David Antoine

Bio: David Antoine is an academic researcher from Curtin University. The author has contributed to research in topics: Ocean color & SeaWiFS. The author has an hindex of 43, co-authored 122 publications receiving 8146 citations. Previous affiliations of David Antoine include University of Paris & Centre national de la recherche scientifique.

Oceanic primary production: 2. Estimation at global scale from satellite (Coastal Zone Color Scanner) chlorophyll

Abstract: A fast method has been proposed [Antoine and Morel, this issue] to compute the oceanic primary production from the upper ocean chlorophyll-like pigment concentration, as it can be routinely detected by a spaceborne ocean color sensor. This method is applied here to the monthly global maps of the photosynthetic pigments that were derived from the coastal zone color scanner (CZCS) data archive [Feldman et al., 1989]. The photosynthetically active radiation (PAR) field is computed from the astronomical constant and by using an atmospheric model, thereafter combined with averaged cloud information, derived from the International Satellite Cloud Climatology Project (ISCCP). The aim is to assess the seasonal evolution, as well as the spatial distribution of the photosynthetic carbon fixation within the world ocean and for a “climatological year”, to the extent that both the chlorophyll information and the cloud coverage statistics actually are averages obtained over several years. The computed global annual production actually ranges between 36.5 and 45.6 Gt C yr−1 according to the assumption which is made (0.8 or 1) about the ratio of active-to-total pigments (recall that chlorophyll and pheopigments are not radiometrically resolved by CZCS). The relative contributions to the global productivity of the various oceans and zonal belts are examined. By considering the hypotheses needed in such computations, the nature of the data used as inputs, and the results of the sensitivity studies, the global numbers have to be cautiously considered. Improving the reliability of the primary production estimates implies (1) new global data sets allowing a higher temporal resolution and a better coverage, (2) progress in the knowledge of physiological responses of phytoplankton and therefore refinements of the time and space dependent parameterizations of these responses.

A comparison of global estimates of marine primary production from ocean color

Abstract: The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 degrees C, and chlorophyll concentration exceeding 1 mg Chlm(-3). Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate. (c) 2006 Elsevier Ltd. All rights reserved.

Seasonal and interannual variability in algal biomass and primary production in the Mediterranean Sea, as derived from 4 years of SeaWiFS observations

Abstract: [1] Because the Mediterranean has been subject for several decades to increasing anthropogenic influences, monitoring algal biomass and primary production on a long-term basis is required to detect possible modifications in the biogeochemical equilibrium of the basin. This work was initiated thanks to a 4-year-long time series of SeaWiFS observations. Seasonal variations of algal biomass (estimated using a previously developed regional algorithm) and primary production were analyzed for the various regions, and compared with those estimated using the CZCS sensor (1978–1986). Also, interannual variations could be assessed for the first time. The seasonal cycles of algal biomass generally reveal a maximum in winter or spring, and a minimum in summer. Some conspicuous differences with CZCS observations (e.g., in the Northwest Basin, reduction of the deep convection zone, earlier start of the spring bloom, quasi-absence of the vernal bloom) likely result from environmental changes. Interannual variations in algal biomass are noticeable all over the basin, including in the very oligotrophic waters of the Eastern Basin. The seasonal evolution of primary production is predominantly influenced by that of algal biomass in the Western Basin (with, in particular, a spring maximum). In the Eastern Basin, the seasonal courses of PAR and biomass tend to compensate each other, and primary production varies weakly along the year. The annual values computed over the 1998–2001 period for the Western Basin (163 ± 7 gC m−2 yr−1) and the Eastern Basin (121 ± 5 gC m−2 yr−1) are lower (by 17 and 12%, respectively) than those previously derived (using the same light-photosynthesis model) from CZCS data.

