Characterizing CO2 fluxes from oceans and terrestrial ecosystems

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Characterizing CO2 fluxes from oceans and
terrestrial ecosystems

• Nir Krakauer
• PhD thesis seminar
• May 19, 2006

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The atmospheric CO2 mixing ratio
Australian Bureau of Meteorology
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Warming is underway
Dragons Flight (Wikipedia) Data Hadley Centre
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The atmospheric CO2 mixing ratioA closer look

• 1990s fossil fuel emissions 6.4 Pg carbon / year
• The amount of CO2 in the atmosphere increased by
  3.2 Pg C / year
• Where did the other half of the CO2 go?
• Why the interannual variability?

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Ocean CO2 uptake

• The ocean must be responding to the higher
  atmospheric pCO2 models estimate 2 Pg C/ year
  uptake
• Hard to measure directly because air-sea CO2
  fluxes are patchy, depending on ocean
  circulation, biology, heating, gas exchange rate

LDEO
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CO2 uptake on land
Buermann et al 2002

• Change in C content of biomass very patchy hard
  to extrapolate from small-scale surveys
• Uptake must make up for 1.5 Pg C / year
  deforestation
• Land biomass might be growing because of longer
  growing seasons, CO2 fertilization, N
  fertilization, fire suppression, forest regrowth

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1) Tree-ring evidence for the effect of volcanic
eruptions on plant growth
Chris Newhall, via GVP
Henri D. Grissino-Mayer
N. Y. Krakauer, J. T. Randerson, Global
Biogeochem. Cycles 17, doi 10.1029/2003GB002076
(2003)
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Motivation

• Why did the atmospheric CO2 growth rate drop for
  2 years after the 1991 Pinatubo eruption?
• Changes in the latitudinal CO2 gradient and in
  d13C suggest that part of the sink was from
  northern land biota
• An enhanced carbon sink also followed the 1982 El
  Chichón and 1963 Agung eruptions

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How would eruptions lead to a carbon sink?

• Roderick et al (2001) and Gu et al (2003) light
  scattering by aerosols boosts canopy
  photosynthesis for 1-2 years after eruptions
• Jones and Cox (2001) and Lucht et al (2002) soil
  respiration is lower because of cooling boreal
  photosynthesis decreases

Gu et al 2003
Harvard Forest (clear skies)
Lucht et al 2002
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What I did

• What happened to tree ring widths after past
  eruptions?
• Large eruptions since 1000 from ice core sulfate
  time series

• 40,000 ring width series from the International
  Tree Ring Data Bank (ITRDB)

Crowley 2000
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Ring width anomalies by latitude
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above 45N by genus
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The 1990s Harvard Forest
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Part 1 Conclusions

• Northern trees (gt45N) had narrower rings up to 8
  years after Pinatubo-size eruptions
• Eruptions had no significant effect on trees at
  other latitudes (few trees from the tropics
  though)
• From this sample, negative influences on NPP
  appear to dominate positive ones respiration
  slowdown is likely to be responsible for the
  inferred carbon sink

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Part 1 Research directions

• Are there niches where diffuse light does
  strongly enhance growth? understory trees,
  tropical rainforest
• Why are boreal rings narrower so long after
  eruptions?
• Can we tell what happens to trees physiology
  after eruptions (short growing season, nutrient
  stress)? tree-ring d13C, d15N

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2) Selecting parameters in inversions for
regional carbon fluxes by generalized
cross-validation
Baker et al 2006
N. Y. Krakauer, T. Schneider, J. T. Randerson, S.
C. Olsen, Geophys. Res. Lett. 31, doi
10.1029/2004020323 (2004).
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CO2 fluxes from concentration differences a
linear inverse problem
Measurements of CO2 concentrations, with error
covariance matrix Cb
the (unknown) flux magnitudes
Ax b
A transport operator that relates concentration
patterns to flux magnitudes
x x0
A plausible prior flux distribution, with
prior uncertainty covariance matrix Cx
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Ambiguities in parameter choice

• Solving the inverse problem requires specifying
  Cb, Cx, x0
• Adjustable parameters include How much weight to
  give the measurements vs. the prior guesses?
  Weight CO2 measurements equally or
  differentially?
• Different parameter values lead to varying
  results for, e.g., the land-ocean and
  America-Eurasia distribution of the missing
  carbon sink

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Generalized cross-validation (GCV)

• Craven and Wahba (1979) a good value of a
  regularization parameter in an inverse problem is
  the one that provides the best invariant
  predictions of left-out data points
• Choose the parameter values that minimize the
  GCV function

T effective degrees of freedom
GCV
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The TransCom 3 inversion
Gurney et al 2002

• Estimates mean-annual fluxes from 11 land and 11
  ocean regions
• Data 1992-1996 mean CO2 concentrations at 75
  stations, and the global mean rate of increase

