Risultati finali
Dual observation and modelling approach, based inversion of atmospheric observations and on the use of satellite data and ecosystem models.
Bottom up integration using MOSES/JULES and Spatial Data
Top down Methods based on the Inversion of Atmospheric Concentrations
Dual observation and modelling approach, based inversion of atmospheric observations and on the use of satellite data and ecosystem models
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Develop inverse models for the TEMS and the atmospheric transport model (ATM) use these within an offline Carbon Cycle Data Assimilation System (CCDAS), to adjust TEM parameters and prior flux estimates based on a 20-25 year simulation period.
Implement in an AGCM, using existing Numerical Weather Prediction (NWP) data assimilation system where possible to nudge internal model variables (e.g. respiring carbon) to optimally fit the observations.
Carry-out a prototype online CCDAS experiment to infer the European carbon balance from 1990 onwards.
Atmospheric CO2 data and remotely sensed biophysical parameters (WP1)
Improved TEMs and parameters based on model validation (WP2)
Initial carbon stores and model parameters based on 20th century land carbon balance (WP3).
P3).
FORWARD MODELLING
Dual observation and modelling approach, based inversion of atmospheric observations and on the use of satellite data and ecosystem models.
Bottom up integration using MOSES/JULES and Spatial Data
Top down Methods based on the Inversion of Atmospheric Concentrations
Dual observation and modelling approach, based inversion of atmospheric observations and on the use of satellite data and ecosystem models
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INVERSE MODELLING
Method: Use atmospheric transport model to infer CO2 sources and sinks most consistent with atmospheric CO2 measurements.
Advantages: a) Large-scale; b) Data based (transparency).
Disadvantages:
a) Uncertain (network too sparse);
b) not constrained by eco-physiological understanding;
c) net CO2 flux only (cannot isolate land management).
The Kyoto Protocol (and any subsequent agreements designed to curb global warming) will require monitoring of carbon emissions and uptake.
Modelling and measurement techniques have been developed which can estimate land-atmosphere exchange (i.e. Kyoto sinks) at various time and space scales.
A carbon data assimilation system is required to optimally combine these approaches and to make best use of future CO2 measurements from satellite.
CAMELS is a project on "Carbon Assimilation and Modelling of the European Land Surface" and primarily aims at producing best estimates and uncertainty bounds for the contemporary and historical land carbon sinks in Europe and elsewhere, isolating the effects of direct land-management.
CAMELS combine top-down and bottom up approaches. The assumption used in CAMELS is that the best way to spatially extrapolate the results from the flux measurements is not through fluxes, but through parameter values that describe the underlying processes in terrestrial ecosystem models. Within CAMELS these parameters are constrained by measurements on a suite of scales ranging from the laboratory to stand and global scales.
The Bayesian framework for inversion allows combining observational information with prior knowledge on parameters in a consistent way. Not only does the Bayesian approach provide the most likely parameter values, it also delivers uncertainty bounds on the parameters. Weakly constrained parameters are thus given an appropriate uncertainty range instead of being excluded a priori from the optimisation. The method is applied on global scale using satellite observed vegetation colour and atmospheric carbon dioxide (Kaminski et al. 2002, Rayner et al., 2004) and on the stand scale, i.e. using flux measurements as observational constraint (Knorr and Kattge, 2004).
The parameter values optimised on the stand scale are used as a priori values in a global carbon Cycle Data Assimilation System (CCDAS). CAMELS has so far produced one prototype CCDAS based on the ecosystem model BETHY: in a first data assimilation step, BETHY takes satellite-observed values of "greenness" to optimise parameters related to water status, phenology, and total plant cover. Next, observed atmospheric carbon dioxide provided by the GLOBALVIEW sampling network is used to constrain 58 parameters in the physiological and energy-balance parts of BETHY (carbon-BETHY). The latter assimilation step uses an efficient variational approach, based on the adjoint (the first derivative of the code with respect to model parameters) of carbon-BETHY coupled to the atmospheric transport model TM2. Uncertainties of optimised model parameters are derived from the Hessian (the second derivative of the carbon-BETHY code with respect to the parameters). These parameter uncertainties, that reflect both the prior information (in a Bayesian context) as well as the large-scale information from the atmospheric carbon dioxide are finally translated to uncertainty bounds for CO2 fluxes and any other model diagnostic by means of the Jacobian of the carbon-BETHY code. All derivative code (adjoint, Hessian, and Jacobian) is generated automatically by FastOpt's compiler tool TAF. Automatic generation ensures that improvements of BETHY can be used in the assimilation scheme without delay.
