ECOSMO II(CHL): a marine biogeochemical model for the North Atlantic and the Arctic

Abstract

Abstract. ECOSMO II is a fully coupled bio-physical model of 3D hydrodynamics with an intermediate-complexity NPZD (nutrient, phytoplankton, zooplankton, detritus) type biology including sediment-water column exchange processes originally formulated for the North Sea and Baltic Sea. Here we present an updated version of the model incorporating chlorophyll a as a prognostic state variable: ECOSMO II(CHL). The version presented here is online coupled to the HYCOM ocean model. The model is intended to be used for regional configurations for the North Atlantic and the Arctic incorporating coarse to high spatial resolutions for hind-casting and operational purposes. We provide the full descriptions of the changes in ECOSMO II(CHL) from ECOSMO II and provide the evaluation for the inorganic nutrients and chlorophyll a variables, present the modelled biogeochemistry of the Nordic Seas and the Arctic, and experiment on various parameterization sets as use cases targeting chlorophyll a dynamics. We document the performance of each parameter set objectively analysing the experiments against in situ, satellite and climatology data. The model evaluations for each experiment demonstrated that the simulations are consistent with the large-scale climatological nutrient setting and are capable of representing regional and seasonal changes. Explicitly resolving chlorophyll a allows for more dynamic seasonal and vertical variations in phytoplankton biomass to chlorophyll a ratio and improves model chlorophyll a performance near the surface. Through experimenting with the model performance, we document the general biogeochemisty of the Nordic Seas and the Arctic. The Norwegian and Barents seas primary production show distinct seasonal patterns with a pronounced spring bloom dominated by diatoms and low biomass during winter months. The Norwegian Sea annual primary production is around double that of the Barents Sea while also having an earlier spring bloom.

An along-track biogeochemical Argo modelling framework, a case study of model improvements for the Nordic Seas

“…These experiments are not only located in the Norwegian Sea, but cover various regions in the northern North Atlantic (Fig. 1), showing that the changes can improve model results throughout the northern North Atlantic which is the main region that ECOSMO II(CHL) is actively developed for (Yumruktepe et al, 2022b). As discussed above, fine-tuning is necessary as the model is too productive which is also the case for other experiments presented in this study.…”

“…For instance, we note that the model chlorophyll a is on the higher end with the parameter values chosen in this study (see Section 3.3.3). Finally, to achieve the full potential of this framework, improved process formulation should be evaluated with a more complex model in a 3D setting covering a range of use cases from operational oceanography (e.g., Yumruktepe et al, 2022b), to regional/global links to higher trophic levels (e.g., Utne et al, 2012) or to climate (e.g., Tjiputra et al, 2020).…”

“…We used ECOSMO II(CHL) (Y2022; Yumruktepe et al, 2022b) to simulate the biogeochemical processes in the water column. ECOSMO II(CHL) is an intermediate-complexity lower trophic level biogeochemical model resolving four inor-100 ganic nutrients (nitrate, ammonium, phosphate and silicate) utilized by three types of phytoplankton (diatoms, flagellates and cyanobacteria).…”

“…Element flow between ECOSMO II(CHL) variables are given in Figure 2. presents the upgrades to DS2013 version with the addition of an explicit chlorophyll a variable for each phytoplankton functional type, Yumruktepe et al (2022b) model evaluation reveal that further refinement of chlorophyll a is needed to improve its dynamical response to varying light conditions. We address this issue while presenting the use case of along-track BGC-Argo modelling framework.…”

“…Photosynthetically k Chl light attenuation due to chlorophyll a concentration constant m 2 mgChl −1 j = 1,2 denote the specific phytoplankton types and i = 1,2 the specific zooplankton types. Please refer to Yumruktepe et al (2022b) and Daewel and Schrum (2013) for the parameter values that are not given Table 2.…”