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Authors: Paul Palmer, Mathew Williams and Shaun Quegan

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CFusion/NCEO Working Note
A UK research programme exploiting carbon dioxide measurements from the NASA Orbiting Carbon Conservatory (OCO) and the JAXA Greenhouse gas Observing SATellite (GOSAT)
Authors: Paul Palmer, Mathew Williams and Shaun Quegan.

1 Introduction

The twentieth century saw a rapid rise in atmospheric CO2 concentrations, due largely to anthropogenic activity. This trend is set to continue in the twenty-first century with increased emissions from deforestation, fossil fuel burning and cement manufacture due to increased global economic activity. The current century is likely to see a range of responses from land and ocean carbon pools to the associated climate warming (e.g., net release of carbon from peat reservoirs due to melting of permafrost). It is therefore critical to have a capability to monitor and quantitatively understand the rate of change in land and ocean carbon pools.

Observed variations in atmospheric CO2 concentrations measure the net surface-atmosphere exchange. Inferences on the surface fluxes giving rise to these concentrations currently rely on inversing models of atmospheric transport and mixing, combined with CO2 concentrations measured by the ground-based network. This ill-posed problem requires regularization, typically provided by prior CO­2 concentrations derived from estimates of surface CO2 fluxes inferred from in situ data, and has several problematic features: a) the sparseness of the data network, particularly over tropical landmasses; b) biases introduced by inaccurate modelling of atmospheric transport and mixing processes; c) covariance between surface fluxes and boundary layer meteorology (rectification artefacts). Diffusive atmospheric transport amplifies these uncertainties. Recent improvements in the sampling density from ground-based and aircraft-based instrumentation have improved flux estimates over northern hemisphere landmasses. However, the tropical landmasses, thought to be large sinks of CO2, remain one of the most under-sampled regions in the world for carbon cycle research. Space-borne measurements of CO2 have the potential to fill these gaps, providing global coverage and daily observations. Although less accurate than in situ measurements and challenging to use, these data seem certain to offer new quantitative insights into the working of the global carbon cycle.

NERC is well placed to contribute significantly to the exploitation of CO2 data from two new space-based missions to be launched in 2008: the NASA Orbiting Carbon Observatory (OCO) and the JAXA Greenhouse gas Observing SATellite (GOSAT). OCO and GOSAT are the first missions dedicated to measuring column CO2 with sufficient precision to test current quantitative understanding of the global carbon cycle. UK involvement with these new data is a natural progression from pioneering UK work on interpreting space-based CO2 measurements from SCIAMACHY and AIRS, and builds on decades of UK research on carbon cycle measurements, satellite remote sensing, biomass burning, terrestrial and ocean biosphere modelling, atmospheric transport and data assimilation. The UK’s contribution to these missions should also include ground-based and aircraft measurements of CO2 and other trace gases as part of the calibration and validation activities critical to the success of OCO and GOSAT. The expertise and leadership embodied within the National Centre for Earth Observation (NCEO) and its research partners places the UK in an enviable position as regards reaping science and applications benefit from use of these instruments. Failure to work effectively with these data is likely to put the UK far behind internationally in both carbon cycle research and our ability to provide quantitative estimates of carbon fluxes.
The document is divided into sections related to the major steps within the work-plan in Figure 1, and includes a set of recommendations intended to allow the UK to take a leading international role in exploiting the OCO and GOSAT data for C cycle research and monitoring. Section 2 concerns the science questions to be addressed using OCO and GOSAT. Section 3 describes the OCO and GOSAT missions and the associated data products. Section 4 outlines calibration/validation activities in support of OCO and GOSAT. Section 5 deals with surface flux and atmospheric transport models. Section 6 outlines the use of data assimilation to recover surface flux maps of CO2 from OCO and GOSAT observations. Section 7 concerns improvement in source attribution by combining XCO2 data with in situ and other remotely sensed data. Section 8 is a summary of UK capabilities and international collaborations in support of OCO and GOSAT.

