Vichi, Marcello

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

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 study presented in this thesis is principally meant to analyze the genericity of a deterministic, comprehensive marine ecosystem model in combination with various refined representations of hydrodynamical processes, and to evaluate the potential predictability skills of this combined modelling system with specific applications in two rather different coastal basins. This objective has been realized by first developing a modular coupling interface between the Princeton Ocean Model (POM) and the European Regional Seas Ecosystem Model (ERSEM), called High-Resolution OpenSESAME POM ERSEM (HiROPE). Secondly, this model framework, embedding a composite of 'complex' conceptual principles of the functioning of the main biogeochemical processes, has been applied to substantially different marine systems, the Baltic proper and the northern Adriatic Sea. The generic biological first principles of the ERSEM ecosystem model have been throughly controlled for consistency, and a suitable mathematical syntax has been defined in order to accomodate the various biogeochemical cycles of the resolved elements. The model has been specifically applied in the chosen basins with different temporal and spatial resolutions: a one-dimensional (vertical, 1D-V), climatological implementation in the northern Adriatic Sea; a 1D-V implementation in the Baltic proper with realistic forcing functions in the period 1979-1991 and a fully three-dimensional, high-frequency realistic implementation in the northern Adriatic Sea (October 1995). General conclusions are that the representation of hydrodynamical variability, the definition and resolution of boundary processes, the introduction of new source terms or the implementation of new biological state variables, affect the predictability of the system behavior more than the utilization of incomplete initial conditions of biological variables in a complex comprehensive ecosystem model.

Several biogeochemical data have been collected in the last 10 years of Italian activity in Antarctica (ABIOCLEAR, ROSSMIZE, BIOSESO-I/II). A comprehensive 1-D biogeochemical model was implemented as a tool to link observations with processes and to investigate the mechanisms that regulate the flux of biogenic material through the water column. The model is ideally located at station B (175° E–74° S) and was set up to reproduce the seasonal cycle of phytoplankton and organic matter fluxes as forced by the dominant water column physics over the period 1990–2001. Austral spring-summer bloom conditions are assessed by comparing simulated nutrient drawdown, primary production rates, bacterial respiration and biomass with the available observations. The simulated biogenic fluxes of carbon, nitrogen and silica have been compared with the fluxes derived from sediment traps data. The model reproduces the observed magnitude of the biogenic fluxes, especially those found in the bottom sediment trap, but the peaks are markedly delayed in time. Sensitivity experiments have shown that the characterization of detritus, the choice of the sinking velocity and the degradation rates are crucial for the timing and magnitude of the vertical fluxes. An increase of velocity leads to a shift towards observation but also to an overestimation of the deposition flux which can be counteracted by higher bacterial remineralization rates. Model results suggest that the timing of the observed fluxes depends first and foremost on the timing of surface production and on a combination of size-distribution and quality of the autochtonous biogenic material. It is hypothesized that the bottom sediment trap collects material originated from the rapid sinking of freshly-produced particles and also from the previous year's production period.

This paper presents a long-term time series (1986–2005) of hydrological and biogeochemical data, both published and unpublished. Data were collected in the north-western area of the Adriatic Sea, at two stations that are considered hydrodynamically and trophically different. The time series have been statistically and graphically analysed on a monthly scale in order to study the annual climatologies, links between the concentrations of chlorophyll-a and the variability in the environment, trophic differences between the two areas and chlorophyll-a trends over time. Basically, the two areas have similar hydrological features, yet they present significant differences in the amount of nutrient inputs: these are in fact higher at the coastal site, which is characterized by a prevalence of surface blooms, while they are lower at the offshore station, which is mainly affected by blooms at intermediate depths. Nonetheless, throughout the whole water column, chlorophyll-a concentrations are only slightly different. Both areas are affected by riverine discharge, though chlorophyll-a concentrations are also driven strongly by the seasonal cycle at the station closer to the coast. Results show that the two stations are not trophically different, although some controlling factors, such as zooplankton grazing in one case and light attenuation in the other, may further regulate the growth of phytoplankton. In both cases no significant trends are detected in either the average chlorophyll-a values or in dispersion of the data, in contrast with significant trends in temperature and salinity.

