Modelling the hydrodynamics and ecosystem of the North-West European continental shelf for operational oceanography

Siddorn, John; Allen, J. Icarus; Blackford, Jerry; Gilbert, F.; Holt, Jason; Holt, M.; Osborne, Jeff; Proctor, Roger; Mills, David K.

doi:10.1016/j.jmarsys.2006.01.018

Cited by 76 publications

(70 citation statements)

References 35 publications

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“…Velocity fields were obtained from the operational runs of the Medium Resolution Continental Shelf (MRCS) version of POLCOMS which are performed at the UK National Centre for Ocean Forecasting (www.met-office.gov.uk/research/ncof/mrcs/, Siddorn et al, 2007). The model has a horizontal spatial resolution of 6-7 km and is forced by modelled wind stresses from the UK Meteorological Office Unified Model.…”

Section: 2mentioning

confidence: 99%

“…The depth-varying RMS error in temperature, calculated against available CTD data from the North Sea Project, was 0.81 °C (Holt et al (2005). The pre-operational version of the MRCS model was also evaluated by Siddorn et al (2007), but the data used were largely obtained from the southern North Sea and Celtic Sea and did not extend to the north-western portion of the continental shelf of interest here.…”

Section: 2mentioning

confidence: 99%

“…The IBM approach provides a contrast to that of generic ecosystem models such as ERSEM (Baretta et al, 1995;Allen et al, 2001), which typically model phytoplankton as functional groups and do not resolve to species level, but in which complex interactions between different functional groups and trophic levels may be simulated. Such models are now entering the era of operational forecasting (Siddorn et al, 2007), but forecast modelling of harmful algal blooms using generic ecosystem models is problematic due to the complexity of food web interactions and the difficulty in such a system of discriminating harmful from benign organisms (Allen et al, 2008). For example, Vanhoutte-Brunier et al (2008) found it necessary to add a specific K. mikimotoi algorithm to a generic ecosystem model to study a bloom in the English Channel during 2003.…”

mentioning

confidence: 99%

“…We coupled that biological model with flow and scalar (i.e. temperature and salinity) fields from the operational deployment (Siddorn et al, 2007) of the Proudman Oceanographic laboratory Coastal Ocean Modelling System (POLCOMS, ). The coupled model was then applied to the simulation of the progression and development of the major K. mikimotoi bloom in Scottish coastal waters during the period of JulySeptember 2006.…”

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confidence: 99%

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Individual-based modelling of the development and transport of a Karenia mikimotoi bloom on the North-west European continental shelf

et al. 2016

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Section: 2mentioning

confidence: 99%

Section: 2mentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Individual-based modelling of the development and transport of a Karenia mikimotoi bloom on the North-west European continental shelf

et al. 2016

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“…Operational and pre-operational physical-biogeochemical models routinely generating ecological products now exist (Siddorn et al, 2007;Brasseur et al, 2009) and their products, including forecasts, are being disseminated in nearreal time to end-users (www.myocean.eu). The South West Algal Pilot Project (SWAPP) and its successor, the AlgaRisk project (www.npm.ac.uk/rsg/projects/algarisk, Barciela et al, 2009), assessed and demonstrated the feasibility of this approach for forecasting algal blooms affecting the coastal waters of the UK, through the combination of satellite observations, model and meteorological data (Mahdon et al, 2010).…”

Section: Decision Support In Near Real Timementioning

confidence: 99%

An ECOOP web portal for visualising and comparing distributed coastal oceanography model and in situ data

et al. 2011

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Abstract. As part of a large European coastal operational oceanography project (ECOOP), we have developed a web portal for the display and comparison of model and in situ marine data. The distributed model and in situ datasets are accessed via an Open Geospatial Consortium Web Map Service (WMS) and Web Feature Service (WFS) respectively. These services were developed independently and readily integrated for the purposes of the ECOOP project, illustrating the ease of interoperability resulting from adherence to international standards.The key feature of the portal is the ability to display coplotted timeseries of the in situ and model data and the quantification of misfits between the two. By using standardsbased web technology we allow the user to quickly and easily explore over twenty model data feeds and compare these with dozens of in situ data feeds without being concerned with the low level details of differing file formats or the physical location of the data.Scientific and operational benefits to this work include model validation, quality control of observations, data assimilation and decision support in near real time. In these areas it is essential to be able to bring different data streams together from often disparate locations.

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Stratified and nonstratified areas in the N orth S ea: Long‐term variability and biological and policy implications

Leeuwen

Tett

Mills

et al. 2015

J. Geophys. Res. Oceans

135

121

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The European Unions' Marine Strategy Framework Directive aims to limit anthropogenic influences in the marine environment. But marine ecosystems are characterized by high variability, and it is not trivial to define its natural state. Here, we use the physical environment as a basis for marine classification, as it determines the conditions in which organisms must operate to survive and thrive locally. We present a delineation of the North Sea into five distinct regimes, based on multidecadal stratification characteristics. Results are based on a 51 year simulation of the region using the coupled hydrobiogeochemical model GETM-ERSEM-BFM. The five identified regimes are: permanently stratified, seasonally stratified, intermittently stratified, permanently mixed, and Region Of Freshwater Influence (ROFI). The areas characterized by these regimes show some interannual variation in geographical coverage, but are overall remarkable stable features within the North Sea. Results also show that 29% of North Sea waters fail to classify as one of the defined stratification regimes, due to high interannual variability. Biological characteristics of these regimes differ from diatombased food webs in areas with prolonged stratification to Phaeocystis-dominated food webs in areas experiencing short-lived or no stratification. The spatial stability of the identified regimes indicates that carefully selected monitoring locations can be used to represent a substantive area of the North Sea.

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Modelling the hydrodynamics and ecosystem of the North-West European continental shelf for operational oceanography

Cited by 76 publications

References 35 publications

Individual-based modelling of the development and transport of a Karenia mikimotoi bloom on the North-west European continental shelf

Individual-based modelling of the development and transport of a Karenia mikimotoi bloom on the North-west European continental shelf

An ECOOP web portal for visualising and comparing distributed coastal oceanography model and in situ data

Stratified and nonstratified areas in the N orth S ea: Long‐term variability and biological and policy implications

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