Earth Observation Data and Carbon Cycle Modelling

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Earth Observation Data and Carbon Cycle Modelling
(an incomplete and subjective view)

• Marko Scholze
• QUEST, Department of Earth Sciences
• University of Bristol
• GAIM/AIMES Task Force Meeting, Yokohama, 24-29
  Oct. 2004

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Overview

• Atmospheric CO2 observations
• TransCom
• Model-Data Synthesis
• Oceanic DIC observations Inverse Ocean Modelling
  Project
• Terrestrial observations Eddy-flux towers
• Atmospheric observations Carbon Cycle Data
  Assimilation system

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TransCom 3

• Linear atmospheric transport inversion to
  calculate CO2 sources and sinks
• 4 background "basis functions" for land, ocean,
  fossil fuels 1990 1995
• 11 land regions, spatial pattern proportional to
  terr. NPP
• 11 ocean regions, uniform spatial distribution

• Solving for 4 (background) 22 (regions) 12
  (month) basis functions!

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TransCom 3 Seasonal Results(mean over 1992 to
1996)
Guerney et al., 2004
inversion results
response to background fluxes
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4
Gt C/yr
-5
-35
ppm
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TransCom 3 Interannual Results (1988 - 2003)
red land blue ocean darker bands
within-model uncertainty lighter bands
between- model uncertainty
Gt C/yr

• larger land than ocean variability
• interannual changes more robust than seasonal

... but atmosphere well mixed interannually...
Baker et al. 2004
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Model-Data SynthesisThe Inverse Ocean Modelling
Project
Recent ocean carbon survey, 60.000 observations
C of Gruber, Sarmiento, and Stocker (1996) to
estimate anthropogenic DIC. Innumerable data
authors, but represented by Feely, Sabine, Lee,
Key.
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The Inverse Ocean Modelling Project
Jacobson, TransCom3 Meeting, Jena, 2003
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The Inverse Ocean Modelling Project

• southward carbon transport of 0.37 Pg C/yr for
  pre-industrial times
• present-day transport -0.06 Pg C/yr (northwards)

Gloor et al. 2003
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Terrestrial observations Fluxnet a global
network of eddy covariance measurements
Inversion of terrestrial ecosystem parameter
values against eddy covariance measurements by
Metropolis Monte Carlo sampling
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A Posteriori parameter PDF for Loobos site
ga,v vegetation factor of atmospheric
conductance Evm activation energy of Vm
Knorr Kattge, 2004
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Carbon sequestration at the Loobos site during
1997 and 1998
Knorr Kattge, 2004
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CCDASCarbon Cycle Data Assimilation System
Forward Modeling Parameters gt Misfit
Misfit to observations
Atmospheric Transport Model TM2
Biosphere Model BETHY
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CCDAS set-up

• 2-stage-assimilation
• AVHRR data
• (Knorr, 2000)
• Atm. CO2 data

• Background fluxes
• Fossil emissions (Marland et al., 2001 und Andres
  et al., 1996)
• Ocean CO2 (Takahashi et al., 1999 und Le Quéré et
  al., 2000)
• Land-use (Houghton et al., 1990)

Transport Model TM2 (Heimann, 1995)
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Methodology
Minimize cost function such as (Bayesian form)
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Gradient Method
Figure from Tarantola, 1987
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Data Fit
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Seasonal Cycle
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Global Growth Rate
Atmospheric CO2 growth rate
Calculated as
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Error Reduction in Parameters
Relative Error Reduction
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Carbon Balance
net carbon flux 1980-2000 gC / (m2 year)
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IAV and processes
Major El Niño events
Major La Niña event
Post Pinatubo period
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Interannual Variability
Lag correlation (low-pass filtered)
correlation coefficient
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Outlook

• Data assimilation problem better constrained
  without "artefacts" (e.g. spatial patterns
  created by station network)
• but cannot resolve processes that are not
  included in the model (look at residuals and
  learn about the model)
• Simultaneous inversion of land and ocean fluxes
• Isotopes
• More data over tropical lands satellites

• Model-Data-Synthesis problem better constrained
  without "artefacts" (e.g. spatial patterns
  created by station network)
• but cannot resolve processes that are not
  included in the model (look at residuals and
  learn about the model)
• Simultaneous inversion of land and ocean fluxes
• Further data constraints (e.g. Isotopes,
  Inventories)
• More data over tropical lands satellites

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Posterior Uncertainty in Net Flux
Uncertainty in net carbon flux 1980-200 gC / (m2
year)
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Uncertainty in prior net flux
Uncertainty in net carbon flux from prior values
1980-2000 gC / (m2 year)
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Atm. Inversion on Grid-cell
Rödenbeck et al. 2003

• prior and posterior uncertainties
• sensitivities (colors)

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Atm. Inversion on Grid-cell
Not really at model grid of TM3, but aggregated
to TM2 grid, 8 x 10, Underdetermined problem ?
correlation matrix (e.g. l1275 km for NEE)
prior/posterior fluxes and reduction in
uncertainty
Rödenbeck et al. 2003
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CO2 Satellite Measurements
Vertical weighting functions
Houweling et al. 2003
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Pseudo Satellite Data Inversion
posterior/prior uncertainty
Houweling et al. 2003