First output of CCDAS using 20 years of atmospheric CO2 observations obtains a considerable reduction in uncertainty for about 12 of the 58 parameters that enter the optimisation. Results derived from the optimised carbon-BETHY, while still somewhat preliminary, clearly show that interannual fluctuations of terrestrial CO2 fluxes are dominated by the El Nino-Southern Oscillation (ENSO) cycle, except for the time after the Pinatubo eruption (Scholze, 2003). During El Nino (warm) pacific conditions, large parts of the tropical ecosystem come under water stress with reduced photosynthesis. The spatial distribution of the long-term mean net flux of CO2 shows a relatively large uptake over the northern hemisphere continents, and uptake over the tropical continents, which partly balances the large background source from land use change. In general the uncertainties are relatively low compared to equivalent uncertainties from direct inversions. Still, high uncertainties are found in tropical America and Africa, mainly due to the lack of observation stations in that areas. Summarizing the results for different regions, we find a terrestrial sink for Europe (excl. Russia) that is around a third of the fossil fuel emissions of the area, but with uncertainty bounds of the same size as the fluxes themselves. The country analysed that has the largest uncertainty in terrestrial CO2 fluxes is Brazil.
Building on the experience gained with CCDAS, CAMELS is currently working on a series of historical ecosystem model simulations that span the entire 20th century and that include further processes, such as land management, nitrogen deposition, and fire.
The final aim is to present a concept for an operational system that is capable to optimally combine all relevant large-scale observations to deliver the best possible estimates of European and global CO2 fluxes on a routine basis. Further information about CAMELS is available form http://www.bgc-jena.mpg.de/public/carboeur/projects/camels.htm; for CCDAS please check the website http://www.ccdas.org.
CAMELS uses a novel approach, termed Carbon Cycle Data Assimilation System (CCDAS) that combines both views and adds a few additional elements. An additional innovation is that CAMELS produces consistent uncertainty bounds on carbon fluxes that are essential for policy purposes. It starts from flux measurements at the stand scale, which are used to improve and best parameterise a number of ecosystem models. The exercise also yields uncertainty bounds for ecosystem model parameters, and, by using data from all major biomes, a notion of the representativeness of the models and parameterisations.
The assumption used in CAMELS is that the best way to spatially extrapolate the results from the flux measurements is not through fluxes, but through parameter values that describe the underlying processes. Hence, the parameter values optimised from the site data are used as a priori values in a global carbon cycle data assimilation system (CCDAS). CAMELS has so far produced one prototype CCDAS based on the ecosystem model BETHY: in a first data assimilation step, BETHY takes satellite-observed values of "greenness" to optimise parameters related to water status, phenology, and total plant cover. Next, the adjoint (the first derivative of the code with respect to model parameters) of the physiological and energy balance part of BETHY coupled with the adjoint of the atmospheric transport model TM2 is used to optimise parameter values of BETHY.
This is done by assimilation of atmospheric CO2 concentration measurements. Uncertainties of optimised model parameters can be derived from the Hessian (the second derivative) of the BETHY code with respect to the parameters. By using the Hessian of the BETHY code with respect to the parameters, uncertainties of optimised model parameters can also be derived. These uncertainties, that reflect both the prior information (in a Bayesian context), as well as the information from the large-scale inversion, can finally be translated into uncertainty bounds for CO2 fluxes and any other model diagnostic. Both the adjoint and Hessian codes are generated automatically using the compiler tool TAF, developed by FastOpt. Automatic generation ensures that improvements of BETHY can be used in the assimilation scheme without delay.
