Real-time forecast modelling for the NW European Shelf Seas

Holt, M.; Li, Z.; Osborne, Jeff

doi:10.1016/s0422-9894(02)80011-3

Cited by 4 publications

(4 citation statements)

References 2 publications

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“…Over the past decades, increased understanding of physical processes and increased computational power have led to the progression from simple hydrodynamic models [e.g., Pingree and Griffiths , , M 2 tidal model] to multidecadal hindcasts and forecasts of entire shelf seas [ Holt et al ., ; Siddorn et al ., ; Kühn et al ., ; Wakelin et al ., ; van Leeuwen et al ., ], including frontal regions, coastal currents, density stratification, and ROFI (Region Of Freshwater Influence) areas. The same progression is noticeable in the marine biological sciences, which started with plankton as indicators of water masses, followed by the understanding that phytoplankters especially related more to vertical processes [ Margalef , ], and, by way of Legendre and Rassoulzadegan [] coming to see lifeforms of marine primary producers in relation to the (more terrestrially oriented) concept of biomes [ Tett et al ., ].…”

Section: Introductionmentioning

confidence: 99%

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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Section: Introductionmentioning

confidence: 99%

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 AMM is the operational implementation of a 12 km resolution POLCOMS which is one‐way nested into the Met Office Forecasting Ocean Assimilation Model (FOAM) 1/3° deep ocean model. For further information on AMM and FOAM the reader is referred to Holt et al [2003] and Bell et al [2003], respectively. MRCS is forced with meteorological fields (wind speed, pressure, heat and moisture fluxes) from the Met Office's Mesoscale Numerical Weather Prediction model.…”

Section: Model Descriptionmentioning

confidence: 99%

Assessment and development of a sediment model within an operational system

Sykes

Barciela

2012

J. Geophys. Res.

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[1] The Medium Resolution Continental Shelf (MRCS) modeling system is a coupled hydrodynamic plus sediment (POLCOMS) and ecosystem (ERSEM) model covering the UK shelf region. It is run operationally at the Met Office providing daily analyses and 5-day forecasts for a variety of fields. The output of the sediment model within the MRCS system has been assessed against CEFAS SmartBuoy turbidity data and satellite-retrieved surface sediment concentration for the period 2008 to 2009. The results of the assessment showed poor variability throughout the year highlighted by low correlations and large differences in standard deviations between the model and observations. In light of these results, the sediment model parameterizations for the mechanisms of erosion, deposition and settling were modified and the model was further developed by incorporating an aggregation/disaggregation scheme. The initialization method was also reviewed and updated. Assessment of this collection of developments showed significant improvements in variability as well as improvements in the quantitative match to the observations. Improvements were seen in correlations, mean values, standard deviations and percent differences throughout the assessment period. As a result of sensitivity studies it was found that each of the model developments had different impacts on improving the model predictions. All the model developments had a quantitative impact on the predicted surface sediment concentration with the aggregation acting to constrain the increase in sediment brought about by the erosion and settling. The changes in erosion and settling predominantly accounted for the improvement in correlation between the model and satellite observations. Citation: Sykes, P. A., and R. M. Barciela (2012), Assessment and development of a sediment model within an operational system,

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“…Holt et al, 2003;Elliott et al, 2007;Siddorn et al, 2007;Korotaev et al, 2011;Kordzadze and Demetrashvili, 2011;Stanev et al, 2011;Zhuang et al, 2011;Mateus et al, 2012), few models routinely produce forecasts of the biogeochemical fields (e.g. Siddorn et al, 2007;Mateus et al, 2012;Wan et al, 2012).…”

Section: Introductionmentioning

confidence: 99%