Wave modelling in archipelagos

Tuomi, Laura; Pettersson, Heidi; Fortelius, Carl; Tikka, Kimmo; Björkqvist, Jan-Victor; Kahma, Kimmo K.

doi:10.1016/j.coastaleng.2013.10.011

Cited by 47 publications

(47 citation statements)

References 14 publications

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“…The particularly high value of the mean square error HH of the significant wave height estimated for the buoys located in the Greek archipelago is clearly related to the particularly complex orography and bathymetry (resolution does not allow for an accurate representation of bathymetric features, e.g. Tuomi et al, 2013). Finally, the Alboran and Balearic seas show positive values of bias together with low values in the HH index of significant wave height.…”

Section: -Year (1979-2010) Hindcastmentioning

confidence: 86%

Performance evaluation of Wavewatch III in the Mediterranean Sea

et al. 2015

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Section: -Year (1979-2010) Hindcastmentioning

confidence: 86%

Performance evaluation of Wavewatch III in the Mediterranean Sea

et al. 2015

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“…It has been extensively used for modelling the Baltic Sea wave fields (Soomere 2003;Soomere 2005;Soomere et al 2008;Tuomi et al 2011;Tuomi et al 2012b;Tuomi et al 2014). The action density spectrum N is considered instead of the energy density spectrum E because in the presence of ambient currents, action density is conserved, but energy density is not.…”

Section: Model Description and Setupmentioning

confidence: 98%

Surface wave effects on water temperature in the Baltic Sea: simulations with the coupled NEMO-WAM model

et al. 2016

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Coupled circulation (NEMO) and wave model (WAM) system was used to study the effects of surface ocean waves on water temperature distribution and heat exchange at regional scale (the Baltic Sea). Four scenarios-including Stokes-Coriolis force, sea-state dependent energy flux (additional turbulent kinetic energy due to breaking waves), seastate dependent momentum flux and the combination these forcings-were simulated to test the impact of different terms on simulated temperature distribution. The scenario simulations were compared to a control simulation, which included a constant wave-breaking coefficient, but otherwise was without any wave effects. The results indicate a pronounced effect of waves on surface temperature, on the distribution of vertical temperature and on upwelling's. Overall, when all three wave effects were accounted for, did the estimates of temperature improve compared to control simulation. During the summer, the wave-induced water temperature changes were up to 1°C. In northern parts of the Baltic Sea, a warming of the surface layer occurs in the wave included simulations in summer months. This in turn reduces the cold bias between simulated and measured data, e.g. the control simulation was too cold compared to measurements. The warming is related to seastate dependent energy flux. This implies that a spatiotemporally varying wave-breaking coefficient is necessary, because it depends on actual sea state. Wave-induced cooling is mostly observed in near-coastal areas and is the result of intensified upwelling in the scenario, when Stokes-Coriolis forcing is accounted for. Accounting for sea-state dependent momentum flux results in modified heat exchange at the water-air boundary which consequently leads to warming of surface water compared to control simulation.

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“…The major limitation is the wind quality. Even though reconstructed wind fields are adequate for the Baltic Sea, replication of the wave climate is still a major challenge for this basin (Tuomi et al, 2011(Tuomi et al, , 2014Hünicke et al, 2015). An intrinsic reason is the variability of ice cover extension from 12.5 to 100 % of the sea surface (Leppäranta and Myrberg, 2009).…”

Section: Introductionmentioning

confidence: 99%

Satellite altimetry reveals spatial patterns of variations in the Baltic Sea wave climate

Kudryavtseva

Soomere

2017

Earth Syst. Dynam.

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Abstract. The main properties of the climate of waves in the seasonally ice-covered Baltic Sea and its decadal changes since 1990 are estimated from satellite altimetry data. The data set of significant wave heights (SWHs) from all existing nine satellites, cleaned and cross-validated against in situ measurements, shows overall a very consistent picture. A comparison with visual observations shows a good correspondence with correlation coefficients of 0.6-0.8. The annual mean SWH reveals a tentative increase of 0.005 m yr −1 , but higher quantiles behave in a cyclic manner with a timescale of 10-15 years. Changes in the basin-wide average SWH have a strong meridional pattern: an increase in the central and western parts of the sea and a decrease in the east. This pattern is likely caused by a rotation of wind directions rather than by an increase in the wind speed.

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Wave modelling in archipelagos

Cited by 47 publications

References 14 publications

Performance evaluation of Wavewatch III in the Mediterranean Sea

Performance evaluation of Wavewatch III in the Mediterranean Sea

Surface wave effects on water temperature in the Baltic Sea: simulations with the coupled NEMO-WAM model

Satellite altimetry reveals spatial patterns of variations in the Baltic Sea wave climate

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