For non-expert users

An explanation of the project for non-expert users


1. General Introduction

CARBONES is a scientific project financed by the European Commission through the 7th Research and Development Framework Programme. Its goal is to provide state-of-the-art carbon flux/pools reanalysis that can be used by scientists and policy makers working in the field of carbon-cycle modelling and global warming. To allow the dissemination of the CARBONES results to a wider public, the objective of this document is to give an overview of the CARBONES goals and major results to non-expert users.


2. Presentation of the Scientific Context

  • The measurements made by scientists over the last few decades indicate that the concentrations of several of the so-called greenhouse gases have increased considerably since the preindustrial times. CO2 has increased by 30%, N2O by 20% and CH4 by 300%. These gases participate in a phenomenon called greenhouse warming in which molecules absorb thermal energy emitted by the surface and reradiate it at a lower temperature. As a result, part of the energy is trapped in the atmosphere, which leads to an increase in temperature. This natural phenomenon is accentuated as a result of human activities such as fossil fuel combustion and modifications of global vegetation through land-use change. It is now widely believed that human activities are the main driver of climate change, the effects of which are already seen through, for example, the increase in the global surface temperature over the last several decades (see figure below) or the shrinking of inland glaciers.


    CO2 concentrations (red curve) measured at the Mauna Loa Observatory (Hawaii, at 3397 m above sea level. The high frequency oscillations represent the annual cycle due to the vegetation uptake/release. The black curve shows the smoothed trend with the annual oscillations removed.


    Line plot of global mean land-ocean temperature index, from 1880 up to the present, with the base period 1951-1980. The dotted black line is the annual mean and the solid red line is the five-year mean. The green bars show uncertainty estimates. [This is an update of Fig. 1A inHansen et al. (2006).] Source: http://data.giss.nasa.gov/gistemp/graphs_v3/
  • In the context of a changing climate, it is necessary to quantify the major emissions and sinks of greenhouse gases and to understand the responses of the different ecosystems to changing conditions (land and ocean ecosystems). Such understanding will help scientists and policy makers in adopting the most appropriate solutions to mitigate the effect of climate change.
  • Over land, the present quantifications of CO2 sources and sinks, based on inventories of forest biomass (amount of carbon stocked in forests) and energy statistics (directly linked to emissions from fossil fuel burning), are too simple to correctly represent the carbon system. For example, they do not explain the observed atmospheric variability of CO2.
  • The three major components that control the contemporary carbon cycle are listed below. The exchanges between these systems are “rapid” compared to geological time scale and have an impact on the observed global warming.
    - the terrestrial biosphere that can stock large amounts of carbon in wood, leaves and soil, but with a strong climate dependency release in a relatively short time scale;
    - the ocean system, a much larger reservoir that stores on average one fourth of the anthropogenic emission of carbon;
    - the atmosphere, which transports greenhouse gases from source to sink regions. Due to a prolonged imbalance in sources and sinks, the concentrations of greenhouse gases in the atmosphere have increased, thus leading to climate change.
  • It is estimated that only half of the CO2 from anthropogenic emissions has remained in the atmosphere until now. The land and oceans have sequestered the other half.

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3. Objectives of the CARBONES project

  • The objective of the CARBONES project is to use most of the available measurements as well as state-of-the-art modelling tools to improve our knowledge about:
    - the stocks of carbon in living biomass and in soil;
    - the rapid exchanges of carbon (called fluxes) between the 3 components of the carbon system.
  • The scientists and engineers involved in the CARBONES project aim at providing a calibrated 20 year-long record of space and time variations of carbon fluxes and pools over the Earth. The record will be consistent with most available in-situ and satellite observations, as well as with the current understanding of the physical processes that drive the carbon cycle which are represented in a mathematical form in the models.

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4. Presentation of the methodology used in CARBONES

  • The estimations of CO2 fluxes and carbon stocks generated by CARBONES are based on numerical simulations that take into account available observations. Numerical models are important tools to the study the carbon cycle and in particular the fate of the carbon emitted by human activities. They help to integrate our physical knowledge about the different components of the carbon cycle: transport in the atmosphere, processes taking place in the surface-land biosphere, and CO2 exchanges between the ocean and the atmosphere. At the interface between models and observations is an activity called data assimilation. It is based on a mathematical methodology that allows model improvement by taking observations into account.
  • CARBONES uses three complex models that simulate the exchanges between the three components of the carbon system:
    - the terrestrial biosphere model (named ORCHIDEE) that simulates, among others, the exchanges of carbon between the global terrestrial vegetation (including soils) and the atmosphere:


    Schematic representation of different ecosystems for which exchanges of carbon are calculated in the ORCHIDEE model

    - a statistical ocean model (called OCVR) that calculates the exchange of CO2 between the ocean and the atmosphere;


    Ocean surface partial pressure of CO2 calculated by OCVR for January 2009.

    - the atmospheric transport model that transports CO2 in the atmosphere and provides for example the link between, on the one hand, the fluxes of CO2 from fossil combustion and biosphere and ocean models, and, on the other hand, the surface measurements of CO2 at remote measurement stations.

