On the key role of nutrient data to constrain a coupled physical–biogeochemical assimilative model of the North Atlantic Ocean

A sequential assimilative system has been implemented into a coupled physical–biogeochemical model (CPBM) of the North Atlantic basin at eddy-permitting resolution (1/4°), with the long-term goal of estimating the basin scale patterns of the oceanic primary production and their seasonal variability. The assimilation system, which is based on the SEEK filter [Brasseur, P., Verron, J., 2006. The SEEK filter method for data assimilation in oceanography: a synthesis. Ocean Dynamics. doi: 10.1007/s10236-006-0080-3], has been adapted to this CPBM in order to control the physical and biogeochemical components of the coupled model separately or in combination. The assimilated data are the satellite Topex/Poseidon and ERS altimetric data, the AVHRR Sea Surface Temperature observations, and the Levitus climatology for salinity, temperature and nitrate.In the present study, different assimilation experiments are conducted to assess the relative usefulness of the assimilated data to improve the representation of the primary production by the CPBM. Consistently with the results obtained by Berline et al. [Berline, L., Brankart, J-M., Brasseur, P., Ourmières, Y., Verron, J., 2007. Improving the physics of a coupled physical–biogeochemical model of the North Atlantic through data assimilation: impact on the ecosystem. J. Mar. Syst. 64 (1–4), 153–172] with a comparable assimilative model, it is shown that the assimilation of physical data alone can improve the representation of the mixed layer depth, but the impact on the ecosystem is rather weak. In some situations, the physical data assimilation can even worsen the ecosystem response for areas where the prior nutrient distribution is significantly incorrect. However, these experiments also show that the combined assimilation of physical and nutrient data has a positive impact on the phytoplankton patterns by comparison with SeaWiFS ocean colour data, demonstrating the good complementarity between SST, altimetry and in situ nutrient data. These results suggest that more intensive in situ measurements of biogeochemical nutrients are urgently needed at basin scale to initiate a permanent monitoring of oceanic ecosystems.     

Modelling the silica pump in the Permanently Open Ocean Zone of the Southern Ocean

A coupled 1D physical–biogeochemical model has been built to simulate the cycles of silicon and of nitrogen in the Indian sector of the Permanently Open Ocean Zone of the Southern Ocean. Based on a simplified trophic network, that includes two size classes of phytoplankton and of zooplankton, and a microbial loop, it has been calibrated by reference to surface physical, chemical and biological data sets collected at the KERFIX time-series station (50°40′S–68°25′E). The model correctly reproduces the high nutrient low chlorophyll features typical of the studied area. In a region where the spring–summer mixed layer depth is usually deeper than 60 m, the maximum of chlorophyll never exceeds 1.5 mg m⁻³, and the annual primary production is only 68 g C m⁻² year⁻¹. In the surface layer nitrate is never exhausted (range 27–23.5 mmoles m⁻³) while silicic acid shows strong seasonal variations (range 5–20 mmoles m⁻³). On an annual basis 71% of the primary production sustained by nanophytoplankton is grazed by microzooplankton. Compared to North Atlantic, siliceous microphytoplankton is mainly prevented from blooming because of an unfavourable spring–summer light-mixing regime. Silicic acid limitation (high half saturation constant for Si uptake: 8 mmoles m⁻³) also plays a major role on diatom growth. Mesozooplankton grazing pressure excerpts its influence especially in late spring. The model illustrates the efficiency of the silica pump in the Southern Ocean: up to 63% of the biogenic silica that has been synthetized in the photic layer is exported towards the deep ocean, while only 11% of the particulate organic nitrogen escapes recycling in the surface layer.     

