Ocean Ecosystem Model Research Articles

Ocean iron fertilization may amplify climate change pressures on marine animal biomass for limited climate benefit.

Climate change scenarios suggest that large-scale carbon dioxide removal (CDR) will be required to maintain global warming below 2°C, leading to renewed attention on ocean iron fertilization (OIF). Previous OIF modelling has found that while carbon export increases, nutrient transport to lower latitude ecosystems declines, resulting in a modest impact on atmospheric CO2 . However, the interaction of these CDR responses with ongoing climate change is unknown. Here, we combine global ocean biogeochemistry and ecosystem models to show that, while stimulating carbon sequestration, OIF may amplify climate-induced declines in tropical ocean productivity and ecosystem biomass under a high-emission scenario, with very limited potential atmospheric CO2 drawdown. The 'biogeochemical fingerprint' of climate change, that leads to depletion of upper ocean major nutrients due to upper ocean stratification, is reinforced by OIF due to greater major nutrient consumption. Our simulations show that reductions in upper trophic level animal biomass in tropical regions due to climate change would be exacerbated by OIF within ~20 years, especially in coastal exclusive economic zones (EEZs), with potential implications for fisheries that underpin the livelihoods and economies of coastal communities. Any fertilization-based CDR should therefore consider its interaction with ongoing climate-driven changes and the ensuing ecosystem impacts in national EEZs.

Impact of the Deep Chlorophyll Maximum in the Equatorial Pacific as Revealed in a Coupled Ocean GCM‐Ecosystem Model

AbstractA coupled ocean general circulation model (OGCM)‐ocean ecosystem model is used to investigate the effects of the deep chlorophyll maximum (DCM) on the ocean state in the equatorial Pacific Ocean. Climatological and interannual three‐dimensional (3‐D) chlorophyll (CHL) fields are captured well in control runs using the coupled ocean physics‐ecosystem model forced by prescribed atmospheric fields. Further sensitivity experiments are performed to assess the effects of 3‐D CHL structure using the OGCM with the prescribed CHL fields taken from the control runs: CHLclim and are runs in which climatological DCM effect is included or only surface CHL effect is included; CHLinter and are runs with interannually varying DCM effects included or not. The differences in the simulated ocean conditions are analyzed to explore DCM effects on sea surface temperature (SST) and amplitude of El Niño‐Southern Oscillation (ENSO). Two competing mechanisms responsible for the DCM effects are revealed: an ocean biology‐induced direct heating (OBH) effect, and an indirect cooling effect due to dynamic processes associated with vertical mixing and shallow meridional overturning circulation. There are three major findings: (a) DCM acts to reduce mean SST by around 0.2°C in the eastern equatorial Pacific, being larger than the surface CHL effects. (b) DCM interannual variability increases the ENSO amplitude to a comparable degree as the surface CHL effects. (c) The total net impact of vertical mixing, currents, and net surface heat flux makes SST drop more under the DCM effect than the surface CHL effect in the eastern Pacific. These findings provide a new insight into the feedback mechanisms for the bioclimate interactions.

Ocean biogeochemistry in the Canadian Earth System Model version 5.0.3: CanESM5 and CanESM5-CanOE

Abstract. The ocean biogeochemistry components of two new versions of the Canadian Earth System Model (CanESM) are presented and compared to observations and other models. CanESM5 employs the same ocean biology model as CanESM2, whereas CanESM5-CanOE (Canadian Ocean Ecosystem model) is a new, more complex model developed for CMIP6, with multiple food chains, flexible phytoplankton elemental ratios, and a prognostic iron cycle. This new model is described in detail and the outputs (distributions of major tracers such as oxygen, dissolved inorganic carbon, and alkalinity, the iron and nitrogen cycles, plankton biomass, and historical trends in CO2 uptake and export production) compared to CanESM5 and CanESM2, as well as to observations and other CMIP6 models. Both CanESM5 models show gains in skill relative to CanESM2, which are attributed primarily to improvements in ocean circulation. CanESM5-CanOE shows improved skill relative to CanESM5 for most major tracers at most depths. CanESM5-CanOE includes a prognostic iron cycle, and maintains high-nutrient/low-chlorophyll conditions in the expected regions (in CanESM2 and CanESM5, iron limitation is specified as a temporally static “mask”). Surface nitrate concentrations are biased low in the subarctic Pacific and equatorial Pacific, and high in the Southern Ocean, in both CanESM5 and CanESM5-CanOE. Export production in CanESM5-CanOE is among the lowest for CMIP6 models; in CanESM5, it is among the highest, but shows the most rapid decline after about 1980. CanESM5-CanOE shows some ability to simulate aspects of plankton community structure that a single-species model can not (e.g. seasonal dominance of large cells) but is biased towards low concentrations of zooplankton and detritus relative to phytoplankton. Cumulative ocean uptake of anthropogenic carbon dioxide through 2014 is lower in both CanESM5-CanOE (122 PgC) and CanESM5 (132 PgC) than in observation-based estimates (145 PgC) or the model ensemble mean (144 PgC).

