Making modelling count - increasing the contribution of shelf-seas community and ecosystem models to policy development and management

Marine legislation is becoming more complex and marine ecosystem-based management is specified in national and regional legislative frameworks. Shelf-seas community and ecosystem models (hereafter termed ecosystem models) are central to the delivery of ecosystem-based management, but there is limited uptake and use of model products by decision makers in Europe and the UK in comparison with other countries. In this study, the challenges to the uptake and use of ecosystem models in support of marine environmental management are assessed using the UK capability as an example. The UK has a broad capability in marine ecosystem modelling, with at least 14 different models that support management, but few examples exist of ecosystem modelling that underpin policy or management decisions. To improve understanding of policy and management issues that can be addressed using ecosystem models, a workshop was convened that brought together advisors, assessors, biologists, social scientists, economists, modellers, statisticians, policy makers, and funders. Some policy requirements were identified that can be addressed without further model development including: attribution of environmental change to underlying drivers, integration of models and observations to develop more efficient monitoring programmes, assessment of indicator performance for different management goals, and the costs and benefit of legislation. Multi-model ensembles are being developed in cases where many models exist, but model structures are very diverse making a standardised approach of combining outputs a significant challenge, and there is a need for new methodologies for describing, analysing, and visualising uncertainties. A stronger link to social and economic systems is needed to increase the range of policy-related questions that can be addressed. It is also important to improve communication between policy and modelling communities so that there is a shared understanding of the strengths and limitations of ecosystem models.     

The PROWQM physical–biological model with benthic–pelagic coupling applied to the northern North Sea

PROWQM, a 1-D depth resolving model which couples physical and microbiological processes in the water column with sedimentation/resuspension and benthic mineralisation processes, has been used to simulate seasonal changes of chlorophyll, nutrients and oxygen at the PROVESS north site (59°20′N 1°00′E) in the North Sea. PROWQM is derived from the 3-D model COHERENS, and improves COHEREN's benthic and pelagic biology.The physical sub-model of PROWQM implicitly solves turbulence closure equations forced by climatological, or realistic high-frequency, meteorological and tidal data. The pelagic biological sub-model 2MPPD includes a ‘diatomy’ microplankton (mp1) and a ‘flagellatey’ (or microbial loop) microplankton (mp2), the cycling of silicon and nitrogen, slow-sinking detritus, and fast-sinking phytodetritus. Phytodetritus is formed by shear-driven aggregation of particulate material, using a simple algorithm for bulk processes that is derived by considering the interactions of single cells. The microplankton compartments include heterotrophic bacteria and protozoa as well as phytoplankton, and most microplankton rates are specified with the aid of a ‘heterotroph fraction’ parameter, which was 0.125 for mp1 and 0.6 for mp2. The microbiological system is closed by mesozooplankton grazing pressures imposed as time varying series determined from observed zooplankton abundance. The benthic boundary sub-model includes a superficial fluff layer and a nutrient element reservoir in the consolidated sediment. Particulate material in the fluff layer can be resuspended (in response to bed stress by near-bed flows), mineralised or carried by bioturbation into the underlying, consolidated, sediment, where it is mineralised and its nutrients returned to the water-column at rates mainly dependent on (implicit) macrobenthic pumping. Benthic denitrification can occur when mineralisation rates exceed oxygen supply.Verification of the PROWQM numerical implementation used test cases and checks for nutrient element conservation. Simulations with realistic forcing, for a range of parameter values, were compared with historic observations in the NOWESP data set and during FLEX76, and with those made during the PROVESS cruises in autumn 1998. PROWQM provided a good simulation of the seasonal succession from a diatom-dominated spring bloom to summer dominance by small flagellates. The simulations included sedimentation of organic matter from the spring bloom, and qualitatively realistic behaviour of the fluff layer, but decay rates were too slow and there was almost no denitrification. The simulated surface mixed layer was too shallow during the summer. Simulated annual net microplankton primary production was in between 59 and 91 g C m⁻² y⁻¹. A large proportion of mineralisation, 28–47% of nitrogen and 40–67% of silicon mineralisation, took place as a result of the decay of sinking and resuspended detritus whilst in the water column.PROWQM is discussed in relation to other models that have been used to simulate this part of the North Sea, in particular the simpler ECOHAM1 and the more complex ERSEM, and in relation to PROWQM's evolution from COHERENS.     

NPZ Models of Plankton Dynamics: Their Construction, Coupling to Physics, and Application

Nutrient-phytoplankton-zooplankton (NPZ) models have been in use in oceanography for at least three decades, and are still a common research tool. Given the discoveries of the last two decades, particularly concerning the role of bacteria in the plankton, there are questions as to whether NPZ models can still be supported as a useful tool in planktonic research. Here I review the construction of NPZ models, and some of the physical platforms they have been coupled to. I then discuss the applications of NPZ-physical models, and conclude that they still constitute an important and viable research tool, provided that the questions being explored are clearly stated. This revised version was published online in August 2006 with corrections to the Cover Date.     