The Mercator global ocean operational analysis system: Assessment and validation of an 11-year reanalysis

This paper presents Prototype Système 2 Global (PSY2G), the first Mercator global Ocean General Circulation Model (OGCM) to assimilate along-track sea level anomaly (SLA) satellite data. Based on a coarse resolution ocean model, this system was developed mainly for climatic purposes and will provide, for example, initial oceanic states for coupled ocean-atmosphere seasonal predictions. It has been operational since 3 September 2003 and produces an analysis and a two-week forecast for the global ocean every week. The PSY2G system uses an incremental assimilation scheme based on the Cooper and Haines [Cooper, M., Haines, K., 1996. Data assimilation with water property conservation. J. Geophys. Res., 101, 1059-1077.] lifting–lowering of isopycnals. The SLA increment is obtained using an optimal interpolation method then the correction is partitioned into baroclinic and barotropic contributions. The baroclinic ocean state correction consists of temperature, salinity and geostrophic velocity increments and the barotropic correction is a barotropic velocity increment. A reanalysis (1993–2003) was carried out that enabled the PSY2G system to perform its first operational cycle. All available SLA data sets (TOPEX/Poséïdon, ERS2, Geosat-Follow-On, Jason1 and Envisat) were assimilated for the 1993–2003 period. The major objective of this study is to assess the reanalysis from both an assimilation and a thermodynamic point of view in order to evaluate its realism, especially in the tropical band which is a key region for climatic studies. Although the system is also able to deliver forecasts, we have mainly focused on analysis. These results are useful because they give an a priori estimation of the qualities and capabilities of the operational ocean analysis system that has been implemented. In particular, the reanalysis identifies some regional biases in sea level variability such as near the Antarctic Circumpolar Current, in the eastern Equatorial Pacific and in the Norwegian Sea (generally less than 1 cm) with a small seasonal cycle. This is attributed to changes in mean circulation and vertical stratification caused by the assimilation methodology. But the model's low resolution, inaccurate physical parameterisations (especially for ocean–ice interactions) and surface atmospheric forcing also contribute to the occurrence of the SLA biases. A detailed analysis of the thermohaline structure of the ocean reveals that the isopycnal lifting–lowering tends to diffuse vertically the main thermocline. The impact on temperature is that the surface layer (0–200 m) becomes cooler whereas in deeper waters (from 500 to 1500 m), the ocean becomes slightly warmer. This is particularly true in the tropics, between 30°N and 30°S. However it can be demonstrated that the assimilation improves the variability in both surface currents and sub-surface temperature in the Equatorial Pacific Ocean.     

A Mean Dynamic Topography of the Mediterranean Sea computed from altimetric data, in-situ measurements and a general circulation model

In the Mediterranean Sea, where the mean circulation is largely unknown and characterized by smaller scales and less intensity than in the open ocean, the interpretation of altimetric Sea Level Anomalies (SLA) is rather difficult. In the context of operational systems such as MFS (Mediterranean Forecasting System) or MERCATOR, that assimilate the altimetric information, the estimation of a realistic Mean Dynamic Topography (MDT) consistent with altimetric SLA to be used to reconstruct absolute sea level is a crucial issue. A method is developed here to estimate the required MDT combining oceanic observations as altimetric and in-situ measurements and outputs from an ocean general circulation model (OGCM).In a first step, the average over the 1993–1999 period of dynamic topography outputs from MFS OGCM provides a first guess for the computation of the MDT. Then, in a second step, drifting buoy velocities and altimetric data are combined using a synthetic method to obtain local estimates of the mean geostrophic circulation which are then used to improve the first guess through an inverse technique and map the MDT field (hereafter the Synthetic Mean Dynamic Topography or SMDT) on a 1/8° resolution grid.Many interesting current patterns and cyclonic/anticyclonic structures are visible on the SMDT obtained. The main Mediterranean coastal currents are well marked (as the Algerian Current or the Liguro–Provenço–Catalan Current). East of the Sicily channel, the Atlantic Ionian Stream divides into several main branches crossing the Ionian Sea at various latitudes before joining at 19°E into a unique Mid-Mediterranean Jet. Also, strong signatures of the main Mediterranean eddies are obtained (as for instance the Alboran gyre, the Pelops, Ierapetra, Mersa-Matruh or Shikmona anticyclones and the Cretan, Rhodes or West Cyprius cyclones). Independent in-situ measurements from Sea Campaigns NORBAL in the North Balearic Sea and the North Tyrrhenian Sea and SYMPLEX in the Sicily channel are used to validate locally the SMDT: deduced absolute altimetric dynamic topography compares well with in-situ observations. Finally, the SMDT is used to compute absolute altimetric maps in the Alboran Sea and the Algerian Current. The use of absolute altimetric signal allows to accurately follow the formation and propagation of cyclonic and anticyclonic eddies in both areas.     