Adaptive carbon export response to warming in the Sargasso Sea

Ocean ecosystem models predict that warming and increased surface ocean stratification will trigger a series of ecosystem events, reducing the biological export of particulate carbon to the ocean interior. We present a nearly three-decade time series from the open ocean that documents a biological response to ocean warming and nutrient reductions wherein particulate carbon export is maintained, counter to expectations. Carbon export is maintained through a combination of phytoplankton community change to favor cyanobacteria with high cellular carbon-to-phosphorus ratios and enhanced shallow phosphorus recycling leading to increased nutrient use efficiency. These results suggest that surface ocean ecosystems may be more responsive and adapt more rapidly to changes in the hydrographic system than is currently envisioned in earth ecosystem models, with positive consequences for ocean carbon uptake.

Plankton community response to fronts: winners and losers

AbstractFronts are particularly productive regions of the ocean, and biodiversity hotspots for many marine species. Here we use an ocean-ecosystem model to investigate the effect of fronts on plankton ecology. We focus on energetic fronts in Western Boundary Current systems that efficiently inject nutrients into the euphotic layer and which are physical boundaries between productive and oligotrophic provinces. We found that the fronts form an environment distinct from both provinces, favorable to some plankton groups (diatoms, dinoflagellates and large carnivorous zooplankton) and less favorable to others (pico-phytoplankton, coccolithophores and small grazers), and with an overall larger diversity. In agreement with previous understanding, we find that bottom-up abiotic processes (nutrient enrichment) explain the prevalence of groups with fast growing rates (the “winners”). Importantly, our results also show that biotic interactions within the ecosystem may play a larger role than previously thought. We show that the winners can have a negative impact on other plankton species (the “losers”) through two indirect competitive processes: community shading (modification of the light environment by the plankton community leading to light-limitation of some plankton groups) and shared predation (where an increase in one functional group leads to increased grazing by a shared predator on another functional group).

Seasonal cycle of surface ocean pCO2 and pH in the northern Indian Ocean and their controlling factors

This paper examines the seasonal variability of surface ocean pCO2and pH in the northern Indian Ocean. It aims to identify their controlling factors using a high-resolution, regional ocean-ecosystem model simulation and available surface ocean carbon observations. The seasonal variability of pCO2 and pH of the northern Indian Ocean is attributed to the changes in surface temperature (T), dissolved inorganic carbon (DIC), total alkalinity (ALK), and salinity (S). The western Arabian Sea has an enormous seasonal variance of pCO2 due to coastal upwelling dynamics. In contrast, the seasonal variance of pCO2 in the Bay of Bengal is governed by the upper ocean mixed layer dynamics, albeit with smaller amplitudes. The contribution of T (DIC) in the seasonal variance of pCO2 and pH at the western Arabian Sea is ±90 (∓100) μatm and ±0.18 (∓0.20) pH units, respectively. The contribution of ALK and S is complementary to each other in inducing seasonal variances of pCO2 and pH in the southeastern Arabian Sea with a magnitude of ±5∼10 μatm and ±0.02 pH units, respectively. In the northern Bay of Bengal, salinity plays a significant role in controlling seasonal variability of pCO2 and pH with amplitudes of roughly ±20 µatm and ±0.18 pH units, respectively, along the pathways of freshwater spreading. The maxima of seasonal amplitudes of pCO2 and pH occur during April-May and August-September for both basins. This study highlights the hotspots of pCO2 and pH in the northern Indian Ocean, where observational efforts to monitor pCO2 and pHbecome an essential requirement.

