Vichi, Marcello

The Equatorial Undercurrent (EUC) is the major source of iron to the equatorial Pacific and it is sensitive to climatic changes as other components of the tropical Pacific. This work proposes a methodology based on a Lagrangian approach aimed at understanding the changes in the transport of iron rich waters to the EUC in a future climate change scenario, using climate model data from an Earth system model. A selected set of regions from the northern and southern extra-equatorial Pacific has been chosen. These regions are charac- terized by the presence of iron sources from continental shelf processes like the Papua New Guinea region and atmospheric deposition like the northern subtropical gyre. The trajectories that reach the EUC during the 20th and the 21st century departing from these areas have been analyzed using a set of statistics designed to determine variations in the amount of transport and in the travel times of the water masses. The transport of waters to the EUC from the north Pacific subtropical gyre and from the Bismarck Sea is projected to increase during the 21st century. The increase is particularly significant for water masses from the northern subtropical gyre, with travel times lower than 10 years in the second half of the 21st century. This increased interaction between the extra-tropics and the EUC may bring additional iron-rich waters in the high-nutrient low-chlorophyll region of the equatorial Pacific compatibly with the significant increase of the simulated net primary production found in the biogeochemical model, thus partly offsetting the anticipated decrease of production implied by the surface warming

A 1-D model system, consisting of the 1-D version of the Princeton Ocean Model (POM) coupled with the European Regional Seas Ecosystem Model (ERSEM) has been applied to a sub-basin of the Baltic Proper, the Bornholm basin. The model has been forced with 3h meteorological data for the period 1979-1990, producing a 12-year hindcast validated with datasets from the Baltic Environmental Database for the same period. The model results demonstrate the model to hindcast the time-evolution of the physical structure very well, confirming the view of the open Baltic water column as a three layer system of surface, intermediate and bottom waters. Comparative analyses of modelled hydrochemical components with respect to the independent data have shown that the long-term system behaviour of the model is within the observed ranges. Also primary production processes, deduced from oxygen (over)saturation are hindcast correctly over the entire period and the annual net primary production is within the observed range. The largest mismatch with observations is found in simulating the biogeochemistry of the Baltic intermediate waters. Modifications in the structure of the model (addition of fast-sinking detritus and polysaccharide dynamics) have shown that the nutrient dynamics are linked to the quality and dimensions of the organic matter produced in the euphotic zone, highlighting the importance of the residence time of the organic matter within the microbial foodweb in the intermediate waters. Experiments with different scenarios of riverine nutrient loads, assessed in the limits of a 1-D setup, have shown that the external input of organic matter makes the open Baltic model more heterotrophic. The characteristics of the inputs also drive the dynamics of nitrogen in the bottom layers leading either to nitrate accumulation (when the external sources are inorganic), or to coupled nitrification-denitrification (under strong organic inputs). The model indicates the permanent stratification to be the main feature of the system as regulator of carbon and nutrient budgets. The model predicts that most of the carbon produced in the euphotic zone is also consumed in the water column and this enhances the importance of heterotrophic benthic processes as final closure of carbon and nutrient cycles in the open Baltic.

This paper presents a global ocean implementation of a multi-component model of marine pelagic biogeochemistry coupled on-line with an ocean general circulation model forced with climatological surface fields (PELAgic biogeochemistry for Global Ocean Simulations, PELAGOS). The final objective is the inclusion of this model as a component in an Earth System model for climate studies. The pelagic model is based on a functional stoichiometric representation of marine biogeochemical cycles and allows simulating the dynamics of C, N, P, Si, O and Fe taking into account the variation of their elemental ratios in the functional groups. The model also includes a parameterization of variable chlorophyll/carbon ratio in phytoplankton, carrying chl as a prognostic variable. The first part of the paper analyzes the contribution of non-local advective–diffusive terms and local vertical processes to the simulated chl distributions. The comparison of the three experiments shows that the mean chl distribution at higher latitudes is largely determined by mixing processes, while vertical advection controls the distribution in the equatorial upwelling regions. Horizontal advective and diffusive processes are necessary mechanisms for the shape of chl distribution in the sub-tropical Pacific. In the second part, the results have been compared with existing datasets of satellite-derived chlorophyll, surface nutrients, estimates of phytoplankton community composition and primary production data. The agreement is reasonable both in terms of the spatial distribution of annual means and of the seasonal variability in different dynamical oceanographic regions. Results indicate that some of the model biases in chl and surface nutrients distributions can be related to deficiencies in the simulation of physical processes such as advection and mixing. Other discrepancies are attributed to inadequate parameterizations of phytoplankton functional groups. The model has skill in reproducing the overall distribution of large and small phytoplankton but tends to underestimate diatoms in the northern higher latitudes and overestimate nanophytoplankton with respect to picoautotrophs in oligotrophic regions. The performance of the model is discussed in the context of its use in climate studies and an approach for improving the parameterization of functional groups in deterministic models is outlined.