Altimeter assimilation in the OCCAM global model: Part I: A twin experiment

An altimeter data assimilation scheme has been tested in the OCCAM (Ocean Circulation and Climate Advanced Modelling) global 1/4°, 36-level model using a twin experiment format. The Cooper and Haines displacement scheme is used. The method works well in most regions and depths. Currents and densities in the top 1000 m generally improve by over 50–70% after 5 months of sea level assimilation every 15 days. Below 1000 m, an error reduction of up to 50% is achieved. The errors remain low during a further 60-day run without assimilation. Diagnostics for the North Atlantic, the Tropical Pacific and the Antarctic Circumpolar Current are shown alongside the global averages.The main problems encountered were in weakly stratified regions of the Antarctic and Arctic seas. A scale selective filter is developed to avoid assimilating scales much larger than the local deformation radius, and this avoids the adverse assimilation effects in the southern oceans. A companion paper uses this scheme to assimilate TOPEX and ERS-1 altimeter maps.     

Data assimilation into a Princeton Ocean Model of the Mediterranean Sea using advanced Kalman filters

This study investigates the effectiveness of the Singular Evolutive Extended Kalman filter (SEEK) and its variants (SEIK and SFEK filters) for data assimilation into a Princeton Ocean Model (POM) of the Mediterranean Sea. The SEEK filters are sub-optimal Kalman filters based on the approximation of the filter's error covariance matrices by singular low-rank matrices, reducing in this way extensive computational burden. At the initialization, the filters error covariance matrix is parameterized by a set of multivariate empirical orthogonal functions (EOFs) which describe the dominant modes of the system's variability. The Mediterranean model is implemented on a 1/4° × 1/4° horizontal grid with 25 sigma levels and is forced with 6-hour ECMWF re-analysis atmospheric data. Several twin experiments, in which pseudo-observations of altimetric data and/or data profiles were assimilated, were first performed to evaluate the filters performances and to study their sensitivities to different parameters and setups. The results of these experiments were very encouraging and helped in setting up an effective configuration for the assimilation of real data in near-real time situation. In the hindcast experiments, Topex/Poseidon and ERS weekly sea level anomaly data were first assimilated during 1993 and the filters solution was evaluated against independent Reynolds sea surface temperature (SST) analysis. The assimilation system was able to significantly enhance the consistency between the model and the assimilated data, although the improvement with respect to independent SST data was significantly less pronounced. The model SST was only improved after including SST data in the assimilation system.     

A generalized model of pelagic biogeochemistry for the global ocean ecosystem. Part II: Numerical simulations

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.     

Description of a flexible and extendable physical–biogeochemical model system for the water column

A modelling system for coupled physical–biogeochemical simulations in the water column is presented here. The physical model component allows for a number of different statistical turbulence closure schemes, ranging from simple algebraic closures to two-equation turbulence models with algebraic second-moment closures. The biogeochemical module consists of models which are based on a number of state variables represented by their ensemble averaged concentrations. Specific biogeochemical models may range from simple NPZ (nutrient–phytoplankton–zooplankton) to complex ecosystem models. Recently developed modified Patankar solvers for ordinary differential equations allow for stable discretisations of the production and destruction terms guaranteeing conservative and non-negative solutions. The increased stability of these new solvers over explicit solvers is demonstrated for a plankton spring bloom simulation. The model system is applied to marine ecosystem dynamics the Northern North Sea and the Central Gotland Sea. Two different biogeochemical models are applied, a conservative nitrogen-based model to the North Sea, and a more complex model including an oxygen equation to the Baltic Sea, allowing for the reproduction of chemical processes under anoxic conditions. For both applications, earlier model results obtained with slightly different model setups could be basically reproduced. It became however clear that the choice for ecosystem model parameters such as maximum phytoplankton growth rates does strongly depend on the physical model parameters (such as turbulence closure models or external forcing).     