Figure 1: Schematic of workplan for processing and interpreting CO2 measurements from OCO and GOSAT.

2 Outstanding Questions and Uncertainties in Carbon Cycle Science

Global coupled carbon-cycle climate models disagree on the strength of carbon-climate coupling (Friedlingstein et al 2006), reflecting fundamental gaps in our knowledge of C cycling. These differences between models are clear indicators of major uncertainty in predictions of the future of the Earth system. Most information about the C cycle is gathered at either global scales or local scales (e.g. eddy flux towers). Regional datasets, lying between these scales, are sparser and more uncertain (by regional, we mean observations that sample the seasonal activity of an ecoregion, such as the Amazon basin, Siberian taiga, Alaskan tundra and African deciduous woodlands (~106 km2)). Lack of regional data is one of the major issues preventing severe testing and subsequent winnowing of the coupled models.

Atmospheric inventory and fossil fuel burning estimates provide strong constraints on the C cycle at the global scale (Table 1). At the regional scale the constraints are weaker. This is related to sparsity of the CO2 network and fire records; equatorial and tropical ecosystems are particularly poorly observed. The largest weaknesses relate to: a) quantifying carbon emissions from fires in terms of long-lived carbon stores lost to the atmosphere and global and regional flux estimates, b) regional distribution of CO2 over land and ocean, particularly over tropical ecosystems, c) land use change and deforestation, again particularly within the tropics, and d) the magnitude of air-sea fluxes of CO2. Given the precision requirements on the XCO2 data from OCO and GOSAT, these data are best employed to constrain surface fluxes of CO2 due to, e.g., fire and biospheric release and uptake.

Constraints on Global C Budget
Strength of Constraint (uncertainty)
Atmospheric C inventory and its rate of change

Atmospheric concentration record

Strong (<5%)

C emissions from fossil fuels and cement manufacture
Carbon Dioxide Information Analysis Centre (CDIAC)

Strong (<5%)

Anthropogenic C in the oceans

Ocean surveys (GEOSECS, WOCE, ongoing repeat sections)

Strong (<5%)

Patterns in atmospheric CO2 and inverse modeling of atmospheric transport

Atmospheric CO2 records (NOAA/ESRL and other networks)

Intermediate (~50%)

Air-sea partial pressure differences

Atmospheric CO2 and ocean surface pCO2
Intermediate for magnitudes (~50%)

Good for spatio-temporal patterns

Fire emissions
Ground-based forest and peat records
Atmospheric records (CO2, CO, 13CO2, CH4, COS, O2/N2)

Global Fire Emission Database

Intermediate (~50%)

Deforestation (mainly tropics)

Remote sensing and atmospheric records (CO2)
Weak (~100 %)

Forest changes

Forest censuses
Strong in N America, Amazon, Europe. Elsewhere weak or missing.





Table 1. Characterizing the strength of various constraints on the global C budget (M. Gloor).

The poor constraints at the regional scale give rise to a number of key outstanding science questions associated with the carbon cycle:

  • What is the relative importance of the land-biosphere CO2 fluxes over different latitudes? There is still argument about the location of hypothesized terrestrial C sinks.

  • Which processes control land-biosphere fluxes in different ecoregions, how do these processes operate and how will they respond to climate change?

  • How much carbon is emitted from biomass burning, deforestation and land use change?

  • What is the magnitude and distribution of air-sea exchange of CO2?

  • How much will large stores of C in northern high latitudes contribute to future carbon emissions?

The overarching objective of this document is to define a UK programme to resolve these questions using novel measurements of atmospheric CO2 from OCO/GOSAT. This programme will provide the tools to exploit OCO/GOSAT data and combine these with state-of-the-art models and surface and aircraft observations. The outcome will be improved understanding of processes that control the distributions of CO2 and ensuing improvements in attribution and prediction of atmospheric CO2. Such a programme will focus a wide range of NERC expertise on unlocking the potential of the OCO and GOSAT missions, thus enhancing the scientific return of NERC-funded carbon cycle research and the profile of NERC in the international arena. In this document we outline the science, the existing UK expertise, and the current gaps and opportunities associated with using CO2 measurements from space.