In this study a coupled ocean‐atmosphere model containing interactive marine biogeochemistry is used to analyze interannual, lagged, and decadal marine biogeochemical responses to the North Atlantic Oscillation (NAO), the dominant mode of North Atlantic atmospheric variability. The coupled model adequately reproduces present‐day climatologies and NAO atmospheric variability. It is shown that marine biogeochemical responses to the NAO are governed by different mechanisms according to the time scale considered. On interannual time scales, local changes in vertical mixing, caused by modifications in air‐sea heat, freshwater, and momentum fluxes, are most relevant in influencing phytoplankton growth through light and nutrient limitation mechanisms. At subpolar latitudes, deeper mixing occurring during positive NAO winters causes a slight decrease in late winter chlorophyll concentration due to light limitation and a 10%–20% increase in spring chlorophyll concentration due to higher nutrient availability. The lagged response of physical and biogeochemical properties to a high NAO winter shows some memory in the following 2 years. In particular, subsurface nutrient anomalies generated by local changes in mixing near the American coast are advected along the North Atlantic Current, where they are suggested to affect downstream chlorophyll concentration with 1 year lag. On decadal time scales, local and remote mechanisms act contemporaneously in shaping the decadal biogeochemical response to the NAO. The slow circulation adjustment, in response to NAO wind stress curl anomalies, causes a basin redistribution of heat, freshwater, and biogeochemical properties which, in turn, modifies the spatial structure of the subpolar chlorophyll bloom.

This work describes a novel implementation of the Biogeochemical Flux Model (BFM) in a sea ice system (BFMSI). The chosen representative groups of the sea ice food web rely on the same dynamics as the BFM. The main differences between BFM and BFMSI stand in the type and number of functional groups, in the parameters assigned to several physiological and ecological processes and in the dimensional size classes they represent. The differential equations of BFMSI are written here according to the nomenclature associated to the new sea ice state variables. At the boundaries, the sea ice system is also coupled to the atmosphere and to the ocean through the exchange of organic and inorganic matter. This is done by computing the entrapment of particulate and dissolved matter and gases when sea ice grows and release to the ocean when sea ice melts to ensure mass conservation. The implementation of the BFM in sea ice and the coupling structure in General Circulation Models will add a new component that may provide new adequate estimate of the role and importance of sea ice biogeochemistry in the global carbon cycle.

