Ali Aydoğdu

CMCC Foundation - Euro-Mediterranean Center on Climate Change

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Simona Masina

CMCC Foundation - Euro-Mediterranean Center on Climate Change

Nadia Pinardi

University of Bologna

Emanuela Clementi

CMCC Foundation - Euro-Mediterranean Center on Climate Change

Andrea Cipollone

CMCC Foundation - Euro-Mediterranean Center on Climate Change

Giovanni Coppini

CMCC Foundation - Euro-Mediterranean Center on Climate Change

Romain Escudier

Mercator Ocean (France)

Jenny Pistoia

CMCC Foundation - Euro-Mediterranean Center on Climate Change

Gianpiero Cossarini

National Institute of Oceanography

Rita Lecci

CMCC Foundation - Euro-Mediterranean Center on Climate Change

Massimiliano Drudi

CMCC Foundation - Euro-Mediterranean Center on Climate Change

Cooperative Institutions

CMCC Foundation - Euro-Mediterranean Center on Climate Change

Centre National de la Recherche Scientifique

National Institute of Oceanography and Applied Geophysics

Mercator Ocean (France)

National Research Council

Institute of Marine Science

Central Maine Community College

National Institute of Oceanography

Institute of Structure of Matter

Institut de Recherche pour le Développement

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Improved Arctic sea ice forecasting by combining ensemble Kalman filter with a Lagrangian sea ice model

Sukun Cheng Yumeng Chen Ali Aydoğdu Laurent Bertino Alberto Carrassi

&#160;Advanced data assimilation methods can improve the forecast of Arctic sea ice, which has been widely used in climate modeling systems to merge observations into simulations. We apply the deterministic Ensemble Kalman filter (DEnKF) to a Lagrangian sea ice model, neXtSIM for sea ice forecast. neXtSIM is computationally solved on a time-dependent evolving mesh, causing a key challenge for applying the EnKF since the mesh grid number and positions are generally different in each ensemble member. The DEnKF analysis is performed on a fixed reference mesh, where model variables are interpolated between the reference mesh and the individual ensemble meshes before and after the assimilation. An ensemble-DA forecasting system for Arctic sea ice forecast based on neXtSIM is built by assimilating the OSI-SAF sea ice concentration (SIC) and the CS2SMOS sea ice thickness (SIT). The ensemble is generated by perturbing atmospheric and oceanic forcing online throughout the forecast. We evaluate the impact of sea-ice assimilation on the Arctic winter sea-ice forecast skills against the satellite observations and a free run during the 2019-2020 Arctic winter. Significant improvements in modeled SIT indicate the importance of assimilating CS2SMOS thickness. While the improvement of SIC and ice extend are clearly observed only in the case with daily assimilating OSI-SAF SIC, which avoids the constraint of daily loaded ocean variables. We found that assimilating a special observation gives the best forecast skill of the relevant variables. With a proper assimilation strategy, neXtSIM as a stand-alone sea ice model could perform computationally efficiently and maintain good forecast skills compared with coupled models.

10.5194/egusphere-egu22-1113

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A High Resolution Reanalysis for the Mediterranean Sea

Frontiers in Earth Science (2021)

Romain Escudier Emanuela Clementi Andrea Cipollone Jenny Pistoia Massimiliano Drudi

In order to be able to forecast the weather and estimate future climate changes in the ocean, it is crucial to understand the past and the mechanisms responsible for the ocean variability. This is particularly true in a complex area such as the Mediterranean Sea with diverse dynamics like deep convection and overturning circulation. To this end, effective tools are ocean reanalyses or reconstructions of the past ocean state. Here we present a new physical reanalysis of the Mediterranean Sea at high resolution, developed in the Copernicus Marine Environment Monitoring Service (CMEMS) framework. The hydrodynamic model is based on the Nucleus for European Modelling of the Ocean (NEMO) combined with a variational data assimilation scheme (OceanVar). The model has a horizontal resolution of 1/24° and 141 unevenly distributed vertical z* levels. It provides daily and monthly temperature, salinity, current, sea level and mixed layer depth as well as hourly fields for surface velocities and sea level. ECMWF ERA-5 atmospheric fields force the model and daily boundary conditions in the Atlantic are taken from a global reanalysis. The reanalysis covers the 33 years from 1987 to 2019. Initialized from SeaDataNet climatology in January 1985, it reaches a nominal state after a 2-years spin-up. In-situ data from CTD, ARGO floats and XBT are assimilated into the model in combination with satellite altimetry observations. This reanalysis has been validated and assessed through comparison to in-situ and satellite observations as well as literature climatologies. The results show an overall improvement of the comparison with observations and a better representation of the main dynamics of the region compared to a previous, lower resolution (1/16°), reanalysis. Temperature and salinity RMSD are decreased by respectively 14 and 18%. The salinity biases at depth of the previous version are corrected. Climate signals show continuous increase of the temperature and salinity, confirming estimates from observations and other reanalysis. The new reanalysis will allow the study of physical processes at multi-scales, from the large scale to the transient small mesoscale structures and the selection of climate indicators for the basin.