Assimilation of SeaWiFS ocean chlorophyll data into a three-dimensional global ocean model

Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll data were assimilated with an established three-dimensional global ocean model. The assimilation improved estimates of chlorophyll relative to a free-run (no assimilation) model. Compared to SeaWiFS, annual bias of the assimilation model was 5.5%, with an uncertainty of 10.1%. The free-run model had a bias of 21.0% and an uncertainty of 65.3%. In situ data were compared to the assimilation model over a 6-year time period from 1998 through 2003, indicating a bias of 0.1%, and an uncertainty of 33.4% for daily coincident, co-located data. SeaWiFS bias was slightly higher at − 1.3% and nearly identical uncertainty at 32.7%. The free-run bias and uncertainty at − 1.4% and 61.8%, respectively, indicated how much the assimilation improved model results. Annual primary production estimates for the 1998–2003 period produced a nearly 50% improvement by the assimilation model over the free-run model as compared to a widely used algorithm using SeaWiFS chlorophyll data. These results suggest the potential of assimilation of satellite ocean chlorophyll data for improving model results.     

Concentration of floating biogenic material in convergence zones

Some organisms that live just below the sea surface (the neuston) are known more as a matter of curiosity than as critical players in biogeochemical cycles. The hypothesis of this work is that their existence implies that they receive some food from an upward flux of organic matter. The behaviour of these organisms and of the associated organic matter, hereafter mentioned as floating biogenic material (FBM) is explored using a global physical–biogeochemical coupled model, in which its generation is fixed to 1% of primary production, and decay rate is of the order of 1 month. The model shows that the distribution of FBM should depart rapidly from that of primary production, and be more sensitive to circulation patterns than to the distribution of primary production. It is trapped in convergence areas, where it reaches concentrations larger by a factor 10 than in divergences, thus enhancing and inverting the contrast between high and low primary productivity areas. Attention is called on the need to better understand the biogeochemical processes in the first meter of the ocean, as they may impact the distribution of food for fishes, as well as the conditions for air–sea exchange and for the interpretation of sea color.     

Application of a SEEK filter to a 1D biogeochemical model of the Ligurian Sea: Twin experiments and real in-situ data assimilation

The Singular Evolutive Extended Kalman (SEEK) filter has been implemented to assimilate in-situ data in a 1D coupled physical-ecosystem model of the Ligurian Sea. The biogeochemical model describes the partly decoupled nitrogen and carbon cycles of the pelagic food web. The GHER hydrodynamic model (1D version) is used to represent the physical forcings. The data assimilation scheme (SEEK filter) parameterizes the error statistics by means of a set of empirical orthogonal functions (EOFs). Twin experiments are first performed with the aim to choose the suitable experimental protocol (observation and estimation vectors, number of EOFs, frequency of the assimilation,…) and to assess the SEEK filter performances. This protocol is then applied to perform real data assimilation experiments using the DYFAMED data base. By assimilating phytoplankton observations, the method has allowed to improve not only the representation of the phytoplankton community, but also of other variables such as zooplankton and bacteria that evolve with model dynamics and that are not corrected by the data assimilation scheme. The validation of the assimilation method and the improvement of model results are studied by means of suitable error measurements.     