Currently biogeochemical models of the global ocean focus on simulating the coupling between prevalent physical conditions and the biogeochemical processes with the underlying assumption that coherent biological properties are a direct (or modulated) response to physics. This is one possible biogeographic characterisation of the pelagic environment, since biogeochemistry represents only one aspect of marine ecosystems. Several models are currently capable of simulating the chlorophyll distribution observed from space, though an objective validation with respect to relevant ecosystem properties is still lacking. In this paper we analyse the results of one of the most comprehensive models of ocean biogeochemistry with an emphasis on biogeographic validation sensu Longhurst (Ecological Geography of the Sea, 2007, 2nd edition, Academic Press). A set of multivariate statistical tools, Multi Dimensional Scaling (MDS) and Principal Components Analysis (PCA), are used to verify the existence of pre-defined biogeographic provinces and their statistical significance. The MDS ordination indicates that the given provinces are recognizable in the model on the basis of the selected variables. Analysis of Similarity (ANOSIM) shows that the provinces are statistically separable and they can be more easily distinguished in terms of their environmental features rather than their biology. The underlying relationships between the physical and biological properties are investigated through correlation analyses, thus providing some insights on how the model reproduces features characteristic of the various regions. Satellite chlorophyll data have been used to demonstrate external validation at the biogeographic level. The a priori provinces as characterised by chlorophyll values cannot be statistically separated in either the data or the model. It is likely this is related to the arbitrary choice of province boundaries, which are not necessarily the same as those derivable from non-interpolated SeaWiFS data. The PCA comparison of modelled and observed chlorophyll demonstrated some objective skill in the model as it generally captures the dominant mode of the data, although severe mismatch was identified in certain regions by visual comparison (Indian and Southern Oceans). The model also overestimated seasonal variability compared to the data. The method shows promise for helping overcome problems with model verification due to undersampling of most ocean biogeochemical variables.

A fully prognostic 1-D thermodynamic model, functional for studies of sea-ice biogeochemistry is developed to better understand the physical processes and the interactions between the environment and the sea-ice ecosystem. The physical model is capable of simulating seasonal changes of snow and ice thickness. Particular attention is paid to reproduce the snow-ice and the superimposed ice formation which play important roles in the dynamics of sea ice algae. The assessment of the model capabilities is done in 1979--1993 at four different stations in the Baltic Sea. A sensitivity analysis stresses the importance of adequate surface forcing functions to properly simulate the onset of sea ice. Our results show that thickness of the ice layers and timing of the melting are in good agreement with the observed data and confirm that one of the key variables in modelling sea-ice thermodynamics is the snow layer and its metamorphism.

The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ 14C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models' ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-a was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-a time series were available

This work introduces a novel approach for the modelling and coupling of sea ice biology to sea ice physics. The central concept of the coupling is the definition of the Biologically Active Layer, which is the time-varying fraction of sea ice that is connected to the ocean via brine pockets and channels, and acts as a rich habitat for many microorganisms. A simple but comprehensive physical model of the sea ice thermohalodynamics is coupled to a novel sea ice microalgal model of growth in the framework of the Biogeochemical Flux Model. The physical model provides the key physical properties of the Biologically Active Layer and the biological model simulates the physiological and ecological response of the algal community to the physical environment. Numerical simulations of chl-a were compared with observations at two different ice stations, in the Baltic and off the coast of Greenland, showing that this new coupling structure is sufficiently generic to represent well the temporal and spatial distribution of sea ice algae during the whole ice season at both sites. This model implementation and coupling structure is viable as a new component of General Circulation Models, allowing for estimates of the role and importance of sea ice biology in the local and global carbon cycle.

The seasonal dynamics of pelagic and sea ice communities are closely related in ice-covered waters, however, modelling works that analyse such interactions are scarce. We use the Biogeochemical Flux Model in Sea Ice (BFM-SI) coupled to the pelagic Biogeochemical Flux Model (BFM) in a study area in Greenland to quantitatively investigate: (1) the significance of photoacclimation/photoadaptation strategies of autotrophs, (2) the fate of the sea ice biomass in case of algae seeding, algae aggregation and at different mixed layer depths and (3) the changes in community production under a climate change scenario. The results show that sea ice algae need to be both photoacclimated and photoadapted to the sea ice environment in order to grow, while phytoplankton may adopt different strategies for optimising their growth. The seeding of the phytoplankton bloom shows to be driven, both in timing and magnitude, by the viability of sea ice algae and by the degree of aggregation of algae released from the ice, which also affects the sinking rate to the sea floor. Under a mild climate change scenario (SRES B2, 2071–2090) the sea ice community is projected to be generally more productive, whereas phytoplankton growth will be reduced because the melt of sea ice will occur earlier in the season when light is less favourable to sustain the growth. While it is generally anticipated that the melting of multi-year ice in the Arctic Ocean will cause an increase in marine production, this study shows that seasonal ice-covered seas in the Northern hemisphere may actually be less productive and may shift to more oligotrophic conditions within the next 100 years.