3 The OCO and GOSAT Missions

Both missions are due to be launched in late 2008, acquiring spectroscopic measurements of CO2 and O2 allowing the column integrated CO2 dry air mole fraction, XCO2, to be estimated at precisions of 1 ppm (0.3% of column) on regional scales (8ox10o).

The OCO mission is dedicated to measuring space-based CO2 columns at sufficient precision to identify CO2 sources and sinks on regional scales over the globe and quantify their variability over the seasonal cycle. It has a 2-year design lifetime with launch scheduled for December 2008. OCO will join the EOS Afternoon Constellation (A-Train), flying in a sun-synchronous polar orbit with a constant 1:26 p.m. local solar time flyover, a 16-day (233 km altitude orbit) repeat cycle and near global sampling.

The OCO instrument will measure near-infrared, high-resolution spectra of the O2 A-Band and two CO2 bands in nadir and glint geometry, thus providing high signal-to-noise observations over land and ocean. It will acquire 4-8 cross-track observations with 3 Hz sampling frequency, resulting in 200-400 observations per degree of latitude along-track and 7 to 14 million observations every 16 days. The horizontal resolution of each measured scene will be less than 10 km2, even at large solar zenith angles.
Calibrated Level 1 spectra and noise estimates of all soundings will be available from NASA. The spectra will first be analyzed with a fast semi-analytic algorithm to obtain cloud and aerosol information as well as an estimate of XCO2. A subset (~2% of all soundings) of the cloud-free spectra will then be analyzed with a full-physics, optimal-estimation algorithm that will provide XCO2 retrievals together with error estimates and averaging kernels, as well as estimates of all other retrieved parameters, such as surface pressure and aerosol optical depth.

The Japanese GOSAT mission is led by JAXA, the National Institute for Environmental Studies (NIES) and the Ministry of the Environment (MOE), and will be launched in 2008 with a nominal lifetime of four years. Its main objective is to halve current sub-continental scale CO2 annual flux estimation errors. GOSAT will be launched into a sun-synchronous orbit at 666 km height and an equator crossing time of 1 pm, similar to that of OCO. As compared to OCO, GOSAT offers both CO2 and CH4 with greater coverage of the Earth, but at slightly lower spatial resolution (the issue of resolution is discussed further below).

GOSAT will operate in nadir and glint modes, using a Fourier transform spectrometer (FTS) and a 4-channel camera with 1 km resolution (ch1: 0.38 μm, ch2: 0.67 μm, ch3: 0.87 μm, and ch4: 1.61 μm) for cloud detection. The FTS will also have 4 channels, three in the near infrared and one in the thermal infrared. Channel 1 (0.75-0.78 μm) will cover the 0.76 μm O2 A-band at short wavelengths, channel 2 (1.56-1.72 μm) the 1.6 μm CO2 and CH4 bands, and channel 3 (1.92-2.08 μm) the 2 μm CO2 band at a maximum resolution of 0.2 cm-1. The TIR band (5.5-14.3 μm) will cover some of the long wavelength CO2 and CH4 bands, plus ozone and water vapour. The spatial resolution is 10 km2 on the ground. The estimated signal-to-noise ratio is 300. GOSAT can measure at night using the TIR channels, and will monitor the polarization of the reflected and emitted radiation from the earth, providing additional information about clouds and aerosols. The “operational” GOSAT data products will be total column densities for CO2 and CH4, derived primarily from the NIR data, as well as atmospheric profiles derived mainly from the TIR data. The NIR and TIR will be used synergistically to improve the retrievals.
Effective temporal and spatial resolution

The temporal and spatial resolutions quoted for the OCO and GOSAT sensors are for a single observation. However, the important quantities from the point of view of using the data are their effective resolutions in time and space after averaging or compositing the data. It is not obvious from the available literature what these resolutions will be and what will be their finest possible values, and we need greater clarity about this.

