ALBERT

Description: The El Niño Southern Oscillation (ENSO) drives important changes in the marine productivity of the Equatorial Pacific, in particular during major El Niño/La Niña transitions. Changes in environmental conditions associated with these climatic events also likely impact phytoplankton composition. In this work, the distribution of four major phytoplankton groups (nanoeucaryotes, Prochlorococcus, Synechococcus, and diatoms) was examined between 1996 and 2007 by applying the PHYSAT algorithm to the ocean color data archive from the Ocean Color and Temperature Sensor (OCTS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Coincident with the decrease in chlorophyll concentrations, a large-scale shift in the phytoplankton composition of the Equatorial Pacific, that was characterized by a decrease in Synechococcus and an increase in nanoeucaryotes dominance, was observed during the early stages of both the strong El Niño of 1997 and the moderate El Niño of 2006. A significant increase in diatoms dominance was observed in the Equatorial Pacific during the 1998 La Niña and was associated with elevated marine productivity. An analysis of the environmental variables using a coupled physical-biogeochemical model (NEMO-PISCES) suggests that the Synechococcus dominance decrease during the two El Niño events was associated with an abrupt decline in nutrient availability (−0.9 to −2.5 μM NO3 month−1). Alternatively, increased nutrient availability (3 μM NO3 month−1) during the 1998 La Niña resulted in Equatorial Pacific dominance diatom increase. Despite these phytoplankton community shifts, the mean composition is restored after a few months, which suggests resilience in community structure. Such rapid changes to the composition of phytoplankton groups should be considered in future modeling approaches to represent variability of the marine productivity in the Equatorial Pacific and to quantify its potential implications on food-web and on global carbon cycle.

Description: Dimethylsulfide (DMS) is biologically produced in the surface ocean and is the dominant natural source of sulfur to the atmosphere. Although DMS is an algal by-product, the ratio of DMS to chlorophyll (DMS:Chl) varies widely in the surface ocean. This is presumably because dimethylsulfoniopropionate (DMSP), the major precursor of DMS, DMSP-lyases, which catalyze the conversion of DMSP to DMS, and Chl vary as well with taxonomic composition than with the physiological state of the algal assemblage. Here we use remote sensing of Chl and phytoplankton dominance from PHYSAT with in-situ measured DMS concentrations to assess on an unprecedented spatial scale the affect of species composition on the DMS:Chl ratio in the surface ocean. Meridional distributions at 22° W in the Atlantic, and 95° W and 110° W in the Pacific, showed the same marked drop in DMS:Chl ratios near the equator, down to few mmol g−1, yet the basins exhibited different species dominance signatures. Hence, our results suggest that species composition was of secondary importance in controlling DMS and DMS:Chl variations in equatorial upwellings as well as physiological shifts in algal DMS production since mixed layer growth conditions (i.e., nutrient stress, temperature and light) were relatively homogeneous over the eastern equatorial Pacific. In the Indian sector of the Southern Ocean, warm core eddies with contrasting PHYSAT signatures displayed similar DMS levels. However, DMS:Chl ratios in eddies dominated by Synechococcus (SYN) were about 50% lower than that found in eddies showing nanoeucayotes or Phaeocystis-like signatures. DMS:Chl ratios varied with latitude in SYN dominated regions with ratios at low latitudes (away from equatorial upwellings) about twice that found at high northern and southern latitudes. This is the sole piece of coherent observations which indicates that species composition and growth conditions affect the large-scale dynamics of the DMS:Chl ratio. Overall, it appears that the DMS:Chl ratio is not consistent within specific phytoplankton groups determined from space. So DMS concentrations can not be derived from water-leaving radiance spectra obtained simultaneously from ocean color sensor measurements of Chl concentrations and dominant phytoplankton functional types. To proceed with the global investigation and better discriminate between factors affecting DMS:Chl ratios in the surface ocean, we recommend the use of PHYSAT records with higher spatial resolution in conjunction with other satellite products (e.g. particulate backscattering coefficients and indices of phytoplankton physiology and bloom status).

Description: A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The goal of this study is to identify the current state of carbon observations and needs for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion (by several orders of magnitude) of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over remote areas such as the southern oceans, tropical forests and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in-situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases inter-operable, and on the calibration of each component of the system to agreed-upon international scales.

Description: The Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard Meteosat Second Generation (MSG) launched in 2003 by EUMETSAT is dedicated to the Nowcasting applications and Numerical Weather Prediction and to provide information for climate monitoring and research. We use the data in visible and near infrared channels to derive the Aerosol Optical Thickness (AOT) over land. The algorithm is based on the assumption that the Top Of the Atmosphere (TOA) reflectance increases with the aerosol load. This is a reasonable assumption except in case of absorbing aerosols above bright surfaces. We assume that the minimum in a 14-day time series of the TOA reflectance is, once corrected from gaseous scattering and absorption, representative of the surface reflectance. The AOT and the aerosol model (a set of 5 models are used), are retrieved by matching the simulated TOA reflectance with the TOA reflectances measured by SEVIRI in its visible and Near Infra-Red (NIR) spectral bands. The high temporal resolution of the data acquisition by SEVIRI allows to retrieve the AOT every 15 min with a spatial resolution of 3km at sub-satellite point, over the whole SEVIRI disk which covers Europe, Africa and part of South America. The resulting AOT, a Level 2 product at the same temporal and spatial resolution than SEVIRI, is presented and evaluated in this paper. The AOT has been validated using ground based measurements from AERONET, a sun-photometer network, focusing over Europe for 3 months in 2006. The SEVIRI estimates correlate well with the AERONET measurements, r = 0.64, with a slight underestimate, bias = −0.017. The sources of errors are mainly the cloud contamination and the bad estimation of the surface reflectance. The temporal evolutions exhibited by both dataset show very good agreement which allows to conclude that the AOT Level 2 product from SEVIRI can be used to quantify the aerosol content and to monitor its daily evolution with a high temporal frequency. The comparison with daily maps of MODIS AOT level 3 product shows qualitative good agreements in the retrieved geographic patterns of AOT. Given the high spatial and temporal resolutions obtained with this approach, our results have clear potential for applications ranging from air quality monitoring to climate studies.

