions of
the Adriatic Sea during the winter of 2012, J. Geophys. Res.-Oceans, 119,
3200–3218, https://doi.org/10.1002/2014JC009865, 2014.
Kourafalou, V. H.: River plume development in semi-enclosed Mediterranean regions: north Adriatic Sea and northwestern Aegean Sea, J. Marine Syst., 30,
181–205, https://doi.org/10.1016/S0924-7963(01)00058-6, 2001.
Kuzmić, M., Janeković, I., Book, J. W., Martin, P. J., and
Doyle, J. D.: Modeling the northern Adriatic double-gyre response to intense
bora wind: a revisit, J. Geophys. Res., 111, C03S13,
https://doi.org/10.1029/2005JC003377, 2007.
Malačič, V. and Petelin, B.: Climatic circulation in the Gulf of Trieste (northern Adriatic), J. Geophys. Res., 114, C07002,
https://doi.org/10.1029/2008JC004904, 2009.
Malačič, V., Petelin, B., and Vodopivec, M.: Topographic control of wind-driven circulation in the northern Adriatic, J. Geophys. Res., 117,
C06032, https://doi.org/10.1029/2012JC008063, 2012.
Mantziafou, A. and Lascaratos, A.: Deep-water formation in the Adriatic Sea:
interannual simulations for the years 1979–1999, Deep-Sea Res. Pt. I, 55,
1403–1427, https://doi.org/10.1016/j.dsr.2008.06.005, 2008.
Mascart, P., Noilhan, J., and Giordani, H.: A modified parametrization of
flux-profile relationships in the surface layer using different roughness
length values for heat and momentum, Bound.-Lay. Meteorol., 72, 331–344,
https://doi.org/10.1007/BF00708998, 1995.
Mellor, G.: Users Guide for a Three-Dimensional, Primitive Equation,
Numerical Ocean Model, Tech. Rep., Princeton University, Princeton, NJ, USA, 1998.
Mihanović, H., Vilibić, I., Carniel, S., Tudor, M., Russo, A.,
Bergamasco, A., Bubić, N., Ljubešić, Z., Viličić, D.,
Boldrin, A., Malačič, V., Celio, M., Comici, C., and Raicich, F.:
Exceptional dense water formation on the Adriatic shelf in the winter of 2012, Ocean Sci., 111, 561–572, https://doi.org/10.5194/os-9-561-2013, 2013.
Nielsen, S. and Hansen, E.: Numerical simulation of the rainfall-runoff process on a daily basis, Nord. Hydrol., 4, 171–190, 1973.
Paklar, G. B., Isakov, V., Koračin, D., Kourafalou, V., and
Orlić, M.: A case study of bora-driven flow and density changes on the
Adriatic Shelf (January 1987), Cont. Shelf. Res., 21, 1751–1783,
https://doi.org/10.1016/S0278-4343(01)00029-2, 2001.
Pullen, J., Doyle, J., Hodur, R., Ogston, A., Book, J., Perkins, H., and
Signell, R.: Coupled ocean-atmosphere nested modeling of the Adriatic Sea
during winter and spring 2001, J. Geophys. Res., 108, 3320,
https://doi.org/10.1029/2003JC001780, 2003.
Pullen, J., Doyle, J., and Signell, R.: Two-way air–sea coupling: a study of the Adriatic, Mon. Weather Rev., 134, 1465–1483, https://doi.org/10.1175/MWR3137.1,
2006.
Pullen, J., Doyle, J., Haack, T., Dorman, C., Signell, R., and Lee, C. M.:
Bora event variability and the role of air-sea feedback, J. Geophys. Res.,
112, 33407, https://doi.org/10.1029/2006JC003726, 2007.
Raicich, F.: Notes on the Flow Rates of the Adriatic Rivers, tech. rep., CNR,
Ist. Sper. Talassografico, Trieste, Italy, 1994.
Raicich, F., Malačič, C., Celio, M., Giaiotti, D., Cantoni, C.,
Colucci, R. R., Čermelj, B., and Pucillo, A.: Extreme air-sea
interactions in the Gulf of Trieste (North Adriatic) during the strong Bora
event in winter 2012, J. Geophys. Res.-Oceans, 118, 5238–5250,
https://doi.org/10.1002/jgrc.20398, 2013.
Seity, Y., Brousseau, P.,Malardel, S., Hello, G., Benard, P., Bouttier, F.,
Lac, C., and Masson, V.: The AROME-France convective-scale operational model, Mon.
Weather Rev., 139, 976–991, https://doi.org/10.1175/2010MWR3425.1,
2011.
Strajnar, B., Žagar, N., and Berre, L.: Impact of new aircraft
observations Mode-S MRAR in a mesoscale NWP model, J. Geophys. Res.-Atmos.,
120, 3920–3938, https://doi.org/10.1002/2014JD022654, 2015.
Tonani, M., Pinardi, N., Fratianni, C., Pistoia, J., Dobricic, S., Pensieri,
S., de Alfonso, M., and Nittis, K.: Mediterranean Forecasting System:
forecast and analysis assessment through skill scores, Ocean Sci., 5,
649–660, https://doi.org/10.5194/os-5-649-2009, 2009.
Tudor, M. and Ivatek-Šahdan, S.: The case study of bura of 1st and 3rd
February 2007, Meteorologische Zeitschrift, 19, 453–466,
https://doi.org/10.1127/0941-2948/2010/0475, 2010.
Valcke, S.: The OASIS3 coupler: a European climate modelling community
software, Geosci. Model Dev., 6, 373–388, https://doi.org/10.5194/gmd-6-373-2013, 2013.
Zore-Armanda, M., and Gačić, M.: Effects of Bora on the circulation in the northern Adriatic, Ann. Geophys., 5, 93–102, 1987.
Short summary
We compare the northern Adriatic response to an extreme bora event, as simulated by one-way and two-way (i.e. with ocean feedback to the atmosphere) atmosphere-ocean coupling. We show that two-way coupling yields significantly better estimates of heat fluxes, most notably sensible heat flux, across the air-sea interface. When compared to observations in the northern Adriatic, two-way coupled system consequently leads to a better representation of ocean temperatures throughout the event.
We compare the northern Adriatic response to an extreme bora event, as simulated by one-way and...