Anthropogenic Iron Deposition Alters the Ecosystem and Carbon Balance of the Indian Ocean Over a Centennial Timescale

AbstractPhytoplankton growth in the Indian Ocean is generally limited by macronutrients (nitrogen: N and phosphorus: P) in the north and by micronutrient (iron: Fe) in the south. Increasing atmospheric deposition of N and dissolved Fe (dFe) into the ocean due to human activities can thus lead to significant responses from both the northern and southern Indian Ocean ecosystems. Previous modeling studies investigated the impacts of anthropogenic nutrient deposition on the ocean, but their results are uncertain due to incomplete representations of the Fe cycling. This study uses a state‐of‐the‐art ocean ecosystem and Fe cycling model to evaluate the transient responses of ocean productivity and carbon uptake in the Indian Ocean, focusing on the centennial time scale. The model includes three major dFe sources and represents an internal Fe cycling modulated by scavenging, desorption, and complexation with multiple, spatially varying ligand classes. Sensitivity simulations show that after a century of anthropogenic deposition, ecosystem responses in the Indian Ocean are not uniform due to a competition between the phytoplankton community. In particular, the competition between diatom, coccolithophore, and picoplankton alters the balance between the organic and carbonate pumps in the Indian Ocean, increasing the carbon uptake along 50°S and the southeastern tropics while decreasing it in the Arabian Sea. Our results reveal the important role of ecosystem dynamics in controlling the sensitivity of carbon fluxes in the Indian Ocean under the impact of anthropogenic nutrient deposition over a centennial timescale.

Assessment of an ocean-ecosystem model in simulating the Indian coastal marine ecosystem dynamics

ABSTRACT This study describes an assessment of an ocean-ecosystem model in simulating marine ecosystem dynamics in the Indian coastal waters. Long-term sustained in-situ observations of temperature, salinity, chlorophyll-a and dissolved oxygen (DO) collected in the coastal waters of India, and ship-based observations are used for this assessment. The model captures observed trend of temperature, salinity and chlorophyll-a with high correlation in both eastern and western shelf waters except for salinity and DO along west and DO along east coast. The model performs very well in simulating the Indian coastal shelf ecosystem dynamics. The seasonal occurrence of prominent phytoplankton bloom in the central-east coast during pre-monsoon, south-west coast during monsoon and north-west coast during post-monsoon is realistically reproduced by the model. The model also reproduces the seasonal presence of significantly low DO content in the upwelled water at a shallow depth leading to coastal hypoxia in the south-west and central-east coast of India during summer monsoon. A fine-tuned model is useful in understanding better Indian coastal shelf ecosystem and predicting future changes in time and space, like the occurrence of coastal hypoxia or anticipating phytoplankton blooms. Such information is useful for predicting potential fishing grounds in coastal waters and fisheries management.

Temporal and Spatial Scales of Correlation in Marine Phytoplankton Communities

AbstractOcean circulation shapes marine phytoplankton communities by setting environmental conditions and dispersing organisms. In addition, processes acting on the water column (e.g., heat fluxes and mixing) affect the community structure by modulating environmental variables that determine in situ growth and loss rates. Understanding the scales over which phytoplankton communities vary in time and space is key to elucidate the relative contributions of local processes and ocean circulation on phytoplankton distributions. Using a global ocean ecosystem model, we quantify temporal and spatial correlation scales for phytoplankton phenotypes with diverse functional traits and cell sizes. Through this analysis, we address these questions: (1) Over what timescales do perturbations in phytoplankton populations persist? and (2) over what distances are variations in phytoplankton populations synchronous? We find that correlation timescales are short in regions of strong currents, such as the Gulf Stream and Antarctic Circumpolar Current. Conversely, in the subtropical gyres, phytoplankton population anomalies persist for relatively long periods. Spatial correlation length scales are elongated near ocean fronts and narrow boundary currents, reflecting flow paths and frontal patterns. In contrast, we find nearly isotropic spatial correlation fields where current speeds are small, or where mixing acts roughly equally in all directions. Phytoplankton timescales and length scales also vary coherently with phytoplankton body size. In addition to aiding understanding of phytoplankton population dynamics, our results provide global insights to guide the design of biological ocean observing networks and to better interpret data collected at long‐term monitoring stations.

