Deep‐water dynamics and boundary mixing in a nontidal stratified basin: A modeling study of the Baltic Sea

Holtermann, Peter; Burchard, Hans; Gräwe, Ulf; Klingbeil, Knut; Umlauf, Lars

doi:10.1002/2013jc009483

Cited by 40 publications

(45 citation statements)

References 56 publications

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“…The model has a very good track record for the North SeaÁBaltic Sea transition zone, see for example, Holtermann et al (2014), which is a key area for FCOO. As the numerical experiments themselves are repeatable, it is necessary to, in some sense, perturb ('push' or 'nudge') in order to trigger a branching or bifurcation into different stochastic outcomes.…”

Section: Simulation Perturbation: Branchingmentioning

confidence: 99%

Internal variability of a 3-D ocean model

Büchmann

Söderkvist

2016

Tellus A: Dynamic Meteorology and Oceanography

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A B S T R A C TThe Defence Centre for Operational Oceanography runs operational forecasts for the Danish waters. The core setup is a 60-layer baroclinic circulation model based on the General Estuarine Transport Model code. At intervals, the model setup is tuned to improve 'model skill' and overall performance. It has been an area of concern that the uncertainty inherent to the stochastical/chaotic nature of the model is unknown. Thus, it is difficult to state with certainty that a particular setup is improved, even if the computed model skill increases. This issue also extends to the cases, where the model is tuned during an iterative process, where model results are fed back to improve model parameters, such as bathymetry. An ensemble of identical model setups with slightly perturbed initial conditions is examined. It is found that the initial perturbation causes the models to deviate from each other exponentially fast, causing differences of several PSUs and several kelvin within a few days of simulation. The ensemble is run for a full year, and the long-term variability of salinity and temperature is found for different regions within the modelled area. Further, the developing time scale is estimated for each region, and great regional differences are found Á in both variability and time scale. It is observed that periods with very high ensemble variability are typically short-term and spatially limited events. A particular event is examined in detail to shed light on how the ensemble 'behaves' in periods with large internal model variability. It is found that the ensemble does not seem to follow any particular stochastic distribution: both the ensemble variability (standard deviation or range) as well as the ensemble distribution within that range seem to vary with time and place. Further, it is observed that a large spatial variability due to mesoscale features does not necessarily correlate to large ensemble variability. These findings bear impact on the way data assimilation should be addressed Á especially in relation to operational forecasts.

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Section: Simulation Perturbation: Branchingmentioning

confidence: 99%

Internal variability of a 3-D ocean model

Büchmann

Söderkvist

2016

Tellus A: Dynamic Meteorology and Oceanography

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“…A recent modeling study by Holtermann et al . [] identified and reproduced the main energy sources for deep water boundary mixing in the Baltic Sea (i.e., near‐inertial waves, topographic waves, and a rim current). A detailed investigation of such bottom dynamics has never been performed in the southern Adriatic, even though several studies have analyzed its thermohaline properties and dense water production rates, using either experimental [ Manca et al ., ; Gačić et al ., ; Cardin et al ., ; Bensi et al ., ] or numerical approaches [ Mantziafou and Lascaratos , ; Rubino et al ., ; Querin et al ., ].…”

Section: Introductionmentioning

confidence: 99%

Saw‐tooth modulation of the deep‐water thermohaline properties in the southern Adriatic Sea

et al. 2016

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In this study, we investigate the dynamics of the bottom layer of the southern Adriatic Sea (eastern Mediterranean basin) by merging experimental measurements and numerical simulations. We hypothesize that the recently observed continuous density decrease over time, which was basically related to a temperature increase, and the following sudden density rise, which was caused by the intrusion of very dense water masses (cold but relatively fresh), constitute one cycle of a general saw-tooth pattern: the alternation of long-lasting and almost linear density decreases (mixing phases) and sudden density increases (dense water intrusion phases). The model results, which provide a basin-scale view of the process, corroborate this theory because they satisfactorily reproduced the observed oceanographic features. We describe the almost linear density decrease in terms of local mixing fostered by the advection of flow instabilities that originate from the large-scale quasi-permanent cyclonic circulation. Conversely, diffusive processes play a minor role in determining the bottom layer thermohaline variability. The interpretation of the experimental findings, supported by the numerical simulations, suggests that similar dynamics might be observed in other basins characterized by similar bathymetric and hydrodynamic features

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“…Burchard et al (2004) applied General Estuarine Transport Model (GETM) for simulating dynamics of the estuarine turbidity maxima in the Elbe Estuary. The GETM was also successfully applied for studying the water dynamics in the Baltic Sea (Holtermann et al, 2014). Scully et al (2009) explored the mechanisms driving the estuarine circulation in the Hudson River Estuary utilizing the Regional Ocean Modeling System (ROMS).…”

Section: Investigations Of Estuarine Processesmentioning

confidence: 99%

Estuary, Estuarine Hydrodynamics

Kowalewska-Kalkowska¹,

Marks²

2015

Encyclopedia of Marine Geosciences

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Synonyms River mouth area DefinitionAccording to the definition given by Cameron and Pritchard (1963), an estuary is a semi-enclosed coastal body of water which has a free connection with the open sea and within which seawater is measurably diluted with freshwater derived from land drainage. This definition applies to the so-called classical (positive) estuaries of the Earth's temperate latitudes in which freshwater input is the main driver of the long-term circulation. Freshwater inflow establishes longitudinal density gradients resulting in long-term surface outflow and net inflow underneath. In some arid basins, called inverse (negative) estuaries, where evaporation exceeds the sum of precipitation and runoff, the loss of freshwater becomes a main force shaping long-term circulation and the development of longitudinal density gradients, in analogy to classical estuaries (Valle-Levinson, 2010).

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Deep‐water dynamics and boundary mixing in a nontidal stratified basin: A modeling study of the Baltic Sea

Cited by 40 publications

References 56 publications

Internal variability of a 3-D ocean model

Internal variability of a 3-D ocean model

Saw‐tooth modulation of the deep‐water thermohaline properties in the southern Adriatic Sea

Estuary, Estuarine Hydrodynamics

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