Behaviour of the ocean DMS(P) pools in the Sargasso Sea viewed in a coupled physical-biogeochemical ocean model

Abstract

Abstract:The dimethylsulfide (DMS) production model NODEM (Northern Oceans DMS Emission Model) was coupled with the water column ocean model GOTM (General Ocean Turbulence Model) that includes a two-equation k-ε turbulence scheme. This coupled physical-biogeochemical ocean model represents a significant improvement over the previous uncoupled version of NODEM that was driven by a diagnostic vertical mixing scheme. Using the same set of biogeochemical parameters, the coupled model is used to simulate the annual cycles of 1992 and 1993 at Hydrostation S in the Sargasso Sea. The better reproduction of the turbulent mixing environment corrects some deficiencies in nitrogen cycling, especially in the seasonal evolution of the nutrient concentrations. Hence, the coupled model captures the late-winter chlorophyll-and DMS(P)-rich blooms. It is also more adept at reproducing the vertical distribution of chlorophyll and DMS(P) in summer. Moreover, the DMS pool becomes less dependent on parameters controlling the nitrogen cycle and relatively more sensitive to parameters related to the sulfur cycle. Finally, the coupled model reproduces some of the observed differences in DMS(P) pools between 1992 and 1993, the latter being an independent data set not used in calibrating the initial version of NODEM.Résumé : Le modèle NODEM (« Northern Oceans DMS Emission Model ») de production de dimethylsulfide (DMS) a été couplé avec le modèle 1-D d'océan GOTM (« General Ocean Turbulence Model »), qui inclue un schéma de la turbulence océanique du second ordre de type k-ε. Ce modèle couplé physique et biogéochimique constitue une amé-lioration significative de la précédente version non couplée de NODEM, qui s'appuyait sur un schéma diagnostique pour le mélange vertical. Reprenant les mêmes paramètres biogéochimiques, le modèle couplé a été utilizé pour simuler le cycle saisonnier des années 1992 et 1993 à la station S en mer des Sargasses. La meilleure prise en compte de l'aspect turbulent du mélange océanique corrige certains défauts dans la représentation du cycle de l'azote, en particulier l'évolution saisonnière des concentrations en nutriments. Le modèle couplé capture maintenant les floraisons phytoplanctoniques de fin d'hiver et les pics en chlorophylle et en DMS(P) qui les caractérisent. Il améliore également la représentation des distributions verticales de chlorophylle et de DMS(P) en été. De plus, le réservoir de DMS est moins dépendant des paramètres contrôlant le cycle de l'azote, et relativement plus sensible aux paramètres reliés au cycle du souffre. Finalement, le modèle couplé reproduit certaines des différences observées entre 1992 et 1993 dans les réservoirs de DMS(P), la dernière année constituant un jeu de données indépendant qui n'a pas été utilizé pour la calibration de la version initiale de NODEM.Le Clainche et al. 803

A dynamic model of oceanic sulfur (DMOS) applied to the Sargasso Sea: Simulating the dimethylsulfide (DMS) summer paradox

“…Therefore, Cropp [2002] recommends that a priority for the next generation of DMSP/DMS models is the inclusion of a realistic microbial loop. Similar conclusions were reported by other authors [ Lefevre et al , 2002; Le Clainche et al , 2004; Vézina , 2004].…”

“…This allowed a higher degree of decoupling between DMS and CHL in these models. It was, however, shown by Le Clainche et al [2004] for the Sargasso Sea (using the same model as Lefevre et al [2002] but coupled to a dynamic turbulent scheme) that the seasonality of modeled DMS was lower than that of DMS observations and the summer maximum was underestimated.…”

The Dimethylsulfide Cycle in the Eutrophied Southern North Sea: A Model Study Integrating Phytoplankton and Bacterial Processes

“…Most of them subdivide phytoplankton into several functional groups characterized by a specific DMSP cell quota (S:C) in agreement with observations [7]. S:C quota is generally considered as a constant with the exception of models of Le Clainche et al [52] and Polimene et al [58] that include variation of S:C with light intensity. The representation of heterotrophic compartments is generally less complex [43] and only some recent modelling studies include an explicit representation of the bacteria (e.g.…”

Pelagic functional group modeling: Progress, challenges and prospects

“…Gabric et al, 1993Gabric et al, , 2003Archer et al, 2002;Lefe`vre et al, 2002;Cropp et al, 2004;Le Clainche et al, 2004). These models vary widely in their linkages to the carbon or nitrogen based ecosystem models that they are embedded in and in the number of phytoplankton (1-3), zooplankton (1-3) and bacterial (0-2) compartments simulated.…”