Response of lower trophic ecosystem in the Japan Sea to horizontal nutrient flux change through the Tsushima Strait

The Japan Sea is a semi-closed sea with straits such as the Tsushima Strait (Korea Strait). The nutrient transport through the Tsushima Strait impacts on the ecosystem around the coast of Japan. We analyzed hydrographic data from the Tsushima Straits to reveal interannual variations in the volume transport, nutrient concentration, and nutrient transport. The nutrient transport in the strait has large interannual variations of ±50% of average transport. We developed a coupled ocean circulation and ecosystem model, in which the lateral boundary condition was applied based on our observation data, and investigated the biogeochemical responses in the Japan Sea to the variations in horizontal nutrient flux through the Tsushima Strait.We reproduced the lower trophic ecosystem in the Japan Sea and evaluated the contribution ratio of dissolved inorganic nitrogen supplied from the Tsushima Strait to the biogeochemical cycles in the Japan Sea. A primary production of more than 70% in the region of 300–400 km from the coast of Japan is determined by the nutrient inflow through the Tsushima Straits. We investigated the response of the lower trophic ecosystem in the Japan Sea associated with nutrient transport change (±50%) through the Tsushima Strait. We found large impacts on primary production related to horizontal nutrient flux change in the central regions in the Japan Sea and near the East Korea Warm Current region. The increase of chlorophyll a in the central regions is caused by the transportation of nutrients through the sub-surface layer of the Tsushima Straits from 50 m to 100 m. Horizontally transported nutrients in the sub-surface layer are not utilized by phytoplankton during the summer because of stratification, but they are supplied in the surface layer in autumn and winter by vertical mixing. These processes also increase primary production in broader regions (132° E, 37–41° N). The case study on the increased time for nutrient transport showed that the nutrient flux change in summer had the highest impact on the lower ecosystem changes. The present study suggests that the interannual variations in the nutrient transport through the Tsushima Straits impact the productivity of autumn blooms in the broader regions of the Japan Sea.

EcoGEnIE 1.0: plankton ecology in the cGEnIE Earth system model

Abstract. We present an extension to the carbon-centric Grid Enabled Integrated Earth system model (cGEnIE) that explicitly accounts for the growth and interaction of an arbitrary number of plankton species. The new package (ECOGEM) replaces the implicit, flux-based parameterisation of the plankton community currently employed, with explicitly resolved plankton populations and ecological dynamics. In ECOGEM, any number of plankton species, with ecophysiological traits (e.g. growth and grazing rates) assigned according to organism size and functional group (e.g. phytoplankton and zooplankton) can be incorporated at runtime. We illustrate the capability of the marine ecology enabled Earth system model (EcoGEnIE) by comparing results from one configuration of ECOGEM (with eight generic phytoplankton and zooplankton size classes) to climatological and seasonal observations. We find that the new ecological components of the model show reasonable agreement with both global-scale climatological and local-scale seasonal data. We also compare EcoGEnIE results to the existing biogeochemical incarnation of cGEnIE. We find that the resulting global-scale distributions of phosphate, iron, dissolved inorganic carbon, alkalinity, and oxygen are similar for both iterations of the model. A slight deterioration in some fields in EcoGEnIE (relative to the data) is observed, although we make no attempt to re-tune the overall marine cycling of carbon and nutrients here. The increased capabilities of EcoGEnIE in this regard will enable future exploration of the ecological community on much longer timescales than have previously been examined in global ocean ecosystem models and particularly for past climates and global biogeochemical cycles.