Argo

Bathythermograph

Ocean surface topography

Ocean dynamics

Ocean observations

Boundary current

10.3389/feart.2021.702285

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Citations (104)

Ensemble Kalman Filter for non-conservative moving mesh solvers with a joint physics and mesh location update

Christian Sampson Alberto Carrassi Ali Aydoğdu Chris K. R. T. Jones

Numerical solvers using adaptive meshes can focus computational power on important regions of a model domain capturing important or unresolved physics. The adaptation can be informed by the model state, external information, or made to depend on the model physics.&#160; &#160;In this latter case, one can think of the mesh configuration&#160; as part of the model state. If observational data is to be assimilated into the model, the question of updating the mesh configuration with the physical values arises. Adaptive meshes present significant challenges when using popular ensemble Data Assimilation (DA) methods. We develop a novel strategy for ensemble-based DA for which the adaptive mesh is updated along with the physical values. This involves including the node locations as a part of the model state itself allowing them to be updated automatically at the analysis step. This poses a number of challenges which we resolve to produce an effective approach that promises to apply with some generality. We evaluate our strategy with two testbed models in 1-d comparing to a strategy that we previously developed that does not update the mesh configuration. We find updating the mesh improves the fidelity and convergence of the filter. An extensive analysis on the performance of our scheme beyond just the RMSE error is also presented.

Adaptive Mesh Refinement

Benchmark (surveying)

Testbed

10.5194/egusphere-egu21-16403

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Anomalous 2022 deep-water formation and intense phytoplankton bloom in the Cretan area

State of the Planet (2024)

Anna Teruzzi Ali Aydoğdu Carolina Amadio Emanuela Clementi Simone Colella

Abstract. The Mediterranean Sea is a quasi-permanently stratified and oligotrophic basin with intense late-winter and early-spring phytoplankton blooms typically limited to few regions (i.e. northwestern Mediterranean Sea, the southern Adriatic Sea, and the Rhodes Gyre). In these areas, blooms are sustained by nutrient injection to surface layers by winter vertical mixing and convective processes. A markedly intense bloom was predicted in spring 2022 in an unusual area of the southeastern Mediterranean Sea (i.e. southeast of Crete) by the Mediterranean Sea Copernicus Marine Forecasting Centre (MED MFC) system. Combining Copernicus modelling and observation products, the 2022 event and a number of driving and concurrent features have been investigated in a multidisciplinary way. A noticeable cold spell that occurred in Eastern Europe at the beginning of 2022 has been identified as the main driver of an intense deep-water formation event, with associated high nutrient concentrations in the surface layers. Consequently, an extreme phytoplankton bloom that was 50 % more intense than usual occurred in the area southeast of Crete, starting nearly 1 month later than usual and lasting for 3–4 weeks. Impacts on primary production were also relevant in the 2022 event area and were 35 % higher than the climatological annual primary production. Furthermore, the documented link between primary productivity and fishery catches suggests possible consequences along the whole food chain up to the marine ecosystem in the eastern Mediterranean Sea.