Bidirectional reflectance of oceanic waters: accounting for Raman emission and varying particle scattering phase function

Abstract: The bidirectionality of the upward radiance field in oceanic case 1 waters has been reinvestigated by incorporation of revised parameterizations of inherent optical properties as a function of the chlorophyll concentration (Chl), considering Raman scattering and making the particle phase function shape (βp) continuously varying along with the Chl. Internal consistency is thus reached, as the decrease in backscattering probability (for increasing Chl) translates into a correlative change in βp. The single particle phase function (previously used) precluded a realistic assessment of bidirectionality for waters with Chl > 1 mg m-3. This limitation is now removed. For low Chl, Raman emissions significantly affect the radiance field. For moderate Chl (0.1–1 mg m-3), new and previous bidirectional parameters remain close. The ocean reflectance anisotropy has implications in ocean color remote-sensing problems, in derivation of coherent water-leaving radiances, in associated calibration–validation activities, and in the merging of data obtained under various geometrical configurations.

Generalized ocean color inversion model for retrieving marine inherent optical properties

Abstract: Ocean color measured from satellites provides daily, global estimates of marine inherent optical properties (IOPs). Semi-analytical algorithms (SAAs) provide one mechanism for inverting the color of the water observed by the satellite into IOPs. While numerous SAAs exist, most are similarly constructed and few are appropriately parameterized for all water masses for all seasons. To initiate community-wide discussion of these limitations, NASA organized two workshops that deconstructed SAAs to identify similarities and uniqueness and to progress toward consensus on a unified SAA. This effort resulted in the development of the generalized IOP (GIOP) model software that allows for the construction of different SAAs at runtime by selection from an assortment of model parameterizations. As such, GIOP permits isolation and evaluation of specific modeling assumptions, construction of SAAs, development of regionally tuned SAAs, and execution of ensemble inversion modeling. Working groups associated with the workshops proposed a preliminary default configuration for GIOP (GIOP-DC), with alternative model parameterizations and features defined for subsequent evaluation. In this paper, we: (1) describe the theoretical basis of GIOP; (2) present GIOP-DC and verify its comparable performance to other popular SAAs using both in situ and synthetic data sets; and, (3) quantify the sensitivities of their output to their parameterization. We use the latter to develop a hierarchical sensitivity of SAAs to various model parameterizations, to identify components of SAAs that merit focus in future research, and to provide material for discussion on algorithm uncertainties and future emsemble applications.

Primary Production of the Biosphere: Integrating Terrestrial and Oceanic Components

Abstract: Integrating conceptually similar models of the growth of marine and terrestrial primary producers yielded an estimated global net primary production (NPP) of 104.9 petagrams of carbon per year, with roughly equal contributions from land and oceans. Approaches based on satellite indices of absorbed solar radiation indicate marked heterogeneity in NPP for both land and oceans, reflecting the influence of physical and ecological processes. The spatial and temporal distributions of ocean NPP are consistent with primary limitation by light, nutrients, and temperature. On land, water limitation imposes additional constraints. On land and ocean, progressive changes in NPP can result in altered carbon storage, although contrasts in mechanisms of carbon storage and rates of organic matter turnover result in a range of relations between carbon storage and changes in NPP.

Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model

Abstract: The continued increase in the atmospheric concentration of carbon dioxide due to anthropogenic emissions is predicted to lead to significant changes in climate. About half of the current emissions are being absorbed by the ocean and by land ecosystems, but this absorption is sensitive to climate as well as to atmospheric carbon dioxide concentrations, creating a feedback loop. General circulation models have generally excluded the feedback between climate and the biosphere, using static vegetation distributions and CO2 concentrations from simple carbon-cycle models that do not include climate change. Here we present results from a fully coupled, three-dimensional carbon–climate model, indicating that carbon-cycle feedbacks could significantly accelerate climate change over the twenty-first century. We find that under a 'business as usual' scenario, the terrestrial biosphere acts as an overall carbon sink until about 2050, but turns into a source thereafter. By 2100, the ocean uptake rate of 5 Gt C yr-1 is balanced by the terrestrial carbon source, and atmospheric CO2 concentrations are 250 p.p.m.v. higher in our fully coupled simulation than in uncoupled carbon models, resulting in a global-mean warming of 5.5 K, as compared to 4 K without the carbon-cycle feedback.