Extraction of Photosynthesis Parameters from Time Series Measurements of In Situ Production: Bermuda Atlantic Time-Series Study

Computing the vertical structure of primary production in ocean ecosystem models requires information about the vertical distribution of available light, chlorophyll concentration and photosynthesis response parameters. Conversely, given information on vertical structure of chlorophyll and light, we can extract photosynthesis parameters from vertical profiles of primary production measured at sea, as we illustrate here for the Bermuda Atlantic Time-Series Study. The procedure is based on a model of the production profile, which itself depends on the underwater light field. To model the light field, attenuation coefficients were estimated from measured optical profiles using a simple model of exponential decay of photosynthetically-available irradiance with depth, which accounted for 97% of the variance in the measured optical data. With the underwater light climate known, an analytical solution for the production profile was employed to recover photosynthesis parameters by minimizing the residual model error. The recovered parameters were used to model normalized production profiles and normalized watercolumn production. The model explained 95% of the variance in the measured normalized production at depth and 97% of the variance in measured normalized watercolumn production. A shifted Gaussian function was used to model biomass profiles and accounted for 93% of the variance in measured biomass at depth. An analytical solution for watercolumn production with the shifted Gaussian biomass was also tested. With the recovered photosynthesis parameters, maximum instantaneous growth rates were estimated by using a literature value for the carbon-to-chlorophyll ratio in this region of the Atlantic. An exact relationship between the maximum instantaneous growth rate and the daily growth rate in the ocean was derived. It was shown that calculating the growth rate by dividing the production by the carbon-to-chlorophyll ratio is equivalent to calculating it from the ratio of the final to the initial biomass, even when production is time dependent. Finally, the seasonal cycle of the recovered assimilation number at the Bermuda Station was constructed and analysed. The presented approach enables the estimation of photosynthesis parameters and growth rates from measured production profiles with only a few model assumptions, and increases the utility of in situ primary production measurements. The retrieved parameters have direct applications in satellite-based estimates of primary production from ocean-colour data, of which we give an example.

Modular System for Shelves and Coasts (MOSSCO v1.0) – a flexible and multi-component framework for coupled coastal ocean ecosystem modelling

Abstract. Shelf and coastal sea processes extend from the atmosphere through the water column and into the seabed. These processes reflect intimate interactions between physical, chemical, and biological states on multiple scales. As a consequence, coastal system modelling requires a high and flexible degree of process and domain integration; this has so far hardly been achieved by current model systems. The lack of modularity and flexibility in integrated models hinders the exchange of data and model components and has historically imposed the supremacy of specific physical driver models. We present the Modular System for Shelves and Coasts (MOSSCO; http://www.mossco.de), a novel domain and process coupling system tailored but not limited to the coupling challenges of and applications in the coastal ocean. MOSSCO builds on the Earth System Modeling Framework (ESMF) and on the Framework for Aquatic Biogeochemical Models (FABM). It goes beyond existing technologies by creating a unique level of modularity in both domain and process coupling, including a clear separation of component and basic model interfaces, flexible scheduling of several tens of models, and facilitation of iterative development at the lab and the station and on the coastal ocean scale. MOSSCO is rich in metadata and its concepts are also applicable outside the coastal domain. For coastal modelling, it contains dozens of example coupling configurations and tested set-ups for coupled applications. Thus, MOSSCO addresses the technology needs of a growing marine coastal Earth system community that encompasses very different disciplines, numerical tools, and research questions.

Functional dynamics of Emiliania huxleyi virus‐host interactions across multiple spatial scales

AbstractMarine viruses have an important role in the dynamics of phytoplankton blooms and have increasing representation in ocean ecosystem and biogeochemical models. There are multiple described functional forms available for incorporating viruses into ocean models, but most of them have not been validated against time series abundance data. We reviewed the functional forms currently used for lytic marine virus‐host dynamics and evaluated them against a compiled database of Emiliania huxleyi and E. huxleyi‐virus (EhV) abundances. The database includes data aggregated from three scales: laboratory, mesocosm, and field studies. Data‐model comparison supported some standard functional forms, for example a linear infection term, and did not support other standard functional forms, for example a linear viral decay term. This analysis also provided evidence of density dependence within virion populations and a possible mechanism for lower virus‐host ratios at high virion abundances. Some of the patterns were scale‐dependent, suggesting that processes studied at one scale might not translate to another scale. As marine virus model formulations diversify over time, there is the need for model inter‐comparison and evaluation.

