Analysis of wave heights and wind speeds in the Adriatic Sea

Katalinić, Marko; Ćorak, M; Parunov, Joško

doi:10.1201/b17494-188

Cited by 12 publications

(15 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, we expect that this limitation does not strongly affect our results on connectivity. In fact, though strong winds (Ruiz‐Montoya et al., ) can affect movement of floating fruits (Grech et al., ), this effect is minor (McMahon et al., ), and expected to be modest in the Adriatic considering local wind speed (Katalinić, Ćorak, & Parunov, ) and limited tidal currents (Poulain, ). The biological component of the model (see Melià et al., for a more detailed description) accounts for the key traits affecting P. oceanica dispersal by sexual propagules: P. oceanica produces positively buoyant fruits, which are released between January and April (Balestri & Cinelli, ; Buia & Mazzella, ) and float in the upper layers of the water column for about 28 days before dehiscence and consequent release of the sinking seed (Serra et al., ).…”

Section: Methodsmentioning

confidence: 99%

Potential and realized connectivity of the seagrass Posidonia oceanica and their implication for conservation

Jahnke

Casagrandi

Melià

et al. 2017

Diversity and Distributions

View full text Add to dashboard Cite

Aim: Connectivity assessments are crucial to large-scale conservation planning, in particular for establishing and monitoring connected networks of marine protected areas (MPAs). Using biophysical modelling and genetic analyses, we assessed potential and realized connectivity among MPA populations of a benthic foundation species, the Mediterranean endemic seagrass Posidonia oceanica. Location: Adriatic and Ionian seas (central Mediterranean). Methods:We assessed potential and realized connectivity among eight P. oceanica meadows, mostly located in MPAs. Potential connectivity was assessed over a time horizon of 10 years via an individual-based biophysical model whose physical component relies on fine-scale spatio-temporal ocean circulation fields. Genetic assessments of realized connectivity were carried out by means of a set of 14 neutral microsatellite loci, as well as a larger dataset of 19 loci including outlier loci that did not conform to expectations under neutrality. Results: Our findings point out a relatively high potential connectivity through longrange dispersal of floating fruits. Genetic connectivity analyses show a complex scenario with an apparent lower realized connectivity. The P. oceanica meadow within Torre Guaceto MPA (TOG), a well-enforced MPA within our study area, showed one of the highest levels of genotypic richness, indicative of high levels of sexual reproduction and/or recruitment of foreign genotypes. Both biophysical modelling and population genetics indicate that TOG is important to ensure the viability of the species at the local scale, and does likely play a key role as a source of propagules for the whole Adriatic area. Main conclusions: Our results show that realized dispersal does not necessarily match with the potential for dispersal. Still, both genetic and physical connectivity analyses show good agreement in identifying hotspots of connectivity. Such information can guide management of networks of MPAs and advance conservation of marine biodiversity. K E Y W O R D S dispersal, genetic connectivity, Lagrangian, marine protected areas, propagules, seagrass

show abstract

Section: Methodsmentioning

confidence: 99%

Potential and realized connectivity of the seagrass Posidonia oceanica and their implication for conservation

Jahnke

Casagrandi

Melià

et al. 2017

Diversity and Distributions

View full text Add to dashboard Cite

show abstract

“…This is not the case with ocean waves that arrive from different physical sources, e.g., wind waves and swells. However, the Adriatic Sea, used for this case study, has a wave climate dominated by wind waves [18], as significant swell influence is disabled by its enclosed boundaries. Finally, an unfavorable characteristic of the ID approach for long return period estimations is that the theoretical distribution fitting is largely influenced by the bulk data recorded for lower significant wave heights.…”

Section: The Initial Distribution Approach-three Parameter Weibull DImentioning

confidence: 99%

Uncertainties of Estimating Extreme Significant Wave Height for Engineering Applications Depending on the Approach and Fitting Technique—Adriatic Sea Case Study

Katalinić

Parunov

2020

JMSE

View full text Add to dashboard Cite

Studies on the extrapolation of extreme significant wave height, based on long-term databases, are extensively covered in literature. An engineer, working in the field of naval architecture, marine engineering, or maritime operation planning, when tackling the problem of extreme wave prediction, would typically follow relevant codes and standards. Currently, authorities in the field of offshore operation within its guidelines propose several methods: the initial-distribution, extreme value, and peak-over threshold approaches. Furthermore, for each proposed method, different mathematical fitting techniques are applicable to optimize the candidate distribution parameters: the least-square method, the method of moments, and the maximum likelihood method. A comprehensive analysis was done to determine the difference in the results depending on the choice of method and fitting technique. All combinations were tested on a long-term database for a location in the Adriatic Sea. The variability of the results and trends of extreme wave height estimates for long return periods are presented, and the limitations of certain methods and techniques are noted.

show abstract

“…Development of bura wind waves is limited by relatively narrow fetch across the Adriatic, so the maximum wave heights are expected in range from 6.2 m to 7.2 m. Opposed to waves generated by bura, waves generated by jugo are higher and longer and already formed enter through Otranto Strait, causing more developed sea state. In stormy conditions, wind speed of jugo can reach 30 ms −1 and maximum recorded wave height during this wind was 10.8 m [6].…”

Section: Introductionmentioning

confidence: 96%

Mitigation of the Effects of Unknown Sea Clutter Statistics by Using Radial Basis Function Network

Vondra¹,

Bonefačić²

2020

RADIOENGINEERING

View full text Add to dashboard Cite

In this paper, we investigate feasibility of employing Radial Basis Function (RBF) network into non-coherent detection process, for detection of targets embedded in sea clutter of unknown statistics. We particularly have in mind Croatian part of Adriatic Sea, the local sea whose clutter statistic properties are not available in open literature. Performance of the detection process employing proposed RBF network is tested with simulated clutter samples based on real sea clutter data. These data were collected under sea state conditions that represent two thirds of the total wave heights in Adriatic and are chosen to represent unknown clutter statistics due to the fact that no single probability density function equally well fits amplitude distribution of the range bins under test. It is demonstrated that, compared to the traditional [zlog(z)] method, RBF network with just four components and lognormal basis function, yields operating characteristics that better match designed ones.

show abstract

Analysis of wave heights and wind speeds in the Adriatic Sea

Cited by 12 publications

References 1 publication

Potential and realized connectivity of the seagrass Posidonia oceanica and their implication for conservation

Potential and realized connectivity of the seagrass Posidonia oceanica and their implication for conservation

Uncertainties of Estimating Extreme Significant Wave Height for Engineering Applications Depending on the Approach and Fitting Technique—Adriatic Sea Case Study

Mitigation of the Effects of Unknown Sea Clutter Statistics by Using Radial Basis Function Network

Contact Info

Product

Resources

About