Constructing and evaluating forward models of the terrestrial carbon cycle

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Constructing and evaluating forward models of the
terrestrial carbon cycle
Peter Thornton Terrestrial Sciences
Section Climate and Global Dynamics Division NCAR
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Relevance of the terrestrial carbon cycle to
studies of the global climate

• Biophysical characteristics of the land surface
  depend on the interactions between surface
  weather, atmospheric composition and chemistry,
  and vegetation ecophysiology leaf area, canopy
  height, Bowen ratio, relative abundance of
  different plant functional types.
• Atmospheric concentration of CO2 depends, in
  part, on the dynamics of the terrestrial carbon
  cycle, with important variation at seasonal,
  interannual, decadal, and longer timescales.

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• Research questions
• What are the current dynamics of the
  terrestrial carbon cycle?
• What are the likely future trends in
  source/sink strengths under different emission
  and landuse change scenarios?
• How do current dynamics and likely future
  trends depend on coupling with climate and
  atmospheric chemistry?
• How much model detail is required to capture
  the dominant spatial and temporal modes of
  variation in the current and likely future
  terrestrial carbon cycles?
• How can coupled climate and carbon cycle models
  be evaluated?

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Coupled
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Land-Atmosphere Nitrogen Cycle
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Effects on NEE of natural and anthropogenic
disturbances Simulation based on recorded
disturbance history at Harvard Forest
NEE (gC m-2 yr-1)
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Effects on NEE of anthropogenic changes in
atmospheric composition and chemistry
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Terrestrial carbon cycle model evaluation over
gradients in climate and disturbance
history Evaluation based on observations of
carbon and water budget components from seven
evergreen needleleaf forest Fluxnet
sites Fluxnet collaborators B.E. Law, H.L.
Gholz, K.L. Clark, E. Falge, D.S. Ellsworth, A.H.
Goldstein, R.K. Monson, D. Hollinger, M. Falk, J.
Chen, J.P. Sparks
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Based on DeFries et al., 2000
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Location of Fluxnet sites included in this study
Base map average annual precipitation for
1980-1997
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Location of seven ENF Fluxnet sites in climate
space
Grey region Complete climate space for the U.S.
(lower 48)
Black region Climate space occupied by evergreen
needleleaf forest in the U.S (lower 48)
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Summary of site characteristics
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Duke Forest, NC
Gainesville, FL
Blodgett Forest, CA
Niwot Ridge, CO
Wind River Crane, WA
Howland Forest, ME
Metolius NRA, OR
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Modeling Protocol

• Using the Daymet surface weather database as the
  model driver at all sites.
• Spinup simulation to bring C and N pools into
  steady state repeated 18-year record of surface
  weather. Using assumed levels of CO2atm and
  Ndep circa 1795 AD.
• Ensemble of site history simulations, with
  increasing CO2atm (IS92a), increasing Ndep from
  anthropogenic sources (following Holland et al.,
  1997), and disturbance history as recorded at
  each site. All simulations ending at 2000 AD.
• Evaluation of ensemble statistics at current
  stand age, comparison against historical
  observations where possible.

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Daymet database of daily surface weather drivers
climate summary
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Disturbance history ensembling Each member
consists of a disturbance history simulation
initiated in a different year of the cyclic
18-year surface weather record.
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Results Decadal and longer timescale variations
dominated by disturbance history
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Results Decadal and longer timescale variations
dominated by disturbance history
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Results Relationship between NEE and GEP depends
on time since disturbance, and on changing
CO2atm and Ndep
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Results Relationship between NEE and GEP depends
on time since disturbance (continued)
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Results NEE response to disturbance, changing
CO2atm, and Ndep shows strong interaction
effects
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Results NEE response to CO2atm for old sites
near steady state depends on the rate of increase
in CO2
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Results Model captures observed variability in
leaf area index across the climate and
disturbance history gradients
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Results Model captures observed variability in
evapotranspiration across the climate and
disturbance history gradients
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Results Model captures observed seasonality in
evapotranspiration across the climate and
disturbance history gradients
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Results Model tends to underestimate annual NEE,
with strong biases at the warmest sites (FL, DU)
and the old sites (ME, WR).
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Results Model in generally poor agreement with
observed seasonal cycle of NEE
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Results but the biases are not consistently
attributed to either Re or GEP.
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Results but the biases are not consistently
attributed to either Re or GEP.
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Model evaluation at Metolius old-growth site
Comparison to biometric measurements of carbon
budget components
(all units gC m-2 yr-1)
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Results Model in generally poor agreement with
observed seasonal cycle of NEE
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Results Model agrees well with chronosequence
estimates of NEE at the one site where they are
available (FL)
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Results Model in generally poor agreement with
observed seasonal cycle of NEE
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Problem How to get rid of the double peak in
seasonal cycle of NEE? Focus on the Duke Forest
site
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• Reducing the temperature sensitivity for MR and
  HR gives some improvement, but double peak
  persists.
• Excessive reduction of temperature sensitivity
  for HR results in low GPP due to limited N
  mineralization (reduced decomposition of soil
  organic matter).
• Have to turn to the temperature dependencies
  for GPP and consider the RuBisCO enzyme.

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Ribulose-1,5-bisphosphate carboxylase/oxygenase (R
uBisCO)

• Enzyme kinetics described by Woodrow and Berry,
  1988, Ann. Rev. Plant Physiology and Plant
  Molecular Biology.
• Enzyme activity increases exponentially with
  temperature (eventual irreversible decrease in
  activity at high temperature, as proteins
  denature).
• RuBisCO catalyzes the fixation of CO2
  (photosynthesis) and the fixation of O2 (leading
  to photorespiration).
• The carboxylase and oxygenase reactions have
  different Michaelis-Menten coefficients, and
  these coefficients have different temperature
  dependencies.
• These differences result in an optimal
  temperature for photosynthesis which does not
  depend directly on the temperature sensitivity
  for the enzyme activity.

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The values listed are calculated from
measurements of the enzyme from spinach. There
may, however, be small significant differences in
the kinetic properties of Rubisco from different
species of C3 plants. -Woodrow and Berry, 1988
Low Topt
High Topt
Re
GEP
GEP
Re
MR
MR
HR
GR
HR
GR
NEE
NEE
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Results There is apparently a significant
variation in the kinetic parameters for RuBisCO
across the climate gradient.
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• Next steps in model parameterization and
  evaluation
• Find optimal kinetic parameters at each site, try
  to establish a dependency with simple climate
  indices that explains the variation in optimal
  temperature (underway).
• Incorporate measurements from soil chambers and
  leaf-level gas exchange data as additional
  constraints. Test climate dependency of optimal
  temperature with these data (underway).
• Expand the analysis to other plant functional
  types deciduous broadleaf forest, evergreen
  broadleaf forest, and grasses (C3 and C4).
• Bring in more extensive evaluation databases
  (inventory, remote sensing).

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Simulated Leaf Area Index for Evergreen
Needleleaf Forest, NW U.S.
(Compute time approximately 70 hours running
threaded code on lhotse)