Multi-dimensional interpolation of SMOS sea surface salinity with surface temperature and in situ salinity data

Availability of accurate remotely-sensed sea surface salinity (SSS) measurements is crucial to investigating fundamental aspects of the global hydrological cycle, ocean dynamics and marine biogeochemistry. The European Space Agency (ESA) Soil Moisture Ocean Salinity (SMOS) mission has been specifically designed for this aim. However, SMOS data display a high level of noise with respect to the signal they have to detect. Space–time averaging over relatively large sampling periods/areas is thus generally carried out to increase SSS accuracy, and further interpolation is required to fill in data gaps resulting from both mission geometry and other instrumental/physical limitations. Here, a daily, 1/4° nominal resolution, mesoscale-resolving SSS field product is obtained by using a multidimensional optimal interpolation (OI) algorithm combining SMOS salinity retrievals and satellite sea surface temperature data with in situ salinity measurements. The methodology has been developed in the framework of the ESA OSMOSIS (Ocean ecoSystem Modelling based on Observations from Satellite and In-Situ data) project and it is applied here to a wide zonal portion of the Southern Hemisphere (10°S–65°S). The interpolated SSS has been validated by looking at the differences with respect to fully independent in situ observations and by performing a wavenumber spectrum analysis. Despite minor progress being obtained in terms of root mean square of the differences with respect to in situ observations, a significant improvement in terms of effective spatial resolution is obtained with the new technique with respect to presently available SSS observation-based analyses.

Impact of marine mercury cycling on coastal atmospheric mercury concentrations in the North- and Baltic Sea region

Abstract The cycling of mercury between ocean and atmosphere is an important part of the global Hg cycle. Here we study the regional contribution of the air-sea exchange in the North- and Baltic Sea region. We use a newly developed coupled regional chemistry transport modeling (CTM) system to determine the flux between atmosphere and ocean based on the meteorological model COSMO-CLM, the ocean-ecosystem model ECOSMO, the atmospheric CTM CMAQ and a newly developed module for mercury partitioning and speciation in the ocean (MECOSMO). The model was evaluated using atmospheric observations of gaseous elemental mercury (GEM), surface concentrations of dissolved gaseous mercury (DGM), and air-sea flux (ASF) calculations based on observations made on seven cruises in the western and central Baltic Sea and three cruises in the North Sea performed between 1991 and 2006. It was shown that the model is in good agreement with observations: DGM (Normalized Mean Bias NMB=-0.27 N=413), ASF (NMB=-0.32, N=413), GEM (NMB=0.07, N=2359). Generally, the model was able to reproduce the seasonal DGM cycle with the best agreement during winter and autumn (NMBWinter=-0.26, NMBSpring=-0.41, NMBSummer=-0.29, NMBAutumn=-0.03). The modelled mercury evasion from the Baltic Sea ranged from 3400 to 4000 kg/a for the simulation period 1994–2007 which is on the lower end of previous estimates. Modelled atmospheric deposition, river inflow and air-sea exchange lead to an annual net Hg accumulation in the Baltic Sea of 500 to 1000 kg/a. For the North Sea the model calculates an annual mercury flux into the atmosphere between 5700 and 6000 kg/a. The mercury flux from the ocean influenced coastal atmospheric mercury concentrations. Running CMAQ coupled with the ocean model lead to better agreement with GEM observations. Directly at the coast GEM concentrations could be increased by up to 10% on annual average and observed peaks could be reproduced much better. At stations 100km downwind the impact was still observable but reduced to 1–3%.

A new application of conditional nonlinear optimal perturbation approach to boundary condition uncertainty

AbstractThe conditional nonlinear optimal perturbation (CNOP) approach was mainly used to investigate the effects of the uncertainties in initial condition and model parameters on model results. This study presents a new application of the CNOP approach to the investigation of the effects of boundary condition uncertainty. Specifically, we first give the general formulation of the CNOP approach for uncertainties of initial and boundary conditions and model parameters. The method is then applied to analyze the effects of nutrient perturbations at the bottom boundary of the water column on the modeled deep chlorophyll maximum (DCM) using an ocean ecosystem model. The results show that nutrient perturbations at the bottom boundary have significant impacts on the modeled DCM. Interestingly, the approach also reveals that nonlinear processes play important roles in the evolution of phytoplankton perturbations caused by nutrient perturbations at the bottom boundary. This implies that the CNOP approach is useful for investigating the effects of boundary condition uncertainty.