Description: The Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard Meteosat Second Generation (MSG) launched in 2003 by EUMETSAT is dedicated to the Nowcasting applications and Numerical Weather Prediction and to the provision of observations for climate monitoring and research. We use the data in visible and near infrared (NIR) channels to derive the aerosol optical thickness (AOT) over land. The algorithm is based on the assumption that the top of the atmosphere (TOA) reflectance increases with the aerosol load. This is a reasonable assumption except in case of absorbing aerosols above bright surfaces. We assume that the minimum in a 14-days time series of the TOA reflectance is, once corrected from gaseous scattering and absorption, representative of the surface reflectance. The AOT and the aerosol model (a set of 5 models is used), are retrieved by matching the simulated TOA reflectance with the TOA reflectances measured by SEVIRI in its visible and NIR spectral bands. The high temporal resolution of the data acquisition by SEVIRI allows to retrieve the AOT every 15 min with a spatial resolution of 3 km at sub-satellite point, over the entire SEVIRI disk covering Europe, Africa and part of South America. The resulting AOT, a level 2 product at the native temporal and spatial SEVIRI resolutions, is presented and evaluated in this paper. The AOT has been validated using ground based measurements from AErosol RObotic NETwork (AERONET), a sun-photometer network, focusing over Europe for 3 months in 2006. The SEVIRI estimates correlate well with the AERONET measurements, r = 0.64, with a slight overestimate, bias = −0.017. The sources of errors are mainly the cloud contamination and the bad estimation of the surface reflectance. The temporal evolutions exhibited by both datasets show very good agreement which allows to conclude that the AOT Level 2 product from SEVIRI can be used to quantify the aerosol content and to monitor its daily evolution with a high temporal frequency. The comparison with daily maps of Moderate Resolution Imaging Spectroradiometer (MODIS) AOT level 3 product shows qualitative good agreement in the retrieved geographic patterns of AOT. Given the high spatial and temporal resolutions obtained with this approach, our results have clear potential for applications ranging from air quality monitoring to climate studies. This paper presents a first evaluation and validation of the derived AOT over Europe in order to document the overall quality of a product that will be made publicly available to the users of the aforementioned research communities.

Description: The El Niño Southern Oscillation (ENSO) drives important changes in the marine productivity of the Equatorial Pacific, in particular during major El Niño/La Niña transitions. Changes in environmental conditions associated with these climatic events also likely impact phytoplankton composition. In this work, the distribution of four major phytoplankton groups (nanoeucaryotes, Prochlorococcus, Synechococcus, and diatoms) was examined between 1996 and 2007 by applying the PHYSAT algorithm to the ocean color data archive from the Ocean Color and Temperature Sensor (OCTS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Coincident with the decrease in chlorophyll concentrations, a large-scale shift in the phytoplankton composition of the Equatorial Pacific, that was characterized by a decrease in Synechococcus and an increase in nanoeucaryote dominance, was observed during the early stages of both the strong El Niño of 1997 and the moderate El Niño of 2006. A significant increase in diatoms dominance was observed in the Equatorial Pacific during the 1998 La Niña and was associated with elevated marine productivity. An analysis of the environmental variables using a coupled physical-biogeochemical model (NEMO-PISCES) suggests that the Synechococcus dominance decrease during the two El Niño events was associated with an abrupt decline in nutrient availability (−0.9 to −2.5 μM NO3 month−1). Alternatively, increased nutrient availability (3 μM NO3 month−1) during the 1998 La Niña resulted in Equatorial Pacific dominance diatom increase. Despite these phytoplankton community shifts, the mean composition is restored after a few months, which suggests resilience in community structure.

Description: A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales.

Description: Dimethylsulfoniopropionate (DMSP) is produced in surface seawater by phytoplankton. Phytoplankton culture experiments have shown that nanoeucaryotes (NANO) display much higher mean DMSP-to-Carbon or DMSP-to-Chlorophyll (Chl) ratios than Prochlorococcus (PRO), Synechococcus (SYN) or diatoms (DIAT). Moreover, the DMSP-lyase activity of algae which cleaves DMSP into dimethylsulfide (DMS) is even more group specific than DMSP itself. Ship-based observations have shown at limited spatial scales, that sea surface DMS-to-Chl ratios (DMS:Chl) are dependent on the composition of phytoplankton groups. Here we use satellite remote sensing of Chl (from SeaWiFS) and of Phytoplankton Group Dominance (PGD from PHYSAT) with ship-based sea surface DMS concentrations (8 cruises in total) to assess this dependence on an unprecedented spatial scale. PHYSAT provides PGD (either NANO, PRO, SYN, DIAT, Phaeocystis (PHAEO) or coccolithophores (COC)) in each satellite pixel (1/4° horizontal resolution). While there are identification errors in the PHYSAT method, it is important to note that these errors are lowest for NANO PGD which we typify by high DMSP:Chl. In summer, in the Indian sector of the Southern Ocean, we find that mean DMS:Chl associated with NANO + PHAEO and PRO + SYN + DIAT are 13.6±8.4 mmol g−1 (n=34) and 7.3±4.8 mmol g−1 (n=24), respectively. That is a statistically significant difference (P