A spatially explicit, global-scale dataset of crop and pasture area for each year from 1700-1900 was constructed by merging, interpolating and reconciling two independent source datasets (Klein Goldewijk 2001, Ramankutty and Foley 1999). These data may be used as input to Terrestrrial Ecosystem Models, which require anthropogenic disturbance as a forcing.
The construction of annual pasture fraction datasets based on KG required interpolation and a number of assumptions regarding fractional coverage and the exact nature of grazing land. WRT the latter it is important to know its history as that determines to a large extend the (soil) carbon pool: is it intensively grazed land converted from either natural grassland or forest, or is it natural grassland. In the absence of more precise information, datasets of the fractional coverage of pasture at years other than 1700, 1750, 1800, 1850, 1900, 1950, 1970 and 1990 were obtained by simple linear interpolation between those dates.
In many grid squares it was necessary to deal with the dual presence of both pasture from KG and crops from RF, as a result of which a grid square could contain a pasture fraction of 1.0 and also a non-zero crop fraction, giving a total "disturbed fraction" greater than 1.0. The crop and/or pasture fractions are therefore adjusted in order to avoid total disturbed fractions of more than 1.0. 0.
The final datasets provide fractional coverage of crops and pastures at 0.5 resolution, each year from 1700 to 1990.
Significant progress has been made during the last twenty years in describing land-atmosphere fluxes of momentum, heat and vapour in climate and weather forecasting models. More recently, with interest in functioning of the global carbon cycle, such models have been enhanced to include CO2 fluxes, and are utilised at spatial scales appropriate to coupling within Global Circulation Models (GCMs). Central to most land-surface schemes is application of the Penman-Monteith energy combination equation for single leaves (Monteith, 1981), a description of the dependence of stomatal opening on environmental conditions, and an integration algorithm for scaling from leaf to canopy level.
Despite their more recent and novel uses, a fundamental requirement for land-surface models is that they can replicate fluxes measured at single points. In most cases, this involves comparison against data from eddy-covariance towers, using simultaneous weather measurements to drive the surface model. Unfortunately, it is frequently found in such studies that predictions of Net Ecosystem Productivity (NEP) saturate too rapidly during the diurnal cycle, and there is a growing consensus that this might be in part due to leaf-to-canopy scalings that are too simplistic. To address this, new process descriptions are being developed to give land-surface models a more explicit canopy structure. Some multi-source models already exist (Shuttleworth and Wallace, 1985, Huntingford et al., 1995) but these have concentrated on internal canopy energy fluxes. Here we examine the impact of a more sophisticated treatment of canopy light-interception on the simulation of the diurnal cycle in NEP.
Online and ad hoc consultation to European Commission.
Camels project results were presented at several occasions during 2004. Noticeably the project progresses reached a series of potential end users from the scientific modelling community to policy oriented stakeholders and institutions.
In particular during 2004 two events can be reported as of significant importance:
1. The workshop organized by the Global Carbon Project in collaboration with CarboEurope GHG concerted action with the title: Regional Carbon Budgets: from methodologies to quantification held in Beijing, China on 15-18 November 2004. The aim of workshop was to develop a common framework to improve comparability among different approaches and estimates of carbon stocks and fluxes based on their scope and system boundaries (constraints, time-space scales, etc.). Methods for integrating observational data for both stocks and stock changes (eg, inventory data, atmospheric gradient analyses) and fluxes (eg, flux tower networks) were discussed. CAMELS outline and strategy was presented as an example of integrated carbon data assimilation system.
2. The Conference of the Parties to UNFCC in Buenos Aires (COP10) where a side event on carbon research was organized by the EU Commission. Riccardo Valentini presented some initial results of CAMELS and its strategy. At the side event we had an outstanding participation of about 50-60 negotiators coming from several countries and representing both Parties delegation as well as international institutions such as World Bank, UNEP, GreenPeace etc.
It was an important opportunity to address the importance of Science in the current discussion of future Kyoto commitments and vulnerabilities of carbon cycle. The feed-back that we received was the need to develop more how carbon data assimilation systems could provide a backbone of monitoring of terrestrial carbon for understanding its vulnerabilities and the capacity of the terrestrial biosphere to adapt to changing climate. These were priorities for policy makers.