The winter St. Helena climate index and extreme Benguela upwelling

Climate changes in the subtropical South-east Atlantic turn out to be well described by the St. Helena Island Climate Index (HIX) and observed fluctuations are in good agreement with inter-decadal variability of the entire South Atlantic Ocean. Year-to-year variations of the averaged austral winter HIX (July–September), representative of the main upwelling season, were compared with (i) corresponding averages of the geostrophic alongshore component of the south-east trade wind (SET) between St. Helena Island in the south-west and Luanda/Angola in the north-east, (ii) the meridional distribution of surface waters colder than 13 °C to characterise intense Benguela upwelling (IBU), and (iii) the meridional position of the Angola-Benguela Frontal Zone (ABFZ) determined by means of sea surface temperature images for offshore distances between 50 and 400 km. Temporal changes of these parameters were investigated and showed that the frequency of consecutive years of strong and relaxed Benguela upwelling is characterised by a quasi-cycle of about 11–14 years. It is proposed that the index of the winter HIX may be used as a ‘surveyor’s rod' to describe interannual changes in the Benguela upwelling regime as well as those of the embedded marine ecosystem.     

1/32° real-time global ocean prediction and value-added over 1/16° resolution

A 1/32° global ocean nowcast/forecast system has been developed by the Naval Research Laboratory at the Stennis Space Center. It started running at the Naval Oceanographic Office in near real-time on 1 Nov. 2003 and has been running daily in real-time since 1 Mar. 2005. It became an operational system on 6 March 2006, replacing the existing 1/16° system which ceased operation on 12 March 2006. Both systems use the NRL Layered Ocean Model (NLOM) with assimilation of sea surface height from satellite altimeters and sea surface temperature from multi-channel satellite infrared radiometers. Real-time and archived results are available online at http://www.ocean.nrlssc.navy.mil/global_nlom. The 1/32° system has improvements over the earlier system that can be grouped into two categories: (1) better resolution and representation of dynamical processes and (2) design modifications. The design modifications are the result of accrued knowledge since the development of the earlier 1/16° system. The improved horizontal resolution of the 1/32° system has significant dynamical benefits which increase the ability of the model to accurately nowcast and skillfully forecast. At the finer resolution, current pathways and their transports become more accurate, the sea surface height (SSH) variability increases and becomes more realistic and even the global ocean circulation experiences some changes (including inter-basin exchange). These improvements make the 1/32° system a better dynamical interpolator of assimilated satellite altimeter track data, using a one-day model forecast as the first guess. The result is quantitatively more accurate nowcasts, as is illustrated by several model-data comparisons. Based on comparisons with ocean color imagery in the northwestern Arabian Sea and the Gulf of Oman, the 1/32° system has even demonstrated the ability to map small eddies, 25–75 km in diameter, with 70% reliability and a median eddy center location error of 22.5 km, a surprising and unanticipated result from assimilation of altimeter track data. For all of the eddies (50% small eddies), the reliability was 80% and the median eddy center location error was 29 km. The 1/32° system also exhibits improved forecast skill in relation to the 1/16° system. This is due to (a) a more accurate initial condition for the forecast and (b) better resolution and representation of critical dynamical processes (such as upper ocean – topographic coupling via mesoscale flow instabilities) which allow the model to more accurately evolve these features in time while running in forecast mode (forecast atmospheric forcing for the first 5 days, then gradually reverting toward climatology for the remainder of the 30-day forecast period). At 1/32° resolution, forecast SSH generally compares better with unassimilated observations and the anomaly correlation of the forecast SSH exceeds that from persistence by a larger amount than found in the 1/16° system.     

Validation of the 3D biogeochemical model MIRO&CO with field nutrient and phytoplankton data and MERIS-derived surface chlorophyll a images

