Effects of Deep Water Source Sink Terms in 3rd generation Wave Model SWAN using different wind data in Black Sea

2016-04-17
Coastal development in Black Sea has increased in recent years. Therefore, careful monitoring of the storms and verification of numerical tools with reliable data has become important. Previous studies by Kirezci and Ozyurt (2015) investigated extreme events in Black Sea using different wind datasets (NCEP's CFSR and ECMWF's operational datasets) and different numerical tools (SWAN and Wavewatch III). These studies showed that significant effect to results is caused by the deep water source-sink terms (wave growth by wind, deep water dissipation of wave energy (whitecapping) and deep water non-linear wave-wave interactions). According to Timmermans(2015), uncertainty about wind forcing and the process of nonlinear wave-wave interactions are found to be dominant in numerical wave modelling. Therefore, in this study deep water source and sink term solution approaches of 3rd generation numerical tool (SWAN model) are tested, validated and compared using the selected extreme storms in Black Sea. 45 different storms and storm like events observed in Black Sea between years 1994-1999 are selected to use in the models. The storm selection depends on the instrumental wave data (significant wave heights, mean wave period and mean wave direction) obtained in NATO-TU Waves project by the deep water buoy measurements at Hopa, Sinop, Gelendzhik, and wind data (mean and peak wind speeds, storm durations) of the regarding events. 2 different wave growth by wind with the corresponding deep water dissipation terms and 3 different wave -wave interaction terms of SWAN model are used in this study. Wave growth by wind consist of two parts, linear growth which is explained by Cavaleri and Malanotte-Rizzoli(1981),and dominant exponential growth. There are two methods in SWAN model for exponential growth of wave, first one by Snyder et al. (1981), rescaled in terms of friction velocity by Komen et. al (1984) which is derived using driving wind speed at 10m elevation with related drag coefficient (WAM Cycle 3).The second method follows the quassi linear wind-wave theory by Janssen(1989,1991) which also considers the atmospheric boundary layer effects and the roughness length of the sea surface (WAM Cycle 4).(SWAN Technical Documentation,2015) The dissipation caused by whitecapping depends on the steepness of the waves. There are two different steepness dependent coefficient configurations in SWAN model corresponding to the selected wind-wave interaction formulations which are mentioned above (Komen and Janssen approaches). Lastly ,there are 3 options for defining deep water non-linear wave-wave interaction, which are DIA(Discrete Interaction Approximation)by Hasselman (quadruplets), XNL(which is based on the original six-dimensional Boltzmann integral formulation of Hasselmann), and multiple DIA which considers up to 6 wave number configurations by Hashimoto et al. (2002).(SWAN Technical Documentation,2015) In this study, 540 test cases are modelled using all possible selections of deep water source and sinks approaches available in SWAN model. The computed results are compared with buoy measurements. The uncertainty due to different source sink selections are quantified using different statistical analysis. Preliminary results show that some of the term configurations predict the significant wave height (Hs) less than actual values measured at the buoy locations. One of the reasons of the underestimation of the wave parameters could be the lower wind speed estimated in closed basins and the other one is the uncertainties in the wind-sea interaction. All of the results, comparisons and discussions will highlight the best source sink approach to be used to model extreme wave events in Black Sea. References Kirezci C., Ozyurt G., (2015), "Comparison of Wave Models in Black Sea", UK YCSEC 2015, 21-23 March 2015, Manchester Özhan, E. and Abdalla, S.,(1999)"Wind and Wave Climotology of the Turkish Coast and the Black Sea:An Overview of the NATO TU-WAVES Project.",p.1-20. SWAN Team.,(2015)," SWAN Scientific and Technical Documentation,SWAN Cycle III version 41.01AB", Delft University of Technology Timmermans, B.,(2015), "Uncertainty In Numerical Wind-Wave Models", Doctoral dissertation of University of Southampton
EGU General Assembly 2016