The Conference of the Parties to UNFCC in Montreal (COP11) where a side event on carbon research was organized by the EU Commission. Riccardo Valentini presented some initial results of CAMELS and its strategy. At the side event we had an outstanding participation of about 50-60 negotiators coming from several countries and representing both Parties delegation as well as international institutions such as World Bank, UNEP, GreenPeace etc. A CAMEL brochure is released at the meeting.
Dataset of fAPAR for Europe, and other remote sensing products (JRC) 1. A dedicated CAMELS web. page has been realized and posted on the http://fapar.jrc.it/ Web site: http://fapar.jrc.it/WWW/Data/Pages/FAPAR_Projects/FAPAR _Projects_CAMELS.php
The data related to the project can be downloaded from the data page which is a restricted page and accessible only for CAMELS partners. The package includes: the FAPAR products for 20 CAMELS sites listed in the Table 1 The remote sensing products were extracted from our original global data sets and processed to deliver a set of documentations and binary files containing site specific products. Years 2003 and 2004 have been added in 2005 to the former ones which covered the period from 1998 to 2002, only. European window for 1998, 1999 and 2000 products are also accessible. They include both 10-days and monthly composite FAPAR products with their associated remote sensing by-products.
The European window data were created and delivered on Hierarchical Data Format (HDF) format. 2. FAPAR Global products @ 0.5 x 0.5 degrees have been generated. FAPAR Global products were re-gridded @0.5x0.5 degrees in lat/lon and sinusoidal projection and published for years 1998 to 2004. 3. Additional software was developed and delivered to access and read global data. 4. Nadine Gobron participated in the fifth CAMELS meeting in JOENSUU, January 24, 2005. Datasets of FAPAR for Europe and other remote sensing products available for CAMELS were presented during this meeting.
The description of the computations involved in the derivation of FAPAR was presented as well as first results of the validation exercise. The results of application which has been achieved with FAPAR data concerning the drought impact on land surface over Europe in 2003 has been presented and published in: Gobron, N., B. Pinty, F. Melin, M. Taberner, M.M. Verstraete, A. Belward, T. Lavergne & J.-L. Widlowski (2005) The state of vegetation in Europe following the 2003 drought , International Journal of Remote Sensing Letters, Vol. 26, Number 9, 2013-2020. 5. Bernard Pinty and Nadine Gobron will participate to the last meeting in Spello in November 2005. Table 1: CAMELS Sites Site Plant Functional Type Latitude Longitude Aberdeldy, UK Temperate needle-leaved Evergreen 56.6037 -3.7773 Bondville, USA C4 crops 40.0061 -88.2918 Braschaat, Belgium Temperate Needle-leaved Evergreen 51.3091 4.5205 Castelporziano, Italy Temperate broad-leaved Evergreen 41.7058 12.3773 Flakaliden, Sweden Boreal Needle-leaved Deciduous 64.1127 19.4569 Gunnarsholt, Iceland Boreal Broad-leaved Deciduous 63.8333 -20.216667 Harvard, USA Temperate Broad-leaved Deciduous 42.5377 -72.1714 Hesse, France Temperate Broad-leaved Deciduous 48.6742 7.0646 Hyytalia ? 61.8474 24.2947 LeBray, France Temperate Needle-leaved Evergreen 44.7171 -0.7993 LittleWashita, USA C3 Grass 34.9604 -97.9788 Loobos, Nederlands Temperate broad-leaved Evergreen 52.1678 5.71396 Metolius, USA Temperate Needle-leaved Evergreen 44.4371 -121.5667 SkyOak ?? 33.2389 -116.458 Soroe, Denmark Temperate broad-leaved Evergreen 55.4869 11.6458 Tharandt, Germany Temperate Needle-leaved Evergreen 50.9636 13.5669 Upad, Alaska Tundra Vegetation 70.2813 -148.8847 Vielsam, Belgium Temperate Broad-leaved Deciduous 50.3088 5.9986 WalkerBranch, USA Temperate Broad-leaved Deciduous 35.9588 -84.287 Weidenbrunnen, Germany Temperate Needle-leaved Evergreen 50.3166 11.8833 ed Evergreen 50.3166 11.8833.
