Validation of the NEMO-ERSEM operational ecosystem model for the North West European Continental Shelf

Edwards, K. P.; Barciela, Rosa; Butenschön, Momme

doi:10.5194/os-8-983-2012

Cited by 66 publications

(59 citation statements)

References 54 publications

(65 reference statements)

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“…The version of ERSEM used is an alternative development of the original code of Baretta et al (1995), led by Plymouth Marine Laboratory (PML), and is described in detail by Blackford et al (2004) and Edwards et al (2012). The pelagic component includes four phytoplankton and three zooplankton functional groups, and one bacterial group.…”

Section: Nemo-ersemmentioning

confidence: 99%

“…Since the focus of this study is on the phytoplankton community structure in August 2010 and 2011, most of the validation presented here is for these 2 months. For more general model validation the reader is referred to Edwards et al (2012) Calculations have been performed for log 10 (chlorophyll) rather than for chlorophyll in order to provide a more Gaussian distribution (Campbell, 1995).…”

Section: Model Validation -Domain Scalementioning

confidence: 99%

“…This uses terrain-following coordinates whilst ensuring a fixed surface resolution of 1 m. Remotely sensed and in situ observations of SST were assimilated using a 3D-Var implementation of the NEMOVAR data assimilation scheme (Waters et al, 2015;O'Dea et al, 2012). River inputs were taken from the E-HYPE model (Donnelly et al, 2015) for flow values, and from the same climatology as in Edwards et al (2012) for nutrients and SPM. Lateral boundary conditions for physical variables were taken from a reanalysis of the GloSea5 seasonal forecasting system (MacLachlan et al, 2014) at the Atlantic boundaries, and from the IOW-GETM model (Stips et al, 2004) at the Baltic boundary.…”

Section: Nemo-ersemmentioning

confidence: 99%

“…The final section, which this study uses, started in November 2003, with physics initial conditions taken from the corresponding date of a non-assimilative hindcast of the entire reanalysis period. Biogeochemical initial conditions were taken from a winter date of the run of NEMO-ERSEM described in Edwards et al (2012).…”

Section: Nemo-ersemmentioning

confidence: 99%

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Observing and modelling phytoplankton community structure in the North Sea

et al. 2017

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Abstract. Phytoplankton form the base of the marine food chain, and knowledge of phytoplankton community structure is fundamental when assessing marine biodiversity. Policy makers and other users require information on marine biodiversity and other aspects of the marine environment for the North Sea, a highly productive European shelf sea. This information must come from a combination of observations and models, but currently the coastal ocean is greatly under-sampled for phytoplankton data, and outputs of phytoplankton community structure from models are therefore not yet frequently validated. This study presents a novel set of in situ observations of phytoplankton community structure for the North Sea using accessory pigment analysis. The observations allow a good understanding of the patterns of surface phytoplankton biomass and community structure in the North Sea for the observed months of August 2010 and 2011. Two physical-biogeochemical ocean models, the biogeochemical components of which are different variants of the widely used European Regional Seas Ecosystem Model (ERSEM), were then validated against these and other observations. Both models were a good match for sea surface temperature observations, and a reasonable match for remotely sensed ocean colour observations. However, the two models displayed very different phytoplankton community structures, with one better matching the in situ observations than the other. Nonetheless, both models shared some similarities with the observations in terms of spatial features and interannual variability. An initial comparison of the formulations and parameterizations of the two models suggests that diversity between the parameter settings of model phytoplankton functional types, along with formulations which promote a greater sensitivity to changes in light and nutrients, is key to capturing the observed phytoplankton community structure. These findings will help inform future model development, which should be coupled with detailed validation studies, in order to help facilitate the wider application of marine biogeochemical modelling to user and policy needs.

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Section: Nemo-ersemmentioning

confidence: 99%

Section: Model Validation -Domain Scalementioning

confidence: 99%

Section: Nemo-ersemmentioning

confidence: 99%

Section: Nemo-ersemmentioning

confidence: 99%

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Observing and modelling phytoplankton community structure in the North Sea

et al. 2017

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“…Interpolations fill under-sampled regions with information from well-sampled regions -an ideal solution for cloud coverage in satellite data (for instance Edwards et al, 2012). However, interpolating sparse, uneven, widely distributed three-dimensional in situ measurements can amplify the effects of sampling bias (Robeson, 1994).…”

Section: Introductionmentioning

confidence: 99%

How should sparse marine in situ measurements be compared to a continuous model: an example

2013

Self Cite

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Abstract. This work demonstrates an example of the importance of an adequate method to sub-sample model results when comparing with in situ measurements. A test of model skill was performed by employing a point-to-point method to compare a multi-decadal hindcast against a sparse, unevenly distributed historic in situ dataset. The point-to-point method masked out all hindcast cells that did not have a corresponding in situ measurement in order to match each in situ measurement against its most similar cell from the model. The application of the point-to-point method showed that the model was successful at reproducing the inter-annual variability of the in situ datasets. Furthermore, this success was not immediately apparent when the measurements were aggregated to regional averages. Time series, data density and target diagrams were employed to illustrate the impact of switching from the regional average method to the point-topoint method. The comparison based on regional averages gave significantly different and sometimes contradicting results that could lead to erroneous conclusions on the model performance. Furthermore, the point-to-point technique is a more correct method to exploit sparse uneven in situ data while compensating for the variability of its sampling. We therefore recommend that researchers take into account for the limitations of the in situ datasets and process the model to resemble the data as much as possible.

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Cross-shelf exchange in the northwestern Black Sea

Zhou

Shapiro

Wobus

2014

J. Geophys. Res. Oceans

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The transports of water, heat, and salt between the northwestern shelf and deep interior of the Black Sea are investigated using a high-resolution three-dimensional primitive equation model. From April to August 2005, both onshore and offshore cross-shelf break transports in the top 20 m were 0.24 Sv on average, which is equivalent to the replacement of 60% of the volume of surface shelf waters (0-20 m) per month. Two main exchange mechanisms are studied: Ekman transport, and transport by mesoscale eddies and associated meanders of the Rim Current. The Ekman drift causes nearly uniform onshore or offshore flow over a large section of the shelf break, but it is confined to the upper layers. In contrast, eddies and meanders penetrate deep down to the bottom, but they are restricted laterally. During the strong wind events of 15-22 April and 1-4 July, some 0.66 3 10 12 and 0.44 3 10 12 m 3 of water were removed from the northwestern shelf, respectively. In comparison, the single long-lived Sevastopol Eddy generated a much larger offshore transfer of 2.84 3 10 12 m 3 over the period 23 April to 30 June, which is equivalent to 102% of the volume of northwestern shelf waters. Over the study period, salt exchanges increased the average density of the shelf waters by 0.67 kg m 23 and reduced the density contrast between the shelf and deep sea, while lateral heat exchanges reduced the density of the shelf waters by 0.16 kg m 23 and sharpened the shelf break front.

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Validation of the NEMO-ERSEM operational ecosystem model for the North West European Continental Shelf

Cited by 66 publications

References 54 publications

Observing and modelling phytoplankton community structure in the North Sea

Observing and modelling phytoplankton community structure in the North Sea

How should sparse marine in situ measurements be compared to a continuous model: an example

Cross-shelf exchange in the northwestern Black Sea

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