Bloom

10.5194/sp-4-osr8-15-2024

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Comment on egusphere-2022-1337

Giovanni Coppini Emanuela Clementi Gianpiero Cossarini Stefano Salon Γεράσιμος Κορρές

Abstract. The Mediterranean Forecasting Systems produces operational analyses, reanalyses and 10-day forecasts for many Essential Ocean Variables (EOVs), from currents, temperature to wind waves and pelagic biogeochemistry. The products are available at a horizontal resolution of 1/24 degrees (approximately 4 km) and 141 unevenly spaced vertical levels. The core of the Mediterranean Forecasting System is constituted by the physical (PHY), the biogeochemical (BIO) and the wave (WAV) components coupled offline, consisting of both numerical models and data assimilation modules. The 3 components together constitute the so-called Mediterranean Monitoring and Forecasting Center (Med-MFC) of the Copernicus Marine Service. Daily 10-day forecasts are produced by the PHY, BIO and WAV components as well as analyses, while reanalyses are produced for the past 30 years about every ~3 years and extended (yearly). The modelling systems, their coupling strategy and evolution is illustrated in detail. For the first time, the quality of the products is documented in terms of skill metrics evaluated on a common three-year period (2018–2020), giving the first complete assessment of uncertainties for all the Mediterranean environmental variable analyses.

Biogeochemistry

Biogeochemical Cycle

10.5194/egusphere-2022-1337-cc1

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Arctic sea ice data assimilation combining an ensemble Kalman filter with a novel Lagrangian sea ice model for the winter 2019–2020

The cryosphere (2023)

Sukun Cheng Yumeng Chen Ali Aydoğdu Laurent Bertino Alberto Carrassi

Abstract. Advanced data assimilation (DA) methods, widely used in geophysical and climate studies to merge observations with numerical models, can improve state estimates and consequent forecasts. We interface the deterministic ensemble Kalman filter (DEnKF) to the Lagrangian neXt generation Sea Ice Model, neXtSIM. The ensemble is generated by perturbing the atmospheric and oceanic forcing throughout the simulations and randomly initialized ice cohesion. Our ensemble–DA system assimilates sea ice concentration (SIC) from the Ocean and Sea Ice Satellite Application Facility (OSI-SAF) and sea ice thickness (SIT) from the merged CryoSat-2 and SMOS datasets (CS2SMOS). Because neXtSIM is computationally solved on a time-dependent evolving mesh, it is a challenging application for ensemble–DA. As a solution, we perform the DEnKF analysis on a fixed and regular reference mesh, on which model variables are interpolated before the DA and then back to each member's mesh after the DA. We evaluate the impact of assimilating different types of sea ice observations on the model's forecast skills of the Arctic sea ice by comparing satellite observations and a free-run ensemble in an Arctic winter period, 2019–2020. Significant improvements in modeled SIT indicate the importance of assimilating weekly CS2SMOS SIT, while the improvements of SIC and ice extent are moderate but benefit from daily ingestion of the OSI-SAF SIC. For most of the winter, the correlation between SIT and SIC is weaker, which results in little cross-inference between the two variables in the assimilation step. Overall, the ensemble–DA system based on the stand-alone sea ice model demonstrates the feasibility of winter Arctic sea ice prediction with good computational efficiency. These results open the path toward operational implementation and the extension to multi-year assimilation.

10.5194/tc-17-1735-2023

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Deep‐Water Variability and Interbasin Interactions in the Eastern Mediterranean Sea

Geophysical monograph (2014)

Emi̇n Özsoy Sarantis Sofianos Isaac Gertman Anneta Mantziafou Ali Aydoğdu

The eastern basin of the Mediterranean is a remote area of the world ocean, the isolation of its various basins increased with distance from the Atlantic Ocean and with further constraints posed by the various straits. This chapter analyzes the deep-water characteristics independent of the changes in the upper-water column. It provides the data sources and methodology, followed by an analysis of the changes in basinwide properties linked with the interactions between individual basins of the eastern Mediterranean, and the intrabasin variability. The chapter compares the general deep-water characteristics of the main subbasins of the eastern Mediterranean, namely, the Aegean and Adriatic shelf seas and the deep Levantine and Ionian basins, through a discussion of the water properties at the most relevant depth for each basin.