Data access

OCO Level 1 and Level 2 data will be delivered to a NASA Distributed Active Archive Center (DAAC) for open distribution no later than 6 months and 9 months after launch, respectively. Members of the OCO science team will have early access to the data for calibration and validation purposes. NASA Headquarters plans to release a NASA Research Announcement (NRA) for participation in the OCO science team within the NASA Roses 2008 program to support cal/val activities.  Such announcements usually require a designated PI for each proposed investigation, but often allow multiple investigators on each team.  A successful proposal to this NRA by a team from NCEO would provide early access to OCO data. 

The ESA third-party agreement is not yet finalized, but ESA will keep us informed on progress.
An invitation to join the GOSAT science team will be announced at the EGU in April.

3.1 The UK should identify individuals or groups charged with acting as the UK points of contact with OCO and GOSAT, who will know how to access the datasets and have detailed knowledge of their properties, especially instrument and retrieval errors properties, sampling and averaging issues. We must if possible ensure participation in the GOSAT science team.

4 Calibration and validation

The unprecedented precision required for the total CO2 column measurements makes extensive cal/val imperative if OCO and GOSAT are to meet their mission objectives. Expertise within the UK will allow NERC to make a major contribution to cal/val, and thus benefit from early access to OCO and GOSAT data, as well as science team hardware and software knowledge that will greatly improve our understanding of the data.
Ground-Based Instruments

The OCO team has installed a small network of Fourier Transform spectrometers (FTS) that observe the solar spectrum after passage of the direct beam through the atmospheric column. This network, called the Total Carbon Column Observing Network (TCCON,, is dedicated to making accurate and precise measurements of CO2 and O2 in support of OCO and GOSAT. Figure X shows the sites of current, future and possible sites within TCCON.

The FTS instruments have been placed at locations that provide information on aerosols (e.g. Atmospheric Radiative Measurements sites []), because space-based retrievals of CO2 are sensitive to optical depth and aerosol scattering. The satellite instruments will be pointed at a specific ground-site and measure an atmospheric spectrum using scattered sunlight and/or thermal emission; at the same time, the ground-based FTS will measure a solar absorption spectrum in the same spectral interval, but at higher spectral resolution. The vertical columns of CO2 and CH4 measured by the satellite and the FTS will then be compared using the same atmospheric forward model and the same spectroscopic parameters.
Mention should also be made of the NOAA ESRL flask network ( that currently provides the ground-based observations supporting atmospheric inversion. It seems likely that OCO and GOSAT will be used alongside the flask data in any scientifically mature carbon data assimilation scheme.

Aircraft campaigns

The OCO science team has recently prepared a science case for the Carbon Observatory Validation Experiment (COVE). This will deploy in situ sensors on two aircraft: a high-altitude platform that can reach the tropopause (ER-2 or WB-57B) and an aircraft that will routinely measure trace gases in the boundary layer, focusing on CO2 and other species measurable by the FTS (CH4, CO, O3). The high-altitude platform will also carry the GOSAT airborne simulator, a cloud imager and aerosol lidar, and a sun photometer capable of measuring in the near IR. These in situ concentration data will be used to sample atmospheric profiles of key species from the surface to the mid-stratosphere, with sampling anchored at the FTS sites at Park Falls, WI and the Oklahoma ARM site. The GOSAT simulator will provide a view of the spectra observed by the space-borne platforms, but with the geometry controlled by the experiment. The aerosol and cloud data will inform level-1 retrieval algorithm developers and testers. COVE will likely take advantage of aircraft deployments already planned for late 2009 or early 2010.