Effect of seasonal change in gas transfer coefficient on air–sea CO2 flux in the western North Pacific

We used an eddy-permitting three-dimensional ocean ecosystem model and applied it in the western North Pacific to understand the seasonal variations and horizontal distributions of the air–sea CO2 flux and difference in the partial pressure between sea water and the atmosphere (∆pCO2). The high-resolution model reproduced the observed zonal belt of strong CO2 uptake in the mid-latitude (30–45°N) western North Pacific including the Kuroshio extension and mixed water regions, which was difficult to show in previous coarse-resolution models. The East Asian winter monsoon, an important phenomenon in the western North Pacific, affects the seasonal CO2 air–sea gas exchange with a high (low) gas transfer coefficient in winter (summer). In the subtropical region, ∆pCO2 is negative in winter and positive in summer as a result of the temperature effect. Combination of seasonal change in gas transfer coefficient with ∆pCO2 suppresses CO2 release in the subtropical region, and vice versa in the subarctic region (i.e., suppresses CO2 uptake). That is, the East Asian winter monsoon in the western North Pacific contributes to the reduction of the annual CO2 flux through the seasonal change in the gas transfer coefficient, leading to an overall annual CO2 uptake in the subtropical region and CO2 release in the subarctic region.

Experiences in multiyear combined state–parameter estimation with an ecosystem model of the North Atlantic and Arctic Oceans using the Ensemble Kalman Filter

A sequence of one-year combined state–parameter estimation experiments has been conducted in a North Atlantic and Arctic Ocean configuration of the coupled physical–biogeochemical model HYCOM-NORWECOM over the period 2007–2010. The aim is to evaluate the ability of an ensemble-based data assimilation method to calibrate ecosystem model parameters in a pre-operational setting, namely the production of the MyOcean pilot reanalysis of the Arctic biology. For that purpose, four biological parameters (two phyto- and two zooplankton mortality rates) are estimated by assimilating weekly data such as, satellite-derived Sea Surface Temperature, along-track Sea Level Anomalies, ice concentrations and chlorophyll-a concentrations with an Ensemble Kalman Filter. The set of optimized parameters locally exhibits seasonal variations suggesting that time-dependent parameters should be used in ocean ecosystem models. A clustering analysis of the optimized parameters is performed in order to identify consistent ecosystem regions. In the north part of the domain, where the ecosystem model is the most reliable, most of them can be associated with Longhurst provinces and new provinces emerge in the Arctic Ocean. However, the clusters do not coincide anymore with the Longhurst provinces in the Tropics due to large model errors. Regarding the ecosystem state variables, the assimilation of satellite-derived chlorophyll concentration leads to significant reduction of the RMS errors in the observed variables during the first year, i.e. 2008, compared to a free run simulation. However, local filter divergences of the parameter component occur in 2009 and result in an increase in the RMS error at the time of the spring bloom.

Impact of assimilating physical oceanographic data on modeled ecosystem dynamics in the California Current System

A method to model ocean ecosystems using data-constrained physical circulation estimates is investigated. Physical oceanographic data is assimilated into a Regional Ocean Modeling System implementation of the California Current System using an incremental 4-Dimensional Variational method. The resulting state estimate drives a complex, self-assembling ocean ecosystem model for the year 2003, and results are evaluated against SeaWiFS surface and CalCOFI subsurface observations and with ecosystem model output driven by an unconstrained physical model. While physical data assimilation improves correlation with observations, this method also drives elevated levels of phytoplankton standing stock, leading to a large bias particularly in regions of low mean concentration. We identify two causes for this increase: biological rectification of fluctuating vertical nutrient transport due to gravity wave generation at assimilation cycle initialization and increased nutrient variance on density surfaces. We investigate one and propose other possible remedies for these deleterious side-effects of this data assimilation method.