MAX
We inverted the parameters of the terrestrial ecosystem model BETHY against eddy covariance measurements of Net Ecosystem exchange of CO2 (NEE) and Latent heat (LE) flux at different sites considering a priori information about parameters in a Bayesian context. Based on the experience with the method and constrained a priori uncertainties, we analysed the robustness of the inversion of model parameters against eddy covariance measurements with respect to differences in phenology, data selection within a given year, the seasonal cycle and inter-annual variability for the Hainich site (Germany), a broadleaved deciduous forest.
The inversion was sensitive to the seasonal cycle and phenology, but rather insensitive to the selection of data within a given year as long as the selected data were not too few and almost equally distributed throughout the year. Also the inversion was insensitive to different years. A number of about 12 days of half-hourly data (1 day per month), carefully chosen to select days with high quality data, was sufficient to represent the average parameter set and to constrain parameter uncertainties. The posterior parameter-sets for different years derived from 12 days each were then quite similar. Two parameters were consistently driven out of their prior SE ranges: the basal soil respiration (Rhet0) and the soil water content at the permanent wilting point (SWC). A comparison of different sites showed quite large differences between sites, even of the same plant functional type. Thus it will be important to use a sufficient number of sites per plant functional type to characterize its average behaviour.
LSCE
We applied the same optimisation procedure to 14 different FluxNet sites from mid to high latitudes. These sites cover three major types of ecosystems: Deciduous broadleaf trees (4 sites), temperate conifers (6 sites), and boreal conifers (4 sites). For each site we were able to assimilate on average three years of observations. Most of the parameters are considered to be constant from one year to the next with the exception of the Vcmax, b, Q10 and Albedo parameters. Compared to the first case defined for the Bray site, we added few parameters controlling essentially the phenology and the assimilation of each type of ecosystem within the ORCHIDEE model (beginning and end of the growing season, critical leaf age and temperature dependency of the carboxylation rates).
We also built a cost function integrating both seasonal and diurnal information of the data. The optimised model outputs appear to be significantly closer to the observations than the prior model outputs, for most sites. Figure 4 illustrates the NEE model data fits for one site of the three different ecosystems. The amplitude of the seasonal cycle is modified in each case to reproduce the observed amplitude each year and the phase of the seasonal cycle is also adjusted to match the observed growing season length. Nevertheless, we are still missing some synoptic events especially during the summer. These events are usually associated to drought or rainy periods and the rather simplified soil hydrology in ORCHIDEE (double bucket model) is not able to properly reproduce the water stress and its effect on the NEE or LE fluxes on a synoptic time scale. If we consider the monthly mean diurnal cycles, the optimisation also succeed to improve the model data fit and especially to increase the CO2 uptake during the day according to the observations. However the changes of the diurnal cycle amplitude between spring, summer and autumn is still not perfectly modelled.
MET OFFICE
The best fit of model is determined by selecting the highest percentage of variance explained (PVE) from multiple simulation using 105 sets of parameter combinations. The standard set of parameters, optimised set of parameters and their literature range are given in table 1. The optimised parameters fit the model well and the fitness improved from 32.07 to 60.12 for broad leaf trees, 31.88 to 45.65 for Needle leaf tree, 8.45 to 15.45 for C3 grasses, 35.46 to 58.46 for C4 grasses and 38.18 to 51.12 for shrubs. Of five parameters used in the optimisation exercise, the leaf nitrogen (nl0) is most sensitive and constrained well with the observations. The quantum efficiency parameter (a ) is sensitive to day time fluxes that night time fluxes. The co variation of the parameters is studied showed that the critical moisture content and critical humidity deficit are correlated. Inverting the model parameters against eddy covariance data has shown that the optimised parameters fits the observations better compared to using standard set of parameters.
