Data Assimilation for the Carbon Cycle funded by NASAs Modeling and Analysis Program

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Data Assimilation for the Carbon Cycle funded by
NASAs Modeling and Analysis Program

• PI Steven Pawson (GMAO)
• Atmosphere
• Transport Julio Bacmeister (GMAO), Randy Kawa
  (GSFC)
• Assimilation and Inversion Ivanka Stajner, Andy
  Tangborn (GMAO), Scott Denning (CSU)
• Radiance modeling and retrieval Denis OBrien
  (CSU)
• Land
• Surface temperature assimilation Rolf Reichle
  (GMAO)
• Land carbon Jim Collatz (GSFC), Scott Denning
  (CSU)
• Fossil fuel inventory David Erickson (ORNL)
• Ocean
• Ocean carbon Scott Doney (WHOI) Watson Gregg
  (GMAO)

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Objectives

• Expand the capabilities of NASA/GMAOs GEOS-5
  modeling and analysis system for carbon-cycle
  science
• Develop and implement an infrastructure for
  model-data fusion for carbon cycle studies,
  optimizing top-down and bottom-up constraints on
  sources and sinks
• Exploit NASAs datasets and modeling capabilities
  to enhance our understanding of the carbon-cycle

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Schematic of the Carbon Data Assimilation System
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Research Themes and Plans Built Around GEOS-5
System

• Analysis of high-resolution global simulations of
  atmospheric carbon and sensitivity studies
• Separation of effects of transport error and
  source-sink uncertainty (model perturbations)
  isolate impacts on assimilation and inversions
  (OSSEs real data)
• Two-stage development of assimilation
• Stage 1 examine consistency of top-down and
  bottom-up estimates of CO2 ( CO, CH4) sources
  and sinks (2006-2008)
• Stage 2 develop optimal constraints for a
  coupled atmosphere-land-ocean assimilation system
  (2008-2010)
• Products CO2 concentrations and flux maps (AIRS,
  MODIS, , met. analyses) for 2002 onwards add
  OCO after launch

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Stage 1 Consistency of Top-Down Bottom-Up
Source-Sink Estimates

• The first stage of the proposal will follow this
  sequence
• Determine a first-guess source-sink distribution
  Sf from data-constrained land and ocean models,
  along with uncertainty estimates
• Run the atmospheric assimilation at high
  resolution, ingesting AIRS level-1b radiances and
  in-situ data into the additional carbon modules
  later use OCO data
• Use high-density analysis increments in an
  inversion procedure, to produce coarse-grain (say
  500km²) "corrections" to S
• Investigate the consistency of the improved S by
  examining parametric uncertainties in the
  underlying land- and ocean-carbon models - can we
  reconcile the flux estimates?
• Test concept in an OSSE framework before using
  real data OSSEs allow degradations to be
  included systematically

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Transport of CO in GEOS-4Real-time forecasting
for ICARTT/Intex-NA Field Mission
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Uncertainty of Convective Transport Radon
profiles using GEOS-4/5 Convection
Dashed line GEOS-4 Solid line GEOS-4 with
GEOS-5-like convection
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Schematic of the Challenges Posed by Uncertainty
in Sub-Grid Transport

• This is one of many scenarios need to study
  occurrence of convection and regions of
  inflow-outflow - parameter sensitivity in model
• Field mission data, Cloudsat/CALIPSO, etc., will
  be used along with trajectories from GEOS-5