Accelerating loss of seagrasses across the globe threatens coastal ecosystems

Abstract: Coastal ecosystems and the services they provide are adversely affected by a wide variety of human activities. In particular, seagrass meadows are negatively affected by impacts accruing from the billion or more people who live within 50 km of them. Seagrass meadows provide important ecosystem services, including an estimated $1.9 trillion per year in the form of nutrient cycling; an order of magnitude enhancement of coral reef fish productivity; a habitat for thousands of fish, bird, and invertebrate species; and a major food source for endangered dugong, manatee, and green turtle. Although individual impacts from coastal development, degraded water quality, and climate change have been documented, there has been no quantitative global assessment of seagrass loss until now. Our comprehensive global assessment of 215 studies found that seagrasses have been disappearing at a rate of 110 km(2) yr(-1) since 1980 and that 29% of the known areal extent has disappeared since seagrass areas were initially recorded in 1879. Furthermore, rates of decline have accelerated from a median of 0.9% yr(-1) before 1940 to 7% yr(-1) since 1990. Seagrass loss rates are comparable to those reported for mangroves, coral reefs, and tropical rainforests and place seagrass meadows among the most threatened ecosystems on earth.

Photosynthetic rates derived from satellite‐based chlorophyll concentration

Abstract: We assembled a dataset of 14C-based productivity measurements to understand the critical variables required for accurate assessment of daily depth-integrated phytoplankton carbon fixation (PP(PPeu)u) from measurements of sea surface pigment concentrations (Csat)(Csat). From this dataset, we developed a light-dependent, depth-resolved model for carbon fixation (VGPM) that partitions environmental factors affecting primary production into those that influence the relative vertical distribution of primary production (Pz)z) and those that control the optimal assimilation efficiency of the productivity profile (P(PBopt). The VGPM accounted for 79% of the observed variability in Pz and 86% of the variability in PPeu by using measured values of PBopt. Our results indicate that the accuracy of productivity algorithms in estimating PPeu is dependent primarily upon the ability to accurately represent variability in Pbopt. We developed a temperature-dependent Pbopt model that was used in conjunction with monthly climatological images of Csat sea surface temperature, and cloud-corrected estimates of surface irradiance to calculate a global annual phytoplankton carbon fixation (PPannu) rate of 43.5 Pg C yr‒1. The geographical distribution of PPannu was distinctly different than results from previous models. Our results illustrate the importance of focusing Pbopt model development on temporal and spatial, rather than the vertical, variability.

Ocean Color Chlorophyll Algorithms for SEAWIFS

Abstract: A large data set containing coincident in situ chlorophyll and remote sensing reflectance measurements was used to evaluate the accuracy, precision, and suitability of a wide variety of ocean color chlorophyll algorithms for use by SeaWiFS (Sea-viewing Wide Field-of-view Sensor). The radiance-chlorophyll data were assembled from various sources during the SeaWiFS Bio-optical Algorithm Mini-Workshop (SeaBAM) and is composed of 919 stations encompassing chlorophyll concentrations between 0.019 and 32.79 μg L−1. Most of the observations are from Case I nonpolar waters, and ∼20 observations are from more turbid coastal waters. A variety of statistical and graphical criteria were used to evaluate the performances of 2 semianalytic and 15 empirical chlorophyll/pigment algorithms subjected to the SeaBAM data. The empirical algorithms generally performed better than the semianalytic. Cubic polynomial formulations were generally superior to other kinds of equations. Empirical algorithms with increasing complexity (number of coefficients and wavebands), were calibrated to the SeaBAM data, and evaluated to illustrate the relative merits of different formulations. The ocean chlorophyll 2 algorithm (OC2), a modified cubic polynomial (MCP) function which uses Rrs490/Rrs555, well simulates the sigmoidal pattern evident between log-transformed radiance ratios and chlorophyll, and has been chosen as the at-launch SeaWiFS operational chlorophyll a algorithm. Improved performance was obtained using the ocean chlorophyll 4 algorithm (OC4), a four-band (443, 490, 510, 555 nm), maximum band ratio formulation. This maximum band ratio (MBR) is a new approach in empirical ocean color algorithms and has the potential advantage of maintaining the highest possible satellite sensor signal: noise ratio over a 3-orders-of-magnitude range in chlorophyll concentration.