We inverted the parameters of the terrestrial ecosystem model BETHY against eddy covariance measurements of Net Ecosystem exchange of CO2 (NEE) and Latent heat (LE) flux at different sites considering a priori information about parameters in a Bayesian context.
Based on the experience with the method and constrained a priori uncertainties, we analysed the robustness of the inversion of model parameters against eddy covariance measurements with respect to differences in phenology, data selection within a given year, the seasonal cycle and inter-annual variability for the Hainich site (Germany), a broadleaved deciduous forest. The inversion was sensitive to the seasonal cycle and phenology, but rather insensitive to the selection of data within a given year as long as the selected data were not too few and almost equally distributed throughout the year. Also the inversion was insensitive to different years. A number of about 12 days of half-hourly data (1 day per month), carefully chosen to select days with high quality data, was sufficient to represent the average parameter set and to constrain parameter uncertainties. The posterior parameter-sets for different years derived from 12 days each were then quite similar. Two parameters were consistently driven out of their prior SE ranges: the basal soil respiration (Rhet0) and the soil water content at the permanent wilting point (SWC).
A comparison of different sites showed quite large differences between sites, even of the same plant functional type. Thus it will be important to use a sufficient number of sites per plant functional type to characterize its average behaviour.
Studies based on observations of atmospheric CO2, remote sensing, and on carbon process models, have all indicated that vegetation activity in the Northern Hemisphere is increasing, and this leads to significant carbon sinks in these regions. A number of factors, such as fertilization effect of the increase in atmospheric CO2 concentration and nitrogen deposition, inter-annual climate variability, and lengthening growing season duration, have been supposed contributing to such increasing trends, but the main cause of these trends still remain uncertain (Schimel et al., 2001).
One of the primary objectives of CAMEL project is to improve our knowledge about the mechanisms of such increasing trends and recent carbon sinks. To achieve this goal, we use a terrestrial carbon cycle model ORCHIDEE forced by observed climate (Mitchell and Jones, 2005) and atmospheric CO2 variability to simulate terrestrial ecosystem carbon fluxes (NPP, HR and NEP) for the period from 1901 to 2002. Only modelling results from 1980 to 2002 were saved at every daily step to define timing of phenological events.
Project website with a layered structure is constructed. http://www.camels.org.uk Project website has following layers CAMELS -About Scientific Questions Scientific Objectives Innovation Project Work Plan Workpackages Partner Institutes Reports Peer Reviewed Papers Book Chapters Annual Reports Newsletters Presentations Workpackage Reports Miscellaneous Reports Services Request for data Registration Useful Links Events Meetings and Actions Forthcoming Events Contacts Contact US FAQ's
Project website with a layered structure is constructed.
http://www.camels.org.uk
Project website has following layers
CAMELS -About
Scientific Questions
Scientific Objectives
Innovation
Project Work Plan
Workpackages
Partner Institutes
Reports
Peer Reviewed Papers
Book Chapters
Annual Reports
Newsletters
Presentations
Workpackage Reports
Miscellaneous Reports
Services
Request for data
Registration
Useful Links
Events
Meetings and Actions
Forthcoming Events
Contacts
Contact US
FAQ's
The historical CO2 forcing is provided (following Rayner and Trudinger, CSIRO) as annual mean concentration taken from a spline fit to the ice core record from Law Dome Antarctica (Etheridge et al. 1996) and a combined atmospheric record from the South Pole and Mauna Loa records of the Scripps Institute of Oceanography (Keeling et al. 1995).
The atmospheric record is calculated as a weighted sum (0.75
The Kyoto Protocol to the United Nations Framework Convention on Climate Change (UNFCCC) allows parties to count forestry and other land-use carbon sinks within their accounted emissions of carbon dioxide (CO2).
CAMELS (Carbon Assimilation and Modelling of the European Land Surface) provides scientific advice to support this, by quantifying the contribution of European ecosystems and land use to changes in atmospheric CO2. For the first time, data from a variety of sources were brought together with state-of-the-art models to give a complete picture of the exchange of carbon between the atmosphere and the European land surface.