4.1 Build on UK FTS strengths to establish FTS measurements at one or more sites within the UK and possibly at the NERC-funded Cape Verde atmospheric observatory ( The latter would be particularly important, since there are no confirmed equatorial FTS deployments in TCCON, despite the importance of tropical ecosystems in determining global CO2 concentration.

4.2 Use NCEO influence to raise the priority of OCO and GOSAT cal/val in NCAS activities, including inclusion in the EUFAR proposal, and formulate plans to link aircraft measurements to ground-based data, flux modelling and satellite observations of CO2 and related species.

5 Relating atmospheric column CO2 concentration measurements to surface fluxes

Relating surface CO2 fluxes to global 3-D concentrations of CO2 mole fraction in either forward or inverse mode requires prior estimates of surface fluxes (often derived from a model) together with an atmospheric transport model (here under the more general banner of chemistry-transport models [CTMs]).

Surface flux models

a) Land Biosphere

The UK has great strengths in land surface flux models that estimate biospheric net primary production (NPP) and respiration fluxes, with a particular focus on the JULES land surface scheme that links the Hadley Centre, NCEO and QUEST. Although such models typically carry out ~hourly calculations for their biophysical calculations, they tend not to be used for estimating short-term dynamics, so do not routinely provide flux estimates at the hourly timescales needed for CTMs. Similar calculations are available from the CASA (Carnegie-Ames-Stanford) ecosystem model at a time resolution of 1 month, thus representing the seasonal cycle of NPP and respiration. However, CASA also provides datasets with a 3-hourly timestep by using high time-resolution ECMWF radiation and temperature data in the calculations, and daily values of NPP and respiration are available from the SiB-2 ecosystem model. The CASA and Sib-2 datasets are both at a spatial resolution of 1ox1o. (Typically, the spatial scale of biospheric C flux calculations is determined by the grid-scale of the climate data.)

b) Ocean surface

The most recent air-sea exchange estimate, compiled from global sea-surface pCO2 measurements, is at The ocean element of the NCEO Carbon theme will derive models for both the physical and biological components of CO2 exchange at the ocean surface.

Atmospheric transport modelling

Two world-class global tropospheric 3-D CTMs are supported by the NCEO: GEOS-Chem and TOMCAT (TM5 is also being used in the CCMAP project in Bristol: Marko Scholze). TOMCAT includes a detailed stratosphere and the GLOMAP aerosol scheme, and is driven by ECMWF meteorology, whereas GEOS-Chem includes a more complete aerosol-gas phase chemistry scheme in the troposphere and is driven by GMAO meteorology. Access to GEOS-Chem allows NCEO to benefit from extensive intellectual investment by US and European scientists in its development and the opportunity for continued co-operation. Both models can calculate the CO2 dynamics needed for simulating OCO and GOSAT data.

Currently, Europe has no equivalent of the NOAA ESRL CarbonTracker (, which is the TM5 global CTM with a nested grid over North America, driven by ECMWF analyses. This includes an ensemble Kalman Filter scheme to assimilate flask data, and calculates global and regional CO2 atmospheric concentrations and flux estimates.
An omission from this note is information on ECMWF plans for carbon flux estimates.
Known problems with CTMs:

1. Vertical transport, especially for biomass burning regions.

2. CTM differences cause significant differences in CO2 estimates

5.1 Urgently develop an atmospheric transport simulation capability to support OCO and GOSAT. This should include access to and preparation for NRT ECMWF data.

5.2 Establish a clear link between atmospheric transport modelling and the land and ocean surface flux modelling activities in NCEO and elsewhere.

5.3 Establish (or help develop) a NRT nested-grid simulation of CO2 mole fraction and column over Europe that complements the US CarbonTracker, possibly as a consortium bid. This could be based on CCDAS or the Dutch group responsible for CarbonTracker. Information on ECMWF plans for carbon flux estimates are needed to firm up any recommendation.