Suggestions

Modeling trophic interrelationships in the Black Sea
Gücü, Ali Cemal (1997-06-19)
The Black Sea being one of the largest enclosed seas, has been subjected to severe ecological changes within the last few decades. The river induced nutrient enrichment and eutrophication caused significant changes in the species composition. Some of species have disappeared while some others were newly introduced and became dominant in the Black Sea ecosystem. Among those which dominated the pelagic ecosystem, gelatinous organisms suddenly attained a high level of biomass in 1989, which can hardly be suppo...
Impact of a new invasive ctenophore (Mnemiopsis leidyi) on the zooplankton community of the Southern Caspian sea
Roohi, Abolghasem; Yasin, Zulfigar; Kıdeyş, Ahmet Erkan; Hwai, Aileen Tan Shau; Khanari, Ali Ganjian; Eker-Develi, Elif (2008-12-01)
The invasive ctenophore Mnemiopsis leidyi (Agassiz), which was transported from the Black Sea into the Caspian Sea at the end of the 1990s, has negatively affected the ecosystem of the Caspian Sea. Zooplankton abundance, biomass and species composition were evaluated on the Iranian coast of the Caspian Sea during 2001-2006. A total of 18 merozooplankton (13 species composed of larvae of benthic animals) and holozooplankton (four Copepoda and one Cladocera) species were identified. The total number of zoopla...
Effects of Nutrient Management Scenarios on Marine Food Webs: A Pan-European Assessment in Support of the Marine Strategy Framework Directive
Piroddi, Chiara; et. al. (2021-03-01)
Eutrophication is one of the most important anthropogenic pressures impacting coastal seas. In Europe, several legislations and management measures have been implemented to halt nutrient overloading in marine ecosystems. This study evaluates the impact of freshwater nutrient control measures on higher trophic levels (HTL) in European marine ecosystems following descriptors and criteria as defined by the Marine Strategy Framework Directive (MSFD). We used a novel pan-European marine modeling ensemble of four...
Effect of temperature on clearance rate daily ration and digestiontime of Mnemiopsis leidyi from the southern Caspian Sea
M,, Rowshantabari; Finenko, Ga; Kıdeyş, Ahmet Erkan; Kiabi, B. (University of Guilan, 2012-06-01)
The effect of temperature on the main feeding parameters of Mnemiopsis leidyi from the southern Caspian Sea was studied in 2002. The clearance rates and daily rations were estimated from laboratory experiments in a wide range of temperatures from 12 to 27 ?C for M. leidyi of 12?17 mm in length. Clearance rate values changed from 52.5 to 107.3 ml ind-1 h-1. The coefficient Q10 in temperature 12 - 20 ?C was higher than that in 20 - 27 ?C (3.81 and 1.91, respectively). The specific daily ration changed from 1....
Factors Influencing the Invasion of the Alien Ctenophore Mnemiopsisleidyi Development in the Southern Caspian Sea
Roohi, Aboulghasem; Pourgholam, Reza; Khenari, Ali Ganjian; Kıdeyş, Ahmet Erkan; Sajjadi, Ameneh; Kalantari, Ramin Abdollahzade (2013-11-01)
Mnemiopsis leidyi population activities first were recorded during the coastal observations in 2001 in which its population considerably increased afterward and now sustained the southern Caspian Sea. Maximum summer-autumn M. leidyi abundance was recorded in euphotic layer in 2002 (851±85 ind.m-3) and maximum biomass was in 2001 with 48.1±14.4 g.m-3) while minimum were in aphotic layer. In years 2003 to 2011, M. leidyi abundance and biomass sharply declined to 1-843 ind.m-3 and 0.07-37.7 g.m-3, respectively...
Citation Formats
Ç. Kirezci and G. Özyurt Tarakcıoğlu, “Effects of Deep Water Source Sink Terms in 3rd generation Wave Model SWAN using different wind data in Black Sea,” presented at the EGU General Assembly 2016, 2016, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/71194.