    Representation of vertical and horizontal grids of LMDZ. Colours represent simulated surface and air temperatures, arrows represent wind direction. © L. Fairhead (IPSL/LMD)
  • Data assimilation is a mathematical technique (based on a Bayesian theory) that allows the combination of information from observations and models to produce what is commonly called an analysis. An analysis thus represents information generated by an imperfect, but global model (modelled values are available for each element on a predefined grid),which has been improved by assimilating observations that are generally limited in space and time and which are characterised also by their own uncertainties.
  • In the CARBONES project, a so-called model parameter optimization is used. This means that it is not directly the fluxes that are improved, but instead the observations are used to update i) the empirical parameters used in the process-based ORCHIDEE model that simulates various processes related to the carbon cycle and ii) the statistical parameters of the ocean model. The whole system is thus improved: it provides at the same time the optimized fluxes for the defined period (1990-2010) but it can also be used to improve future forecasts of the carbon budget.
  • In what is called a 'forward model run', a first guess of ORCHIDEE parameters is used by the modelling system to simulate quantities that can be directly compared with the measurements (e.g. CO2 concentrations, vegetation activity, etc.). The variational assimilation technique used in CARBONES allows the improvement of the first guess on the parameters in such a way that the simulated quantities will be closer to observations.
  • In the CARBONES project, the objective is to 'assimilate' available measurements over the last 20 years in order to provide a coherent set of fluxes and stocks of carbon over this period.
  • A schematic representation of the Carbon Cycle Data Assimilation System (acronym: CCDAS) that is used to calculate the fluxes and stocks is depicted in the figure below. The system, indicated by the oval in the centre of the figure, uses input data indicated as rectangles. The output from the system consists of optimized fluxes of CO2, and stocks of carbon in soil and above-ground vegetation.

    Schematic representation of the CARBONES system that includes the modeling core (the oval) as well as different data/observations used for assimilation (improving the models), for forcing the models (e.g. winds for the atmospheric model) and evaluation.

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5. Observations used by CARBONES

  • The observations assimilated in CARBONES include several different types of data ranging from highly localised measurements of atmospheric CO2 concentrations and surface fluxes to observations derived from satellite measurements that represent an integral over an area ranging from a few to several hundred square kilometres.
  • As indicated by the diagram above, the input data were divided into three categories:
    - Data that are assimilated;
    - Data used for evaluation (used to validate the CARBONES products);
    - And forcing data (other data streams used in the CCDAS simulations). These data (e.g.: fossil fuel)are considered as inputs and their uncertainty is neglected.
  • Examples of the above datastreams include:
    - direct atmospheric measurement of CO2 in several key location over the globe;

    Atmospheric surface CO2 measurement stations used in the assimilation

    - local measurements of CO2, water, and energy fluxes between the atmosphere and a given ecosystem (mid-latitude broadleaf forest, savannah, etc.)

    Localization of the different flux measurement sites that were used in the CCDAS (www.fluxdata.org)

    - measurements of the partial pressure of CO2 in surface water, which give an indication of the exchange between the atmosphere and ocean surface;

    Spatial coverage of the pCO2 data used

    - estimations of the total biomass contained by a given ecosystem (such as a forest) and by soil. This data are used in the validation step;
    Global maps of growing stock in 2005, 1x1
    degree resolution.
    Soil Organic Carbon content: WISE5min version 1.0

    - measurements from space, which allow us to obtain information on the activity of the terrestrial vegetation;

    NDVI index for the period of Jan 1-Jan16, 2001, which is related to the photosynthetic capacity, source:http://modis-atmos.gsfc.nasa.gov/NDVI/browse.html. The index is measured from radiances recorded by the MODIS satellite.

    - anthropogenic emissions that are estimated from statistical data that are prepared by each country based on fuel consumption, etc.

    Spatial distribution of hourly fossil fuel emissions considering three different emission height classes for January 16, 2008 at 00 UTC.

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6. Presentation and visualization of the CARBONES products

  • The CARBONES products can be visualized with the help of the portal: www.carbones.eu, (using the Product drop down menu). Data can be explored with two different plotting tools:

    Tool to generate 2 D colour maps Natural Carbon Fluxes
    Monthly mean for January 1990
    Tool to generate regional time series  
  • The CARBONES visualization tool is presented in the following 2 videos:

    - Presentation of the mapping tool


    - Presentation of the regional time series tool

  • In addition to the videos, we provide here:
    - a brief description of the products (section 6.1);
    - a case study illustrating some features of the product (section 6.2) including some exercises for interested users!