6 Level 2 Data Analysis

Figure 1 shows that we can start to directly address science questions with validated XCO2 products (section 4) from OCO and GOSAT without having to use data assimilation machinery (section 7). While OCO and GOSAT will focus on CO2 (and CH4 for GOSAT) there are a number of complementary datasets, available from a range of platforms, which will be used to interpret broad-scale variability in the XCO2 data.
Measurements of multiple carbon-relevant species (e.g., CO2, CO, CH4, COS) have been made on a range of NASA-GTE campaigns (, including INTEX-A and B, TRACE-P, and the PEM flights. Continuous measurements of CO2 mixing ratios are currently made at tall tower sites (up to 500 m) in Wisconsin (WLEF), Texas (KETK), and Maine (AMT). Continuous measurements of CO, a tracer of incomplete combustion, are ongoing or planned at these sites. Weekly flask measurements of CO2, CO, CH4 and COS are made at sites of the NOAA-ESRL surface network ( Bimonthly aircraft profiles are now being made at over fourteen sites worldwide by NOAA-ESRL. Models of atmospheric transport will be used an intermediary between surface data (and incomplete vertical profiles) and the XCO2 data.
There are also a number of space-borne platforms that currently provide detailed information about land-surface properties related to land biosphere and biomass burning properties, including leaf-area index, enhanced vegetation index, fire radiative power, burned area and firecounts. These data provide important additional information to improve source attribution. Other satellite observations of carbon species, such as CO, HCHO (a tracer of biogenic and burning activity) and CH4, will likely be available from GOME-2 and IASI aboard the MetOp platform over the lifetime of OCO and GOSAT. Depending on the lifetime of current low Earth orbiting spacecraft and their onboard instruments we may also have CO, HCHO, CH4 and CO2 data from TES, OMI and SCIAMACHY. In general, melding atmospheric concentration information from different platforms requires careful attention to instrument averaging kernels.


6.1 Establish a programme to improve CO2 source attribution using co-emitted trace gases (NCEO Atmospheric Composition Theme).

6.2 Establish a programme to improve the synergy between trace gas measurements and complementary EO products such as fire radiative power and leaf phenology. This involves close collaboration between the NCEO Carbon Cycle and Atmospheric Composition Themes.

6.3 Establish, with NCAS, an aircraft programme of trace gas measurements that can be used to help interpret observed XCO2 observations over specific geographical regions.

7 Data assimilation of XCO2

Data assimilation is a process that combines data and models, and their respective uncertainties, to give a better estimate of the system state than using either model or data alone. This involves minimizing the discrepancy between modelled and observed values of CO2 by estimating CO2 concentrations, CO2 surface fluxes and/or flux model parameters. Developing a DA framework also enables us to test the consistency between data and models (e.g. are JULES predictions of Amazon drought stress consistent with XCO2 over that region?) and between different data.
Flux estimation

Two complementary assimilation approaches will be adopted in the NCEO: four-dimensional variational assimilation (4DVAR) and the ensemble Kalman Filter (EnKF). The EnKF is supported for CH4 flux estimation by the NCEO DA Themes. An 18-month study to simulate CO2 flux estimation from OCO using EnKF has already started at Edinburgh, funded through the NERC EO Enabling Fund. 4DVAR is supported by the NCEO DA Theme, with a focus on CO2 flux estimation from OCO and GOSAT.

Model parameter estimation

In the NCEO DA theme, 4DVAR will be used to assess the ability of OCO and GOSAT to estimate model parameters in the BETHY terrestrial biosphere model within the CCDAS framework.


Budgets for instrument, retrieval (see Recommendation 2.1) and model, errors need to form part of the DA scheme. In particular, reducing vertical transport error remains a key challenge for atmospheric transport models, especially in the boundary layer and over active convective regions. In theory, DA can account for model error but estimating this error is difficult.

