Forecasting the Aegean Sea hydrodynamics within the POSEIDON-II operational system

Κορρές, Γεράσιμος; Nitti, K; Perivoliotis, L.; Tsiaras, Kostas; Παπαδόπουλος, Αναστάσιος; Triantafyllou, G.; Hoteit, Ibrahim; Abdullah, King

doi:10.1080/1755876x.2010.11020112

Cited by 26 publications

(26 citation statements)

References 31 publications

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“…The heat and freshwater fluxes, at the air-sea interface, are calculated using hourly fields of wind velocity (10 m), relative humidity (2 m), air temperature (2 m), precipitation, net incoming short wave radiation and incoming long wave radiation, using properly tuned bulk formulae set (Korres and Lascaratos, 2003). The circulation model implemented in this study has been validated through various applications with finer (e.g., Kourafalou et al, 2006;Korres et al, 2010) or coarser horizontal resolution (Korres et al, 2007;Tsiaras et al, 2014). The same model is currently operational with a slightly higher resolution (1/30 • ) as part of the POSEIDON forecasting system (www.poseidon.hcmr.…”

Section: Circulation Modelmentioning

confidence: 99%

“…odu.edu/POMWEB/) with numerous applications both for ocean and regional modeling studies. POM has been implemented in the Mediterranean Sea at basin/sub-basin scale (Zavatarelli and Mellor, 1995;Horton et al, 1997;Korres and Lascaratos, 2003, among others) and also on regional studies, including the Aegean Sea (Korres et al, 2010;Androulidakis et al, 2012;among others). It is a primitive equation, sigma coordinate and free surface elevation model that employes a 2.5 turbulence closure scheme (Mellor and Yamada, 1982) for vertical mixing.…”

Section: Circulation Modelmentioning

confidence: 99%

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Modeling the Fate and Distribution of Floating Litter Particles in the Aegean Sea (E. Mediterranean)

et al. 2017

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A circulation model is coupled to a Lagrangian particle-tracking model to simulate the transport floating litter particles in the Aegean Sea, Greece (Eastern Mediterranean). Considering different source regions and release dates, simulations were carried out to explore the fate and distribution of floating litter over 1990-2009, taking into account the seasonal and interannual variability of surface circulation. Model results depicted recurrently high concentrations of floating litter particles in the North Aegean plateau, the Saronikos Gulf, and along Evia and Crete islands. Modeled transport pathways of floating litter demonstrated that source regions are interconnected, with Saronikos Gulf being a main receptor of litter from other sources. Notably higher percent of litter exit (∼35%) than enter the model domain (∼7%) signified that Aegean Sea seems to act as a source rather than receptor of floating litter pollution in the Eastern Mediterranean Sea. Beached litter was found around 10%, mostly located in the western part of the Aegean Sea. This is the first modeling study to explore the transport of floating marine litter in Greek waters.

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Section: Circulation Modelmentioning

confidence: 99%

Section: Circulation Modelmentioning

confidence: 99%

Modeling the Fate and Distribution of Floating Litter Particles in the Aegean Sea (E. Mediterranean)

et al. 2017

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“…o ) regional atmospheric model (Papadopoulos and Katsafados, 2009) issuing forecasts for 5 days ahead. The assimilation system for the Mediterranean Sea hydrodynamic model is very similar to the one presented in the work of Korres et al (2010). It is based on the singular evolutive extended Kalman (SEEK) filter with covariance localization and partial evolution of the correction directions.…”

Section: Appendix A: Data Set Descriptionmentioning

confidence: 99%

“…The error covariance matrix is approximated with 60 EOF modes (correction directions), where the first 18 (the most dominant ones) are evolved with the model dynamics while the rest are kept invariant in time. The localization technique adopted for the Mediterranean Sea forecasting system is explained in Korres et al (2010). The method localizes the covariance matrix by neglecting observations beyond a cut-off radius which is selected upon sensitivity studies to be equal to 200 km.…”

Section: Appendix A: Data Set Descriptionmentioning

confidence: 99%

Development of super-ensemble techniques for ocean analyses: the Mediterranean Sea case

Pistoia

Pinardi

Oddo

et al. 2016

Nat. Hazards Earth Syst. Sci.

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Abstract. A super-ensemble methodology is proposed to improve the quality of short-term ocean analyses for sea surface temperature (SST) in the Mediterranean Sea. The methodology consists of a multiple linear regression technique applied to a multi-physics multi-model super-ensemble (MMSE) data set. This is a collection of different operational forecasting analyses together with ad hoc simulations, created by modifying selected numerical model parameterizations. A new linear regression algorithm based on empirical orthogonal function filtering techniques is shown to be efficient in preventing overfitting problems, although the best performance is achieved when a simple spatial filter is applied after the linear regression. Our results show that the MMSE methodology improves the ocean analysis SST estimates with respect to the best ensemble member (BEM) and that the performance is dependent on the selection of an unbiased operator and the length of training. The quality of the MMSE data set has the largest impact on the MMSE analysis root mean square error (RMSE) evaluated with respect to observed satellite SST. The MMSE analysis estimates are also affected by training period length, with the longest period leading to the smoothest estimates. Finally, lower RMSE analysis estimates result from the following: a 15-day training period, an overconfident MMSE data set (a subset with the higher-quality ensemble members) and the least-squares algorithm being filtered a posteriori.

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“…The assimilation scheme is based on the Singular Evolutive Extended Kalman (SEEK) filter which is an error subspace extended Kalman filter that operates with low-rank error covariance matrices as a way to reduce the prohibitive computational burden of the extended Kalman filter (Pham et al, 1998). The filter is additionally implemented with covariance localization and partial evolution of the correction directions (Korres et al, 2010).…”

Section: The Hydrodynamic Modelmentioning

confidence: 99%

The Aegean sea marine security decision support system

et al. 2011

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As part of the integrated ECOOP (European Coastal Sea Operational observing and Forecasting System) project, HCMR upgraded the already existing standalone Oil Spill Forecasting System for the Aegean Sea, initially developed for the Greek Operational Oceanography System (POSEIDON), into an active element of the European Decision Support System (EuroDeSS). The system is accessible through a user friendly web interface where the case scenarios can be fed into the oil spill drift model component, while the synthetic output contains detailed information about the distribution of oil spill particles and the oil spill budget and it is provided both in text based ECOOP common output format and as a series of sequential graphics. The main development steps that were necessary for this transition were the modification of the forcing input data module in order to allow the import of other system products which are usually provided in standard formats such as NetCDF and the transformation of the model's calculation routines to allow use of current, density and diffusivities data in <i>z</i> instead of sigma coordinates. During the implementation of the Aegean DeSS, the system was used in operational mode in order to support the Greek marine authorities in handling a real accident that took place in North Aegean area. Furthermore, the introduction of common input and output files by all the partners of EuroDeSS extended the system's interoperability thus facilitating data exchanges and comparison experiments

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Forecasting the Aegean Sea hydrodynamics within the POSEIDON-II operational system

Cited by 26 publications

References 31 publications

Modeling the Fate and Distribution of Floating Litter Particles in the Aegean Sea (E. Mediterranean)

Modeling the Fate and Distribution of Floating Litter Particles in the Aegean Sea (E. Mediterranean)

Development of super-ensemble techniques for ocean analyses: the Mediterranean Sea case

The Aegean sea marine security decision support system

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