A refined Semtner 0-layer sea-ice model (ESIM1) is presented and applied to the Baltic landfast sea-ice. The physical model is capable of simulating seasonal changes of snow and ice thickness. Particular attention is paid to reproducing the snow-ice and the super-imposed-ice formation which play important roles in the total mass balance of the Baltic sea-ice. The model prognostic variables include all kinds of ice and snow layers that may be present during a Baltic landfast ice season and, in general, in every coastal area of an ice-covered ocean. The assessment of the model capabilities was done for 1979–1993 for four different stations in the Baltic Sea. A sensitivity test stresses the relevant role of some of the physical parameters, such as the oceanic heat flux, while a scenario analysis highlights the robustness of the model to perturbed physical forcing. Our results show that one of the key variables in modelling sea-ice thermodynamics is the snow layer and its metamorphism, and including the meteoric ice dynamics into a sea ice model is relevant to properly simulate any ice season, also in view of climate change scenarios

Global Ocean Biogeochemistry General Circulation Models are useful tools to study biogeochemical processes at global and large scales under current climate and future scenario conditions. The credibility of future estimates is however dependent on the model skill in capturing the observed multi-annual variability of firstly the mean bulk biogeochemical properties, and secondly the rates at which organic matter is processed within the food web. For this double purpose, the results of a multi-annual simulation of the global ocean biogeochemical model PELAGOS have been objectively compared with multi-variate observations from the last 20 years of the 20th century, both considering bulk variables and carbon production/consumption rates. Simulated net primary production (NPP) is comparable with satellite-derived estimates at the global scale and when compared with an independent data-set of in situ observations in the equatorial Pacific. The usage of objective skill indicators allowed us to demonstrate the importance of comparing like with like when considering carbon transformation processes. NPP scores improve substantially when in situ data are compared with modeled NPP which takes into account the excretion of freshly-produced dissolved organic carbon (DOC). It is thus recommended that DOC measurements be performed during in situ NPP measurements to quantify the actual production of organic carbon in the surface ocean. The chlorophyll bias in the Southern Ocean that affects this model as well as several others is linked to the inadequate representation of the mixed layer seasonal cycle in the region. A sensitivity experiment confirms that the artificial increase of mixed layer depths towards the observed values substantially reduces the bias. Our assessment results qualify the model for studies of carbon transformation in the surface ocean and metabolic balances. Within the limits of the model assumption and known biases, PELAGOS indicates a net heterotrophic balance especially in the more oligotrophic regions of the Atlantic during the boreal winter period. However, at the annual time scale and over the global ocean, the model suggests that the surface ocean is close to a weakly positive autotrophic balance in accordance with recent experimental findings and geochemical considerations.

So far, the role of appendicularians in the biogeochemical cycling of organic matter has been largely overlooked. Appendicularians represent only a fraction of total mesozooplankton biomass, however these ubiquitous zooplankters have very high filtration and growth rates compared to copepods, and produce numerous fecal pellets and filtering houses contributing to export production by aggregating small marine particles. To study their quantitative impact on biogeochemical flux, we have included this group in the biogeochemical flux model, using a recently developed ecophysiological model. One-dimensional annual simulations of the pelagic ecosystem including appendicularians were conducted with realistic surface forcing for the year 2000, using data from the DyFAMed open ocean station. The appendicularian grazing impact was generally low, but appendicularians increased detritus production by 8% and export production by 55% compared to a simulation without appendicularians. Therefore, current biogeochemical models lacking appendicularians probably under, or misestimate the detritus and export production by omitting the pathway from small-sized plankton to fast sinking detritus. Detritus production and export rates are 60% lower than the estimates from mesotrophic sites, showing that appendicularians’ role is lower but still significant in oligotrophic environments. The simulated annual export at 200 m exceeds sediment trap values by 44%, suggesting an intense degradation during the sinking of appendicularian detritus, supported by observations made at other sites. Thus, degradation and grazing of appendicularian detritus need better quantification if we are to accurately assess the role of appendicularia in export flux.

Coupled marine biogeochemical models are composed of a hydrodynamic component with a transport model for the ecological state variables and a model for the biogeochemical dynamics. The combination of these components involves the implementation of a numerical coupling method, that performs the spatial–temporal integration of the combined system, introducing an additional source of error to the system (splitting error). In this article we demonstrate the sensitivity of a comparatively complex 1D hydrodynamical biogeochemical model to the coupling method, showing that for an inadequate choice of the coupling method, the splitting error may dominate the numerical error of the system. It is demonstrated that for this type of system the tracer transport time scale clearly dominates over the scale of the biogeochemical processes, that maybe computed on significantly coarser time scales. In between the implemented coupling schemes Operator Splitting and Source Splitting, the Source Splitting method inserting the biogeochemical rates into the transport tracer integration is to be preferred for these type of models.