Modelling the seasonal cycle of the biological productivity in the Ligurian Sea by means of a 1D interdisciplinary model

A one-dimensional coupled physical-biogeochemical model has been built to study the pelagic food web of the Ligurian Sea (NW Mediterranean Sea). The physical model is the turbulent closure model (version 1D) developed at the GeoHydrodynamics and Environmental Laboratory (GHER) of the University of Liège. The ecosystem model contains nineteen state variables describing the carbon and nitrogen cycles of the pelagic food web. Phytoplankton and zooplankton are both divided in three size-based compartments and the model includes an explicit representation of the microbial loop including bacteria, dissolved organic matter, nano-, and micro- zooplankton. The internal carbon/nitrogen ratio is assumed variable for phytoplankton and detritus, and constant for zooplankton and bacteria. Silicate is considered as a potential limiting nutrient of phytoplankton growth. The aggregation model described in Kriest and Evans (2000) is used to evaluate the sinking rate of particulate detritus. The model is forced at the air-sea interface by meteorological data coming from METEO France. The DYFAMED time series data obtained during the year 2000 are used to calibrate and validate the biological model. The comparison of model results within in-situ DYFAMED data shows that although some processes are not represented by the model, such as horizontal and vertical advections, model results are in good agreement with observations and differences observed can be explained with environmental conditions

Numerical modeling of the central Black Sea ecosystem functioning during the eutrophication phase

Abstract A one-dimensional coupled physical–biogeochemical model has been developed to simulate the ecosystem of the central Black Sea at the end of the 1980s when eutrophication and invasion by gelatinous organisms seriously affected the stability and dynamics of the system. The physical model is the General Ocean Turbulence Model (GOTM) and the biogeochemical model describes the foodweb from bacteria to gelatinous carnivores through 24 state variables including three groups of phytoplankton: diatoms, s The mathematical modeling of phytoplankton and zooplankton dynamics, detritus and the microbial loop is based on the model developed by Van den Meersche et al. [Van den Meersche, K., Middelburg, J., Soetaert, K., van Rijswijk P.H.B., Heip, C., 2004. Carbon–nitrogen coupling and algal–bacterial interactions during an experimental bloom: Modeling a 13c tracer experiment. Limnology and Oceanography 49 (3), 862–878] and tested in the modeling of mesocosm experiments and of the Ligurian sea ecosystem The coupled model extends down to the sediments ( depth) and is forced at the air–sea interface by the 6 hourly ERA-40 reanalysis of ECMWF data. The model has been calibrated and validated using a large set of data available in the Black Sea TU Ocean Base. The biogeochemical model involves some hundred parameters which are first calibrated by hand using published values. Then, an identifiability analysis has been performed in order to determine a subset of identifiable parameters (i.e. ensemble In order to calibrate the particle dynamics and export, the chemical model was run off-line with the particle and microbial loop model in order to check its capacity of simulating anoxic waters. After a 104 year run, the model simulated profiles similar to observations but steady state was not reached suggesting that the Black Sea deep waters are not at steady state. The fully coupled model was then used to simulate the period 1988–1992 of the Black Sea ecosystem. The model solution exhibits a

Application of a sequential data assimilation technique to improve the results of a 1D couled physical-biogeochemical model of the Ligurian Sea

peer reviewe

Modelling the Ligurian Sea ecosystem by means of a 1D couled physical-biogeochemical model. Improvement of model results using sequential data assimilation

peer reviewedA 1D coupled physical-biogeochemical model has been built to study the pelagic food web of the Ligurian Sea (NW Mediterranean Sea). The physical model is the turbulent closure model (version 1D) developed at the GHER (University of Liège, Belgium). The ecosystem model contains nineteen state variables describing the carbon and nitrogen cycles of the pelagic food web. Silicate is considered as a potential limiting nutrient of diatoms’ growth. The aggregation model described in Kriest and Evans (2000) is used to evaluate the sinking rate of particulate detritus. The model is forced at the air-sea interface by the METEO France meteorological data. The DYFAMED time series data of year 2000 are used to calibrate and validate the biological model (Raick et al., 2005). By combining the numerical model and the available observations, data assimilation techniques are useful to improve the state estimation of the ocean. A Singular Fixed Extended Kalman filter (Pham et al., 1998) has been implemented in this way. Twin experiments are first performed to choose the suitable experimental protocol, which is then applied to perform real data assimilation experiments using DYFAMED data (Raick et al., submitted). To be coupled in a 3D environment, the ecosystem model is too complex. Our ongoing work is to perform a simplification, by studying simplified structures in comparison with the original ecosystem model. The advantage of deriving a simplified model from the complex one, is that we would be able to identify the most important processes of the Ligurian Sea ecosystem

Model complexity and performance: how far can we simplify?

Handling model complexity and reliability is a key area of research today. While complex models containing sufficient detail have become possible due to increased computing power, they often lead to too much uncertainty. On the other hand, very simple models often crudely oversimplify the real ecosystem and can not be used for management purposes. Starting from a complex and validated 1D pelagic ecosystem model of the Ligurian Sea (NW Mediterranean Sea), we derived simplified aggregated models in which either the unbalanced algal growth, the functional group diversity or the explicit description of the microbial loop was sacrificed. To overcome the problem of data availability with adequate spatial and temporal resolution, the outputs of the complex model are used as the baseline of perfect knowledge to calibrate the simplified models. Objective criteria of model performance were used to compare the simplified models’ results to the complex model output and to the available data at the DYFAMED station in the central Ligurian Sea. We show that even the simplest (NPZD) model is able to represent the global ecosystem features described by the complex model (e.g. primary and secondary productions, particulate organic matter export flux, etc.). However, a certain degree of sophistication in the formulation of some biogeochemical processes is required to produce realistic behaviors (e.g. the phytoplankton competition, the potential carbon or nitrogen limitation of the zooplankton ingestion, the model trophic closure, etc.). In general, a 9 state-variable model that has the functional group diversity removed, but which retains the bacterial loop and the unbalanced algal growth, performs best. [KEYWORDS: Model complexity reduction ; Model calibration ; Identifiability analysis ; Criteria of model performance ; Coupled hydrodynamic-ecosystem models ; NW Mediterranean Sea]