Exploiting multiple data sources

Combining EO and in situ measurements of co-emitted trace gases and land surface properties will improve attribution of observed variations in CO2 to their sources. For instance, variations in carbon-containing trace gases such as carbon monoxide (CO), methane (CH4), carbonyl sulphide (COS) and formaldehyde (HCHO) provide additional constraints on net surface fluxes of CO2 from the biosphere, biomass burning and fossil-fuel burning. Independent land-surface properties, such as burnt area and enhanced vegetation index, can be used to improve the prior information used in regularizing the inverse problem or used as independent verification for a posteriori flux estimates.

Combining observations from different sensors is not straightforward. Atmospheric DA might help, given the wealth of experience in the NWP community. Key issues are bias correction and better definition of the background (a priori) covariance matrix, suitable for XCO2 assimilation. The latter is important because satellite sensors are usually only able to retrieve broad layers, so detailed vertical information comes directly from the model. This requires proper error statistics; otherwise the information will be misinterpreted.


7.1 Establish a DA working group to consider (a) model error; (b) error covariance for successive measurements and different species; (c) compare DA techniques.

7.2 Obtain funding for OCO and GOSAT DA work after the current EO enabling grant expires.

8 National capability and international collaborations

UK capabilities
Currently funded UK activities relevant to OCO/GOSAT include:

  • Palmer - 18 month PDRA through EO enabling fund

  • Dance - project partner on Edinburgh OCO grant

  • Scholze - NCEO Theme 7 (data assimilation) PDRA

  • Woodward - NCEO Theme 2 (carbon cycle) PDRA

  • Gloor - NERC quota PhD 2007-

  • Monks/Boesch – PDRA (BNSC, Scottish Exec, UKMO); NERC quota studentship; and NCEO PDRA (tbc)

  • Bernath - NERC quota PhD (tbc)

  • Suntharalingam (RCUK fellow)

  • Engelen - GEMS

QUEST and NERC are also funding two other activities around built around CCDAS; the relation of OCO and GOSAT to these activities is described in a separate document.

Instrument Science Teams

Hartmut Boesch and Paul Palmer are science team associates. An AO to join the GOSAT science team is due early 2008. The next OCO science team meeting will be 26-28th March 2008.
National and European weather centres

ECMWF is currently coordinating the GEMS (Global and regional Earth-system Monitoring using Satellite and in-situ data), an integrated project funded by the European Commission Framework 6 programme. GEMS includes 31 European partners and aims to build a global monitoring system for atmospheric composition as well as a regional air-quality forecasting capability (clarification needed: does this include CO2?). The GEMS system has extended the NWP 4D-Var data assimilation system to enable assimilation of various satellite data sources to constrain concentrations of greenhouse gases, reactive gases, and aerosols. ECMWF is open to exchange of expertise and relevant data with research groups that are not directly involved in the project.

UKMO (Chris Jones/Dave Pearson to update)

Our objectives are twofold. Partly, we have some deliverables under CarboEurope along the lines of constrained estimates of European carbon balance using data assimilation techniques. In the longer term we're interested in a full CCDAS-type system - maybe taking CCDAS itself and substituting JULES for BETHY. Initially we will use flask data, but have an eye on satellite CO2, perhaps ogether with some sort of system to Monte Carlo the flux tower data to get prior info as input to CCDAS. Our DA approach: Var with adjoint is the initial aim, but again open for debate if other techniques with JULES look promising.

The National Centre for Earth Observation

The NCEO incorporates satellite remote sensing, modelling of land and ocean processes related to the carbon cycle, atmospheric transport and chemistry, and data assimilation. This represents a unique framework within which to develop the integrated research programme necessary to properly interpret satellite observations of CO2 in terms of land and ocean processes. This will involve close cooperation between the NCEO Carbon Cycle, Atmospheric Chemistry, Data Assimilation and Climate Themes, together with some elements of the Extreme Weather and Water Resources Theme. Resources will also be needed from the Mission Support element of NCEO.

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