This paper presents results obtained with MIRO&CO-3D, a biogeochemical model dedicated to the study of eutrophication and applied to the Channel and Southern Bight of the North Sea (48.5°N–52.5°N). The model results from coupling of the COHERENS-3D hydrodynamic model and the biogeochemical model MIRO, which was previously calibrated in a multi-box implementation. MIRO&CO-3D is run to simulate the annual cycle of inorganic and organic carbon and nutrients (nitrogen, phosphorus and silica), phytoplankton (diatoms, nanoflagellates and Phaeocystis), bacteria and zooplankton (microzooplankton and copepods) with realistic forcing (meteorological conditions and river loads) for the period 1991–2003. Model validation is first shown by comparing time series of model concentrations of nutrients, chlorophyll a, diatom and Phaeocystis with in situ data from station 330 (51°26.00′N, 2°48.50′E) located in the centre of the Belgian coastal zone. This comparison shows the model's ability to represent the seasonal dynamics of nutrients and phytoplankton in Belgian waters. However the model fails to simulate correctly the dissolved silica cycle, especially during the beginning of spring, due to the late onset (in the model) of the early spring diatom bloom. As a general trend the chlorophyll a spring maximum is underestimated in simulations. A comparison between the seasonal average of surface winter nutrients and spring chlorophyll a concentrations simulated with in situ data for different stations is used to assess the accuracy of the simulated spatial distribution. At a seasonal scale, the spatial distribution of surface winter nutrients is in general well reproduced by the model with nevertheless a small overestimation for a few stations close to the Rhine/Meuse mouth and a tendency to underestimation in the coastal zone from Belgium to France. PO₄ was simulated best; silica was simulated with less success. Spring chlorophyll a concentration is in general underestimated by the model. The accuracy of the simulated phytoplankton spatial distribution is further evaluated by comparing simulated surface chlorophyll a with that derived from the satellite sensor MERIS for the year 2003. Reasonable agreement is found between simulated and satellite-derived regions of high chlorophyll a with nevertheless discrepancies close to the boundaries.     

Sequential data assimilation in an upwelling influenced estuary

We have evaluated the impact of assimilating chlorophyll, nitrate, phosphate, silicate and ammonium into a coupled 1D hydrodynamic ecosystem model (GOTM-ERSEM) in an upwelling influenced estuary. The assimilation method chosen is the Ensemble Kalman Filter (EnKF), which has been demonstrated to improve field estimates of key variables (chlorophyll, nutrients) for bulk algal bloom prediction. The 1D model has been set up for a central station inside the Ría de Vigo (Spain). Data from bi-weekly surveys are used to constrain the model. Temperature and salinity profiles are used to ensure the correct representation of the water structure through a relaxation scheme. Chlorophyll extracts and nutrients at three depths are assimilated sequentially during 1 year simulation (1991). The assimilation period includes episodes of active upwelling and downwelling. All five assimilated variables are successfully constrained and represent a large improvement on the reference simulation (without assimilation). Small divergences can be related to poorly resolved physical processes in the model. The assimilation was further evaluated by comparing observed biomass partitioning with model results. Diatoms accounted for the largest biomass update and the largest improvement in terms of percentage of variance explained (R²). This is particularly significant as they represent the 46% of the yearly integrated observed biomass of the planktonic autotrophs. Nonetheless the R² value was low for all phytoplankton groups. Bacteria and nanoflagellates showed an improvement with respect to their yearly Root Mean Square (RMS), while the other functional groups worsen or remained unaffected. Chlorophyll assimilation was responsible for most of the impact on the phytoplankton biomass with small contributions from the silicate. It had minor impact on the updates of nutrients which in turn corrected the state variables related to the detrital pool. In this current setting, combined assimilation of chlorophyll and nutrients is not sufficient to produce a skillful simulation of the phytoplankton succession.     

Improving assimilation of SeaWiFS data by the application of bias correction with a local SEIK filter

Ocean-biogeochemical models show typically significant errors in the representation of chlorophyll concentrations. The model state can be improved by the assimilation of satellite chlorophyll data with algorithms based on the Kalman filter. However, these algorithms do usually not account for the possibility that the model prediction contains systematic errors in the form of model bias. Accounting explicitly for model biases can improve the assimilation performance. To study the effect of bias estimation on the estimation of surface chlorophyll concentrations, chlorophyll data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) are assimilated on a daily basis into the NASA Ocean Biogeochemical Model (NOBM). The assimilation is performed by the ensemble-based SEIK filter combined with an online bias correction scheme. The SEIK filter is simplified here by the use of a static error covariance matrix. The performance of the filter algorithm is assessed by comparison with independent in situ data over the 7-year period 1998–2004. The bias correction results in significant improvements of the surface chlorophyll concentrations compared to the assimilation without bias estimation. With bias estimation, the daily surface chlorophyll estimates from the assimilation show about 3.3% lower error than SeaWiFS data. In contrast, the error in the global surface chlorophyll estimate without bias estimation is 10.9% larger than the error of SeaWiFS data.     