Mediterranean Basin

Oceanic basin

10.1002/9781118847572.ch7

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Evolution of the Black Sea Physical Analysis and Forecasting System within CMEMS

Stefania Angela Ciliberti Eric Jansen Diana Azevedo Murat Gündüz Mehmet Ilıcak

The Black Sea physical analysis and Forecasting System (BSFS) is part of the Black Sea Monitoring and Forecasting Centre (BS-MFC) for the Copernicus Marine Service (CMEMS). It provides analysis every day analysis and 10 days forecast fields for the blue ocean variables (including temperature, salinity, sea surface height, mixed layer depth and currents) in the Black Sea region since. In this work, we present the new version of the operational system that will be part of the next CMEMS &#160;release. The hydrodynamical core model is based on NEMO v4.0, solved on 1/40&#186; horizontal resolution spatial grid (including the overall Black Sea, the Bosporus Strait and part of the Marmara Sea) and 121 vertical levels with z-star. The core model uses ECMWF analysis and forecast atmospheric forcing and GPCP monthly climatological precipitation for computing heat, water and momentum fluxes. A total number of 72 rivers is accounted, as monthly climatology provided by SESAME project. The model implements a new representation of the Danube River with interannual river discharge datasets provided by the National Institute of Hydrology and Water Management. One of the main innovations of this system is the opening of the Bosporus Strait by using a box-approach in a portion of the Marmara Sea: it is achieved thanks to high resolution temperature, salinity, sea surface height, zonal and meridional velocity solutions provided by a novel implementation of the Marmara Sea model including straits based on Shyfem: it represents the optimal interface between the Mediterranean and the Black Sea. The hydrodynamical model is online coupled to an upgraded version of the OceanVar, the CMCC data assimilation scheme, able to assimilate SLA L3 satellite data, T/S in-situ profiles and SST from CMEMS TACs. The contribution focuses on model setup description, processing system and validation. To evaluate BSFS pre-operational run and monitor the operational production, we provide metrics as proposed within GODAE/Oceanpredict and MERSEA/MyOcean (which includes CLASS 1, 2 and 4 metrics).

Black Sea

Forcing (mathematics)

Temperature salinity diagrams

10.5194/egusphere-egu21-6598

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An interlinked coastal observatory network for Europe

Journal of Operational Oceanography (2016)

Stefania Sparnocchia R.R. Nair George Petihakis Ali Aydoğdu Srdjan Dobričić

Existing coastal observatories in European waters are complex systems consisting of different observational components, providing crucial operational data for assessment, model validation and assimilation purposes. However, the geographical, structural, functional and operational heterogeneities that characterise them pose an enormous challenge to their efficient exploitation as information providers on a broader, cross-border, regional scale. To address this problem, the European Union (EU) Seventh Framework Programme (FP7) Towards a Joint European Research Infrastructure Network for Coastal Observatories (JERICO) project is creating a shared, pan-European framework for the networking of such observatories, promoting the identification and dissemination of best practices for their design, implementation and maintenance, as well as common data distribution and transnational access protocols to enhance their performance and sustainability. In doing so, the project is also laying down the foundation for the coastal element of the nascent European Ocean Observing System.

Identification

10.1080/1755876x.2015.1114808

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Citations (14)

Circulation of the Turkish Straits System between 2008–2013 under complete atmospheric forcings

Ali Aydoğdu Nadia Pinardi Emi̇n Özsoy Gökhan Danabasoglu Özgür Gürses

Abstract. A simulation of the Turkish Straits System (TSS) using a high-resolution, three-dimensional, unstructured mesh ocean circulation model with realistic atmospheric forcing for the 2008–2013 period is presented. The depth of the interface layer between the upper and lower layers remains stationary after six years of integration, indicating that despite the limitations of the modelling system, the simulation maintains its realism. The solutions capture important responses to high frequency atmospheric events such as the reversal of the upper layer flow in the Bosphorus due to southerly severe storms, i.e., blocking events, to the extent that such storms are present in the forcing dataset. The annual average circulations show two distinct patterns in the Marmara Sea. When the wind stress maximum is localised in the central basin, the Bosphorus jet flows to the south and turns west after reaching the Bozburun Peninsula. In contrast, when the wind stress maximum increases and expands in the north-south direction, the jet deviates to the west before reaching the southern coast and forms a cyclonic gyre in the central basin. In certain years the mean kinetic energy in the northern Marmara Sea is found to be comparable to that of the Bosphorus inflow.

Forcing (mathematics)

Wind Stress

Atmospheric Circulation

Peninsula

Inflow

10.5194/os-2018-7

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Citations (3)