Computer models based on mathematical equations can be used to estimate processes of carbon exchange at every point across Europe, but these models cannot be perfect and their results are always therefore uncertain to some extent. By compiling extensive information from the forestry sector from nations across Europe, we have mapped the biomass of European forests and established that past afforestation of agricultural lands has caused a net accumulation of carbon in the The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) FAPAR is derived from remote sensing data which enables assessment and monitoring of land surfaces around the globe.
The eddy covariance technique is used to measure the net CO2 exchange between ecosystems and atmosphere. In Europe there are now more than 100 eddy covariance sites covering different land uses and climate conditions with 10 years of measurements. CAMELS initiated a standardization work to check the quality of the eddy covariance datasets. The results from CAMELS were included in the Carboeurope Integrated Project database.
Using eddy-covariance data from all major plant types indicates how well the models represent natural vegetation. The optimised parameter values can then be used as a priori values in the global Carbon Cycle Data Assimilation System (CCDAS) described later in this report. The ORCHIDEE model was used to simulate changes in the growing season and the portion of the year in which the ecosystems. The MOSES model (Met Office Surface Exchange Scheme) was used to simulate the sinks and sources of carbon over the global land surface. Taking observed and reconstructed changes in climate, CO2 concentrations and land use as inputs, MOSES simulated biological processes in the vegetation across the different continents and produced estimates of local uptake and release of carbon in response to the imposed environmental changes.
Thus CCDAS combines a top-down and bottom up approach. CCDAS has been developed by the CCDAS consortium, which consists of CAMELS participants plus external partners (see http://CCDAS.org). The first output of CCDAS using 20 years of atmospheric CO2 observations obtains a considerable reduction in uncertainty for about 10-15 parameters that enter the optimisation. CO2 fluxes derived with the optimised BETHY show a clear relation to the El Nino-Southern Oscillation (ENSO) cycle, except for the time after the Pinatubo eruption. During El Nino (warm) conditions in the east Pacific, large parts of the tropical ecosystem come under water stress with reduced photosynthesis.
The spatial distribution of the long-term mean net flux of CO2 shows a relatively large uptake over the northern hemisphere continents, and uptake over the tropical continents, which partly balances the large background source from land use change.
Project website: http://www.camels.org.uk
Forest inventory data: http://www.efi.fi
FAPAR from remote sensing: http://fapar.jrc.it/
CO2 fluxes from eddy-covariance measurements: http://gaia.agraria.unitus.it/database
Carbon Cycle Data Assimilation System: http://www.ccdas.org
http://www.fastopt.com
Email: camels@metoffice.gov.uk
The latest estimates on European land carbon sinks are published in Janssens et al. (2003) and Nabuurs et al. (2003). These studies are based on (historic) forest inventory data, agricultural production data and models to convert these data to estimates of carbon stocks and fluxes. Figure 3.4 shows the evolution of the European forest sector carbon sink over the period 1950-1999. The increasing sink strength must be attributed to an increase in net annual increment of the forest since the 1960's and a more or less stable harvesting rate. The increase in increment is probably influenced by a complex of factors: changes in the age class distribution of the forest, increased nitrogren deposition and changes in forest management.
The study presents analysis of carbon cycle over last century. Anthropogenic land cover changes during the last millennium played an important and complex role in climate change. The MOSES model (Met Office Surface Exchange Scheme) was used to simulate the sinks and sources of carbon over the global land surfaces. Taking observed and reconstructed changes in climate, CO2 concentrations and land use as inputs, MOSES simulated biological processes in the vegetation across the different continents and produced estimates of local uptakes and release of carbon in response to the imposed environmental changes. The temporal pattern of net carbon exchange simulated by the models is primarily associated with the relative effects of rising of CO2 and land use changes. The global releases associated with land use generally track the releases simulated by the bookkeeping models of Haughton [2003] and where there is variation in the magnitude of increase. In Summary, the results presented here are consistent with the atmospheric data and provide a partitioning of total terrestrial carbon exchange. It has shown that the carbon exchange at the tropical regions compensated by carbon storage at high latitudes.
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