Poseidon: A marine environmental monitoring, forecasting and information system for the Greek seas

The scope of this work is twofold: i) to discuss and analyze some principles, issues and problems related to the development and advancement of Operational Oceanography in Greece and ii) to present a real-time monitoring and forecasting system for the Aegean Sea, which is currently under implementation. Operational Oceanography in Greece has become a necessity today, since it can provide aid to find solutions on problems related to societal, economic, environmental and scientific issues. Most of the Greek coastal regions are under pressure, susceptible to damages due to the increasing tendency of the population to move from the inland to the coast, marine environmental pollution, competitive development of the coastal market sector, etc. Moreover, the complex geomorphology of the coastal areas and the interdependence between natural processes and human activities causes significant alterations in this delicate environment. A rational treatment of these problems can be based on integrated coastal zone management (ICZM). An absolutely necessary means for establishing ICZM is the operation of marine moni- toring systems. Such a system ("POSEIDON system") is under implementation by the National Centre for Marine Research. POSEIDON is a comprehensive marine monitoring and forecasting system, that aims to improve environmental surveillance and facilitate sea transport, rescue and safety of life at sea, fishing and aquaculture, protection of the marine ecosystem, etc. POSEIDON is expected to enhance considerably the capabilities to manage, protect and develop the marine resources of the Greek Seas and to promote Greek Operational Oceanography

The Errors-in-Variables approach for the validation of the WAM wave model in the Aegean Sea

In previous studies, wave fi elds from the 3rd-generation wave model WAM-Cycle 4 have been validated by using in situ buoy measurements in the Aegean Sea within the framework of the POSEIDON project; however, limitations of the data sets, concerning mainly the short distance of the buoys from the shore and the short length of the data, render those validation studies incomplete. In this work, signifi cant wave height forecasts obtained from WAM-Cycle 4 wave model are validated by means of TOPEX/Poseidon (T/P) data in specifi c offshore locations in the central part of the North Aegean Sea. The linear structural relationship between the two data sets has been modelled by implementing the Error- In-Variables approach, assuming that both T/P data and WAM results are subjected to errors. The underestimation of signifi cant wave height from WAM, which has been concluded from the comparison with buoys at near-shore points, is also observed from the WAM-T/P comparison at offshore locations, thus being considered of general validity for the Aegean Sea. In addition, a correction relation for the WAM model results, based on the linear structural relationship, is proposed and applied

The effect of the generalized extreme value distribution parameter estimation methods in extreme wind speed prediction

The modeling and prediction of extreme values of geophysical variables, such as wind, ocean surface waves, sea level, temperature and river flow, has always been a field of main concern for engineers and scientists. The analysis of extreme wind speed particularly plays an important role in natural disasters’ preparedness, prevention, mitigation and management and in various ocean, environmental and civil engineering applications, such as the design of offshore platforms and coastal marine structures, coastal management, wind climate analysis and structural safety. The block maxima (BM) approach is fundamental for extreme value analysis. BM method is closely related to the generalized extreme value (GEV) distribution, which unifies the three asymptotic extreme value distributions into a single one. The most common methods used for the estimation of the GEV parameters are maximum likelihood (ML) and probability weighted moments methods. In this work, several very common as well some less known estimation methods are firstly assessed through a simulation analysis. The results of the analysis showed that the maximum product of spacings (MPS), the elemental percentile (EP), the ordinary entropy method and, in a lesser degree, the ML methods seem to be, in general, superior to the other examined methods with respect to bias, mean squared error and variance of the estimated parameters. The effects of the estimation methods have been also assessed with respect to the n-year design values of real wind speed measurements. The obtained results suggest that the MPS and EP methods, which are rather unknown to the engineering community, describe adequately well the extreme quantiles of the wind speed data samples. © 2015, Springer Science+Business Media Dordrecht

Effects of parameter estimation method and sample size in metocean design conditions

The accurate estimation of extreme values for metocean parameters (wind speed, wave height, etc.) plays a crucial role in marine renewable energy industry and in coastal and offshore engineering applications. The most fundamental approach for extreme value analysis is the annual maxima approach that is directly related to the Generalized Extreme Value (GEV) distribution. Since the performance of the GEV parameter estimation methods is dependent on both the method and the available sample size, the exploration of these issues is analytically performed. Firstly, a simulation study is implemented based on the Maximum Likelihood (ML), the L–moments (LMOM), the Elemental Percentile and the Maximum Product of Spacings methods for different sample sizes. It is concluded that the ML should not be taken for granted since LMOM method performs better in many respects. Afterwards, both methods are applied for the estimation of the GEV parameters of wind speed annual maxima series. LMOM method provided the best fits for the overwhelming majority of cases considered. Finally, the 50- and 100-year wind speed return levels are estimated. With respect to the relative confidence intervals of the return level estimates, no solid conclusions can be drawn since there is lack of a systematic behaviour. © 2018 Elsevier Lt

Assessment of surface circulation using remote-sensed data, in-situ measurements and directional statistics

15-26A method accounting for the directional characteristics of in-situ wind and current measurements is proposed and applied in two characteristic locations of the Aegean Sea. With the combined use of directional statistics, satellite derived SST maps and in-situ measurements, an efficient quantitative description of the directional current behavior and its relation with the corresponding wind fields, thermohaline trends, seasonality and sources of the main meso- and large-scaled surface currents of the Aegean Sea, is elaborated. The evolution, persistence, duration and signal of the surface circulation patterns has been appeared to be quite different during each season or calendar year, shaping in this way a completely different layout of the overall sea surface circulation. This is a novel approach interrelating directional statistics with in-situ measurements and SST maps, for the Aegean Sea