Sea-level fluctuations in the fleet, an English tidal lagoon

Tidal elevation data are presented for places along the length of the Fleet, which is a tidal lagoon behind Chesil Beach on the south coast of England. Harmonic analysis of the data is not able to represent the observations adequately, particularly at the inner end of the lagoon. However, careful inspection of the data shows that the tidal regime is capable of being understood in terms of the non-linear propagation of long waves in very shallow water. Distortion of the tidal wave by unequal progression speeds of high and low water, and the set-up of mean level by frictional effects, are shown to be the important physical mechanisms controlling the observed water level fluctuations. A one-dimensional numerical model which incorporates these processes is able to reproduce the observations satisfactorily. Whilst the model predicts strong effects of wind stress, the meteorological influences in the observed data appear to be largely due to external surges in the English Channel which propagate into the lagoon through its entrance.     

Weak and strong constraint data assimilation in the inverse Regional Ocean Modeling System (ROMS): Development and application for a baroclinic coastal upwelling system

We describe the development and preliminary application of the inverse Regional Ocean Modeling System (ROMS), a four dimensional variational (4DVAR) data assimilation system for high-resolution basin-wide and coastal oceanic flows. Inverse ROMS makes use of the recently developed perturbation tangent linear (TL), representer tangent linear (RP) and adjoint (AD) models to implement an indirect representer-based generalized inverse modeling system. This modeling framework is modular. The TL, RP and AD models are used as stand-alone sub-models within the Inverse Ocean Modeling (IOM) system described in [Chua, B.S., Bennett, A.F., 2001. An inverse ocean modeling system. Ocean Modell. 3, 137–165.]. The system allows the assimilation of a wide range of observation types and uses an iterative algorithm to solve nonlinear assimilation problems. The assimilation is performed either under the perfect model assumption (strong constraint) or by also allowing for errors in the model dynamics (weak constraints). For the weak constraint case the TL and RP models are modified to include additional forcing terms on the right hand side of the model equations. These terms are needed to account for errors in the model dynamics.Inverse ROMS is tested in a realistic 3D baroclinic upwelling system with complex bottom topography, characterized by strong mesoscale eddy variability. We assimilate synthetic data for upper ocean (0–450 m) temperatures and currents over a period of 10 days using both a high resolution and a spatially and temporally aliased sampling array. During the assimilation period the flow field undergoes substantial changes from the initial state. This allows the inverse solution to extract the dynamically active information from the synthetic observations and improve the trajectory of the model state beyond the assimilation window. Both the strong and weak constraint assimilation experiments show forecast skill greater than persistence and climatology during the 10–20 days after the last observation is assimilated.Further investigation in the functional form of the model error covariance and in the use of the representer tangent linear model may lead to improvement in the forecast skill.     

On using Boussinesq-type equations near the shoreline: a note of caution

We briefly analyze some characteristics of the behavior in very shallow waters i.e. near the shoreline of high-order (dispersive-nonlinear) Boussinesq-type equations. By using the Carrier and Greenspan (1958) solution as test flow conditions we illustrate the behavior of both purely dispersive and dispersive-nonlinear contributions near the shoreline. It is also shown that Boussinesq-type equations can be more usefully handled in the swash zone if written in terms of the total water depth.     

Comparison of wind and wave measurements and models in the Western Mediterranean Sea

We have hindcast the wind and wave conditions in the Mediterranean Sea for two one month periods. Four different meteorological models and three different wave models have been used. The results have been compared with satellite and buoy wind and wave observations.Several conclusions concerning both the instruments and the models have been derived. The quality of both wind and wave results has been assessed. Close to the coasts high resolution, nested wave models are required for sufficient reliability.A wave threshold analysis suggests a sufficient reliability only off the coast, with a substantial decrease for low wave heights.     

Some features of the dynamic structure of a deep estuary

A boundary layer formulation for the dynamic structure of a deep estuary is developed. Cross-stream averages are used, but the boundary layer structure is shown to depend on the cross-stream geostrophic constraint. A similarity transformation and a weighted residual method are used to derive an approximate solution for the velocity and salinity structure of the upper layer. This solution indicates that, in the central regime of the estuary, outflow extends through the entire halocline. Inflow takes place in a much less stratified lower layer, and mass exchange between the layers is by upwelling. This structure is modified in the outer regime of the estuary, where mixing between the layers develops, and in the inner regime, where a sharp halocline develops and where the dynamics are dominated by river runoff. The implications of the dynamics for the flushing process and for pollutant movement and dispersion are discussed.     

Forecasting ocean waves: Comparing a physics-based model with statistical models

The literature on ocean wave forecasting falls into two categories, physics-based models and statistical methods. Since these two approaches have evolved independently, it is of interest to determine which approach can predict more accurately, and over what time horizons. This paper runs a comparative analysis of a well-known physics-based model for simulating waves near shore, SWAN, and two statistical techniques, time-varying parameter regression and a frequency domain algorithm. Forecasts are run for the significant wave height, over horizons ranging from the current period (i.e., the analysis time) to 15 h. Seven data sets, four from the Pacific Ocean and three from the Gulf of Mexico, are used to evaluate the forecasts. The statistical models do extremely well at short horizons, producing more accurate forecasts in the 1–5 hour range. The SWAN model is superior at longer horizons. The crossover point, at which the forecast error from the two methods converges, is in the area of 6 h. Based on these results, the choice of statistical versus physics-based models will depend on the uses to which the forecasts will be put. Utilities operating wave farms, which need to forecast at very short horizons, may prefer statistical techniques. Navies or shipping companies interested in oceanic conditions over longer horizons will prefer physics-based models.