Review of Three-Dimensional Ecological Modelling Related to the North Sea Shelf System

Radach, Günther; Moll, A.

doi:10.1201/9781420006391.ch1

Cited by 56 publications

(46 citation statements)

References 72 publications

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“…The model results from 2006 indicate good or very good (Radach and Moll 2006) cost function values for most variables in the different areas. The best results are seen for the summer CHL, which are found to be very good in almost all models and areas, while the lower layer O 2 concentrations have the highest number of poor results (Table 3).…”

Section: Comparison To In Situ Datamentioning

confidence: 99%

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A North Sea and Baltic Sea Model Ensemble Eutrophication Assessment

Almroth

Skogen

2010

AMBIO

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A method to combine observations and an ensemble of ecological models is suggested to produce a eutrophication assessment. Using threshold values and methodology from the Oslo and Paris Commissions (OSPAR) and the Helsinki Commission (HELCOM), four models are combined to assess eutrophication for the Baltic and North Seas for the year 2006. The assessment indicates that the entire southeastern part of the North Sea, the Kattegat, the Danish Straits, the Gulf of Finland, and the Gulf of Riga as well as parts of the Arkona Basin, the Bornholm Basin, and the Baltic proper may be classified as problem areas. The Bothnian Bay and parts of the Baltic proper, the Bornholm Basin, and the Arkona Basin are classified as potential problem areas. This method is a useful tool for the classification of eutrophication; however, the results depend on the threshold values, and further work is needed within both OSPAR and HELCOM to harmonize these values.

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Section: Comparison To In Situ Datamentioning

confidence: 99%

“…The cost function is computed as: In Radach and Moll (2006), the following criteria for performance are used: C \ 1 = very good, 1 \ C \ 2 = good, 2 \ C \ 3 = reasonable, and C [ 3 = poor. One may note that the value of C i becomes large if the modeled mean value differs much from the mean value of the in situ data.…”

Section: The In Situ Datamentioning

confidence: 99%

A North Sea and Baltic Sea Model Ensemble Eutrophication Assessment

Almroth

Skogen

2010

AMBIO

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“…The 'goodness-of-fit' between these model results and associated field measurements was calculated using the 'cost function' (OSPAR, 1998;Radach & Moll, 2006). The cost function is a mathematical function that gives a non-dimensional number, which is indicative of the 'goodness of fit' between two sets of data, in this case, model results and observations.…”

Section: Applicability Of the 'Gem' Modelmentioning

confidence: 99%

“…The validation results were classified according to the following rating criteria (Radach & Moll, 2006) …”

Section: Applicability Of the 'Gem' Modelmentioning

confidence: 99%

“…Substantial river discharges and relatively shallow nearshore waters often result in large fluctuations and strong spatial gradients in salinity, suspended matter concentrations, nutrient concentrations and algal biomass in such water systems. These characteristics, along with complex benthic-pelagic interactions and light attentuation issues, have proven difficult to replicate in models (Radach & Moll, 2006), in particular with regard to scales of temporal and spatial resolution required to simulate the possible impacts of future conditions, including management scenarios.…”

Section: Introductionmentioning

confidence: 99%

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GEM: a generic ecological model for estuaries and coastal waters

Blauw

Los

Bokhorst³

et al. 2008

Hydrobiologia

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The set-up, application and validation of a generic ecological model (GEM) for estuaries and coastal waters is presented. This model is a comprehensive ecological model of the bottom of the foodweb, consisting of a set of modules, representing specific water quality processes and primary production that can be combined with any transport model to create a dedicated model for a specific ecosystem. GEM links different physical, chemical and ecological model components into one generic and flexible modelling tool that allows for variable sized, curvilinear grids to accomodate both the requirements for local accuracy while maintaining a relatively short model run-time. The GEM model describes the behaviour of nutrients, organic matter and primary producers in estuaries and coastal waters, incorporating dynamic process modules for dissolved oxygen, nutrients and phytoplankton. GEM integrates the best aspects of existing Dutch estuarine models that were mostly dedicated to only one type of ecosystem, geographic area or subset of processes. Particular strengths of GEM include its generic applicability and the integration and interaction of biological, chemical and physical processes into one predictive tool. The model offers flexibility in choosing which processes to include, and the ability to integrate results from different processes modelled simultaneously with different temporal resolutions. The generic applicability of the model is illustrated using a number of representative examples from case studies in which the GEM model was successfully applied. Validation of these examples was carried out using the 'cost function' to compare model results with field observations. The validation results demonstrated consistent accuracy of the GEM model for various key parameters in both spatial dimensions (horizontally and vertically) as well as temporal dimensions (seasonally and across years) for a variety of water systems without the need for major reparameterisation.

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Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: Empirical and model results

Duarte

Meyer

Olsen

et al. 2017

J. Geophys. Res. Biogeosci.

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Large changes in the sea ice regime of the Arctic Ocean have occurred over the last decades justifying the development of models to forecast sea ice physics and biogeochemistry. The main goal of this study is to evaluate the performance of the Los Alamos Sea Ice Model (CICE) to simulate physical and biogeochemical properties at time scales of a few weeks and to use the model to analyze ice algal bloom dynamics in different types of ice. Ocean and atmospheric forcing data and observations of the evolution of the sea ice properties collected from 18 April to 4 June 2015, during the Norwegian young sea ICE expedition, were used to test the CICE model. Our results show the following: (i) model performance is reasonable for sea ice thickness and bulk salinity; good for vertically resolved temperature, vertically averaged Chl a concentrations, and standing stocks; and poor for vertically resolved Chl a concentrations. (ii) Improving current knowledge about nutrient exchanges, ice algal recruitment, and motion is critical to improve sea ice biogeochemical modeling. (iii) Ice algae may bloom despite some degree of basal melting. (iv) Ice algal motility driven by gradients in limiting factors is a plausible mechanism to explain their vertical distribution. (v) Different ice algal bloom and net primary production (NPP) patterns were identified in the ice types studied, suggesting that ice algal maximal growth rates will increase, while sea ice vertically integrated NPP and biomass will decrease as a result of the predictable increase in the area covered by refrozen leads in the Arctic Ocean.

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Review of Three-Dimensional Ecological Modelling Related to the North Sea Shelf System

Cited by 56 publications

References 72 publications

A North Sea and Baltic Sea Model Ensemble Eutrophication Assessment

A North Sea and Baltic Sea Model Ensemble Eutrophication Assessment

GEM: a generic ecological model for estuaries and coastal waters

Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: Empirical and model results

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