[1] Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical onedimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways. Citation: Friedrichs, M. A. M., et al. (2007), Assessment of skill and portability in regional marine biogeochemical models: Role of multiple planktonic groups,

In this paper, we review the state of the art and major challenges in current efforts to incorporate biogeochemical functional groups into models that can be applied on basin-wide and global scales, with an emphasis on models that might ultimately be used to predict how biogeochemical cycles in the ocean will respond to global warming. We define the term ''biogeochemical functional group'' to refer to groups of organisms that mediate specific chemical reactions in the ocean. Thus, according to this definition, ''functional groups'' have no phylogenetic meaning-these are composed of many different species with common biogeochemical functions. Substantial progress has been made in the last decade toward quantifying the rates of these various functions and understanding the factors that control them. For some of these groups, we have developed fairly sophisticated models that incorporate this understanding, e.g. for diazotrophs (e.g. Trichodesmium), silica producers (diatoms) and calcifiers (e.g. coccolithophorids and specifically Emiliania huxleyi). However, current representations of nitrogen fixation and calcification are incomplete, i.e., based primarily upon models of Trichodesmium and E. huxleyi, respectively, and many important functional groups have not yet been considered in open-ocean biogeochemical models. Progress has been made over the last decade in efforts to simulate dimethylsulfide (DMS) production and cycling (i.e., by dinoflagellates and prymnesiophytes) and denitrification, but these efforts are still in their infancy, and many significant problems remain. ARTICLE IN PRESSOne obvious gap is that virtually all functional group modeling efforts have focused on autotrophic microbes, while higher trophic levels have been completely ignored. It appears that in some cases (e.g., calcification), incorporating higher trophic levels may be essential not only for representing a particular biogeochemical reaction, but also for modeling export. Another serious problem is our tendency to model the organisms for which we have the most validation data (e.g., E. huxleyi and Trichodesmium) even when they may represent only a fraction of the biogeochemical functional group we are trying to represent.When we step back and look at the paleo-oceanographic record, it suggests that oxygen concentrations have played a central role in the evolution and emergence of many of the key functional groups that influence biogeochemical cycles in the present-day ocean. However, more subtle effects are likely to be important over the next century like changes in silicate supply or turbulence that can influence the relative success of diatoms versus dinoflagellates, coccolithophorids and diazotrophs. In general, inferences drawn from the paleo-oceanographic record and theoretical work suggest that global warming will tend to favor the latter because it will give rise to increased stratification. However, decreases in pH and Fe supply could adversely impact coccolithophorids and diazotrophs in the future.It may be necessary...

Despite the huge extent of the ocean's surface, until now relatively little attention has been paid to the sea surface microlayer (SML) as the ultimate interface where heat, momentum and mass exchange between the ocean and the atmosphere takes place. Via the SML, large-scale environmental changes in the ocean such as warming, acidification, deoxygenation, and eutrophication potentially influence cloud formation, precipitation, and the global radiation balance. Due to the deep connectivity between biological, chemical, and physical processes, studies of the SML may reveal multiple sensitivities to global and regional changes. Understanding the processes at the ocean's surface, in particular involving the SML as an important and determinant interface, could therefore provide an essential contribution to the reduction of uncertainties regarding ocean-climate feedbacks. This review identifies gaps in our current knowledge of the SML and highlights a need to develop a holistic and mechanistic understanding of the diverse biological, chemical, and physical processes occurring at the ocean-atmosphere interface. We advocate the development of strong interdisciplinary expertise and collaboration in order to bridge between ocean and atmospheric sciences. Although this will pose significant methodological challenges, such an initiative would represent a new role model for interdisciplinary research in Earth System sciences.

An optimization experiment is performed with a vertically resolved, nitrogen-based ecosystem model, composed of four state variables (NPZD-model): dissolved inorganic nitrogen (N), phytoplankton (P), herbivorous zooplankton (Z) and detritus (D). Parameter values of the NPZD-model are optimized while assimilating observationsat three locations in the North Atlantic simultaneously, namely at the sites of the Bermuda Atlantic Time-Series Study (BATS; 31N 64W), of the North Atlantic Bloom Experiment (NABE; 47N 20W), and of Ocean Weather Ship-India (OWS-INDIA; 59N 19W). A method is described for a simultaneous optimization which effectively merges different types of observational data at distinct sites in the ocean. A micro-genetic algorithm is applied for the minimization of a weighted least square mis t function. The optimal parameter estimates are shown to represent a compromise among local parameter estimates that would be obtained from single-site optimizations at the individual locations. The optimization yields a high estimate of the initial slope parameter of photosynthesis(a), which is shown to be necessary to match the initial phases of phytoplankton growth. The estimate of a is well constrained by chlorophyll observations at the BATS and OWS-INDIA sites and likely compensates for a de ciency in the parameterizationof light-limited growth. The optimization also points toward an enhanced recycling of organic nitrogen which is perceived from a high estimate for the phytoplankton mortality/ excretion rate.