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6.1 Presentation of the CARBONES products

  • Two general types of products can be displayed on the CARBONES portal:
    - fluxesof CO2,which can be either positive (carbon is emitted into the atmosphere) or negative (carbon is extracted from the atmosphere);
    - stocks, which represent the amount of carbon stocked in a given ecosystem. This estimate is important for example to quantify the impact on the carbon system of the re-growth of European forests (leading to a negative carbon flux) or the cutting of the Amazonian forests which leads in the long run to increasing atmospheric concentrations (burning or decomposition of wood and leaves - positive flux).
  • Three main categories of fluxes can be identified:
    - Fossil fuel emissions;
    - Ocean natural fluxes;
    - Land natural fluxes.
    • Land natural fluxes are further split into several categories:
      - natural fluxes which are further split based on:
      1. type of ecosystem (forest, grassland, croplands) and
      2. process linked to the flux:
      - photosynthesis: this is the familiar term linked to the chemical reaction in which CO2 and H20 react in the presence of energy from the sunlight to produce organic compounds such as sugars. This process is a net sink for atmospheric carbon and takes place in the presence of daylight.
      - respiration: includes both biomass decomposition (e.g. leaves) and the less well-known process in which plants use the energy stored in the stocked organic compounds. As a result, CO2 is released. This process is a net source of carbon and takes place both during day and night.
  • The units of the fluxes are kg of carbon per m2 per time period (day, month, year) considered.
  • Stocks of carbon are calculated only over land as the ocean stocks of carbon do not impact the atmosphere on the timescales considered by this project (two decades).
  • Over land, four reservoirs of carbon are considered:
    - Above ground biomass (biomass being defined here as biological material from living or recently living organisms): trees and other living or decomposing vegetation,
    - Below ground biomass: organic matter in soil,
    - Litter: decomposing organic matter,
    - Soil Organic Matter: fraction of below-ground biomass.
  • In addition, to estimate the activity of the vegetation, the notion of Leaf Area Index (LAI) is often used by scientists. It represents the total upper leaf surface of vegetation present over a considered area. Its units are m2 (of leaf surface)/m2 (of surface considered).
  • Carbon stock units : kgC / m2

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6.2 Zoom on selected CARBONES products

  • Ocean flux:
    - CO2 dissolves in water at the water-atmosphere interface. Depending on the partial pressure of CO2 in the air and in the surface layer of the water, oceans can be either sources (pCO2(aq)>pCO2(air)) or sinks (pCO2(aq)<pCO2(air)) of carbon. pCO2(air) depends on the sea surface pressure and the atmospheric concentration of CO2. pCO2(aq) is dependent mostly on the water temperature and also water salinity. Cold water has lower pCO2(aq) and can thus store more carbon. Similarly, sea water can store more carbon than fresh water. As a result of deep ocean circulation, which has a timescale of several thousand years, relatively carbon-poor water is continuously brought into contact with the atmosphere and the carbon-rich water sinks into the abysses of the ocean. In addition, carbon is absorbed by plankton, either as organic matter (vegetal plankton through photosynthesis) or as calcium carbonate (CaCO3), a fraction of which is buried by sedimentation. For these reasons, oceans have been in the past a constant sink for anthropogenic carbon emissions and have helped to reduce the increase in greenhouse gas concentrations in the atmosphere. However, oceans can locally degas CO2 as a result of, for example, the warming of surface waters.

    Question 1: With the help of the mapping tool and also the time series plotting tool, determine which of the three oceanic regions is a net source of CO2 to the atmosphere.
    a) Northern Ocean
    b) Southern Ocean
    c) Tropical Ocean

    Question 2: Demonstrate with the time series tool that the global ocean is a net sink. Then calculate the fraction of fossil emissions that are absorbed by the ocean.

    Answer 1: The tropical ocean as shown by the figures below.

    Answer 2: Plot the global ocean with the 1D time series tool. Fluxes are negative, which means that oceans, when averaged over all ocean basins, absorb CO2 from the atmosphere. The fossil fuel flux has increased from about 6 Gigatons Carbon/year to almost 9 Gigatons C/year (1 Gigaton of Carbon = 109 tons of carbon = 1012 kg of carbon). The global ocean uptake is about 1 to 1.5 Gtons C/year. Depending on the year, the oceans uptake about 15 to 25% of the CO2 emitted in a given year.

    Net Ocean Flux
    Yearly mean for 2000


  • Natural land fluxes:
    - These fluxes include the net exchange of CO2 between the natural land ecosystems and the atmosphere due to natural processes only. The flux is negative when the biosphere absorbs CO2 and positive when it releases CO2.

    Question 1: With the help of the 1-D plotting tool, plot the 3 hour values for a selected year for Europe and for Natural Carbon Fluxes. What is the reason for the high frequency oscillations in the fluxes?

    Question 2: Demonstrate that the net daily flux for Europe is positive during winter and negative during summer.

    Answer 1: The natural fluxes undergo a strong diurnal cycle. This cycle is due to the presence of two strong terms: photosynthesis (uptake of CO2 by vegetation) and respiration (release of CO2 either through decomposition of organic matter or through the use by plants of the energy stocked in organic compounds). Respiration is active during both day and night. As photosynthesis is active only during the day, a strong diurnal cycle is present with high uptake during the day (during the growing season) and net release of the accumulated carbon during the night.

    Answer 2: Plot the Natural Carbon Fluxes for Europe and for daily averages:
    Natural Carbon Fluxes
    Daily mean from1 January 1990 to 1 January 1991

    CARBONES('20-year re-analysis of CARBON fluxES and pools over Europe and the globe') is a project supported under the 7th Framework Programme (contract number 242316).


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