Appendicularian ecophysiology I: Food concentration dependent clearance rate, assimilation efficiency, growth and reproduction of Oikopleura dioica

Three aspects of the appendicularian O. dioica's ecophysiology were measured here: 1) morphological parameters over a wide range of appendicularian sizes, including mature animals in order to document the morphological characteristics inducing reproduction; 2) clearance rate and assimilation efficiency using feeding incubations with different algal concentrations and 3) the effect of food concentration on growth, mortality and reproduction.The relationship between the body carbon weight and the clearance rate follows a power function, with an exponent of 0.91 (± 0.07). The rate of particles retention increases with the food concentration following a Michaelis–Menten relationship (half-saturation constant = 151 ± 22 µg C l^− 1, maximum clearance rate = 12 ± 1 µg C µg C^− 1 d^− 1). The carbon assimilation efficiency decreases with the increasing food concentration. As a result, appendicularian growth which is limited in concentrations lower than 50 µg C l^− 1 is saturated above 100 µg C l^− 1.In immature animals the gonad represents less than 30% of the body volume whereas in mature individuals, its volume varies between 50% and 87% (mean 63%) suggesting that gonad/total volume ratio can be used as indicator of the maturation stages. The gonad weight in mature animals represents 70.3 (± 4.6)% of the total body carbon weight. Two major maturity stages can explain the changes in energy allocation: i) the somatic growth, when less energy is invested in gonad growth when compared to the rest of the body and ii) the maturation phase where most of the assimilated matter is invested in gonad maturation. This process is rapid, lasting only few hours. For this reason we measured completely mature organisms that are generally not measured during the experimental work with appendicularians. In food-limited conditions, the gonad maturation process starts with smaller individuals and ends with smaller reproductive animals having the same gonad to total volume ratio than in unlimited food conditions. The results obtained in this study were used to model the life cycle of O. dioica (see Lombard, F., Sciandra, A. and Gorsky, G., 2009-this volume. Appendicularian ecophysiology. II. Modeling nutrition, metabolism, growth and reproduction of the appendicularian Oikopleura dioica.).     

Impact of phytoplankton community size on a linked global ocean optical and ecosystem model

We isolated the effect phytoplankton cell size has on varying remote sensing reflectance spectra (R_rs(λ)) in the presence of optically active constituents by using optical and radiative transfer models linked in an offline diagnostic calculation to a global biogeochemical/ecosystem/circulation model with explicit phytoplankton size classes. Two case studies were carried out, each with several scenarios to isolate the effects of chlorophyll concentration, phytoplankton cell size, and size-varying phytoplankton absorption on R_rs(λ). The goal of the study was to determine the relative contribution of phytoplankton cell size and chlorophyll to overall R_rs(λ) and to understand where a standard band ratio algorithm (OC4) may under/overestimate chlorophyll due to R_rs(λ) being significantly affected by phytoplankton size. Phytoplankton cell size was found to contribute secondarily to R_rs(λ) variability and to amplify or dampen the seasonal cycle in R_rs(λ), driven by chlorophyll. Size and chlorophyll were found to change in phase at low to mid-latitudes, but were anti-correlated or poorly correlated at high latitudes. Phytoplankton size effects increased model calculated R_rs(443) in the subtropical ocean during local spring through early fall months in both hemispheres and decreased R_rs(443) in the Northern Hemisphere high latitude regions during local summer to fall months. This study attempts to tease apart when/where variability about the OC4 relationship may be associated with cell size variability. The OC4 algorithm may underestimate [Chl] when the fraction of microplankton is elevated, which occurs in the model simulations during local spring/summer months at high latitudes in both hemispheres.