cfusion and nceo
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CFusion and NCEO
NCEO Components
Climate data synthesis forprediction
Carbon cycle
Atmosphericcomposition
DynamicEarth
Cryosphere
High impactweather and
hydrology
Data assimilation and treatment of uncertainty
EO Informatics
Computing resources TrainingKnowledge transfer
Wider NERC supported EO programme
Σ
Ciais et al. 2003 IGOS-P Integrated Global Carbon Observing Strategy
Geo-referenced emissions inventories
Geo-referenced emissions inventories
Atmospheric measurements
Atmospheric measurements
Remote sensing of atmospheric CO2
Remote sensing of Remote sensing of atmospheric COatmospheric CO22
Atmospheric Transport Model
Atmospheric Transport Model
Ocean Carbon Model
Ocean Carbon Model Terrestrial
Carbon ModelTerrestrial
Carbon Model
Remote sensing of vegetation properties
Growth cycleFires
BiomassRadiation
Land cover/use
Ocean remote sensingOcean colour
AltimetryWindsSSTSSS
Water column inventories
Ocean time seriesBiogeochemical
pCO2
Surface observation
pCO2
nutrients
Optimised model
parameters
Optimised model
parameters
Optimised fluxes
Optimised fluxes
Ecological studies
Biomass soil carbon
inventories
Eddy-covariance flux towers
Coastal studiesCoastal studies
rivers
Lateral fluxes
Data assimilation
link
Climate and weather fields
Geo-referenced emissions inventories
Geo-referenced emissions inventories
Atmospheric measurements
Atmospheric measurements
Remote sensing of atmospheric CO2
Remote sensing of Remote sensing of atmospheric COatmospheric CO22
Atmospheric Transport Model
Atmospheric Transport Model
Ocean Carbon Model
Ocean Carbon Model Terrestrial
Carbon ModelTerrestrial
Carbon Model
Remote sensing of vegetation properties
Growth cycleFires
BiomassRadiation
Land cover/use
Ocean remote sensingOcean colour
AltimetryWindsSSTSSS
Water column inventories
Ocean time seriesBiogeochemical
pCO2
Surface observation
pCO2
nutrients
Optimised model
parameters
Optimised model
parameters
Optimised fluxes
Optimised fluxes
Ecological studies
Biomass soil carbon
inventories
Eddy-covariance flux towers
Coastal studiesCoastal studies
rivers
Lateral fluxes
Data assimilation
link
Climate and weather fields
Global Carbon Data Assimilation System
C Cycle Linkages
CTCD
CASIX
LeicesterOthers
DARC
ABACUS
QUERCC
MUCMSAGES
TROBIT
Terrestrial Carbon
CLASSIC
Ocean carbon
Atmospheric carbon
Atmospheric trace gas DA
NEW NERC PROJECT International Collaboration on Data Assimilation in Terrestrial Carbon Cycle Science
Exchange between scientific staff for three months from key institutions (CSIRO, MPI, LSCE, CSU, MBL; in the UK, CTCD and DARC are joint leaders on this project, but we will also be looking at the needs and opportunities for QUEST, ECMWF, CLASSIC and CEH). International conferenceSix international workshops
CFusion Working Groups
REFLEX – DA comparison experiment OCO and GOSAT Mathematical structures underlying DA Fire
Structure of Carbon Theme
Ocean surface observations
Atmospheric observationsof CO2 and CH4
Land surface observations
Data assimilation
Ocean surfaceFlux model
Model parameters
Atmosphericchemistry-transport model
Land surfaceflux model
Model parameters
Surface fluxes Surface fluxes
C Cycle Sub-themes
Using atmospheric measurements of CO2 and CH4 to learn about surface fluxes and their causes.
Model-data fusion for land C fluxes using surface observations Carbon fluxes from biomass burning Ground-based methods: data, parameters, process descriptions
and EO fundamentals. Understanding the tropical carbon balance of the land surface. Quantification of sea surface processes Quantification of ocean biogeochemistry and carbon fluxes Quantification of bio-physical interactions and air-sea CO2 fluxes Data assimilation techniques for marine ecosystem models. Reanalysis, validation and prediction of marine carbon estimates
EO interactions with a ecosystem model
Parameters
Model
Climate
Soils
Sn Sn+1
Processes
Observable
Land coverForest age
PhenologySnow waterBurnt area
Testing:RadiancefAPAR
Possible feedback
fAPARLAI
Conceptual model of the ocean carbon cycle and surface exchange
NCEO Components
Climate data synthesis forprediction
Carbon cycle
Atmosphericcomposition
DynamicEarth
Cryosphere
High impactweather and
hydrology
Data assimilation and treatment of uncertainty
EO Informatics
Computing resources TrainingKnowledge transfer
Wider NERC supported EO programme
Σ
Mission support
Funding
Total funds = £40.7M over 6 years.
Total funding for C cycle theme: £4.6M.
NERC International Opportunities Fund
Key question: in what areas would the NERC science base most benefit from exposure to international know-how and collaboration?
→ International Collaboration on Data Assimilation in Terrestrial Carbon Cycle Science (CFusion)
Meetings Workshops Staff secondment Reports
Remote sensing of atmospheric CO2
Remote sensing of Remote sensing of atmospheric COatmospheric CO22
Atmospheric Transport Model
Atmospheric Transport Model
Terrestrial Carbon Model
Terrestrial Carbon Model
Remote sensing of vegetation properties
Growth cycleFires
BiomassRadiation
Land cover/use
Optimised model
parameters
Optimised model
parameters
Optimised fluxes
Optimised fluxes
Ecological studies
Biomass soil carbon
inventories
Eddy-covariance flux towers
rivers
Lateral fluxes
Climate and weather fields
Remote sensing of atmospheric CO2
Remote sensing of Remote sensing of atmospheric COatmospheric CO22
Atmospheric Transport Model
Atmospheric Transport Model
Terrestrial Carbon Model
Terrestrial Carbon Model
Remote sensing of vegetation properties
Growth cycleFires
BiomassRadiation
Land cover/use
Optimised model
parameters
Optimised model
parameters
Optimised fluxes
Optimised fluxes
Ecological studies
Biomass soil carbon
inventories
Eddy-covariance flux towers
rivers
Lateral fluxes
Climate and weather fields
Terrestrial Component
+ Water components: SWEsoil moisture
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