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Parameters varied

• ? How closely the solution would fit the prior
  guess x0
• controls size of the prior-flux variance Cx
• higher ? solution will be closer to x0 (more
  regularization)
• Weighting used in original TransCom inversion
  taken as ?1
• t How much preference to give data from
  low-variance (oceanic) stations
• controls structure of the data variance Cb
• 0 all stations weighted equally
• TransCom value 1

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Results the GCV function
Function minimum
Parameter values used in TransCom
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Results inferred CO2 flux (Pg C/ yr)
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Ocean
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Equatorial land
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overall inferred flux distribution
TransCom parameter values
GCV parameter values
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(2) Conclusion and research directions

• Parameter choice explains part of the variability
  in CO2 flux estimates derived from inverse
  methods
• GCV looks promising for empirically choosing
  parameter values in global-scale CO2 inversions,
  e.g. weights for different types of information
• GCV-based parameter choice methods should also be
  useful for studies that try to solve for carbon
  fluxes at high resolution (e.g. NACP)

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3) Regional air-sea gas transfer velocities
estimated from ocean and atmosphere carbon
isotope measurements
GasEx
N. Y. Krakauer, J. T. Randerson, F. W. Primeau,
N. Gruber, D. Menemenlis, submitted to Tellus
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A conceptual model of gas exchange the stagnant
film

• Most of the air-sea concentration difference is
  across a thin (lt0.1 mm) water-side surface layer
• F kw (Cs Ca)
• F gas flux (mass per surface area per time)
• Cs gas concentration in bulk water (mass per
  volume)
• Ca gas concentration in bulk air (partial
  pressure solubility)
• kw gas transfer coefficient (a gas transfer
  velocity)

100 µm
J. Boucher, Maine Maritime Academy
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Measured gas transfer velocities range widely

• Gas transfer velocity usually plotted against
  windspeed (roughly correlates w/ surface
  turbulence)
• Many other variables known/theorized to be
  important wave development, surfactants, rain,
  air-sea temperature gradient
• Several measurement techniques have been used
  all imprecise, sometimes seem to give
  systematically different results

Wu 1996 Pictures WHOI

• Whats a good mean transfer velocity to use?

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..as do parameterizations of kw versus windspeed

• Common parameterizations assume kw to increase
  with windspeed v (piecewise) linearly (Liss
  Merlivat 1986), quadratically (Wanninkhof 1992)
  or cubically (Wanninkhof McGillis 1999)
• Large differences in implied kw, particularly at
  high windspeeds (where there are few
  measurements)
• Are these formulations consistent with ocean
  tracer distributions?

Feely et al 2001
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CO2 isotope gradients are excellent tracers of
air-sea gas exchange
O2 14 d
N2O 17 d
CFC-11 21 d
CO2 295 d
C isotopes 2926 d
ppm
Sample equilibration times with the atmosphere of
a perturbation in tracer concentration for a 50-m
mixed layer
µmol/kg
Ocean carbonate speciation (Feely et al 2001)

• Because most (99) of ocean carbon is ionic and
  doesnt directly exchange, air-sea gas exchange
  is slow to restore isotopic equilibrium
• Thus, the size of isotope disequilibria is
  uniquely sensitive to the gas transfer velocity kw

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Optimization scheme

• Assume that kw scales with some power of
  climatological windspeed u
• kw ltkgt (un/ltungt) (Sc/660)-1/2,
• (where ltgt denotes a global average, and the
  Schmidt number Sc is included to normalize for
  differences in gas diffusivity)
• find the values of
• ltkgt, the global mean gas transfer velocity
• and
• n, the windspeed dependence exponent
• that best fit carbon isotope measurements
• using transport models to relate measured
  concentrations to corresponding air-sea fluxes

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Windspeed varies by latitude
SSM/I climatological wind (Boutin and Etcheto
1996)
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The radiocarbon cycle at steady state

• 14C (?1/2 5730 years) is produced in the upper
  atmosphere at 6 kg / year
• Notation ?14C 14C/12C ratio relative to the
  preindustrial troposphere

Stratosphere 80 90 Pg C
14N(n,p)14C
Troposphere 0 500 Pg C
Land biota 3 1500 Pg C
Air-sea gas exchange
Shallow ocean 50 600 Pg C
Deep ocean 170 37000 Pg C
Sediments 1000 1000000 Pg C
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The bomb spike atmosphere and surface ocean ?14C
since 1950

• Massive production in nuclear tests ca. 1960
  (bomb 14C)
• Through air-sea gas exchange, the ocean took up
  half of the bomb 14C by the 1980s

data Levin Kromer 2004 Manning et al 1990
Druffel 1987 Druffel 1989 Druffel Griffin
1995
bomb spike
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Ocean bomb 14C uptake previous work

• Broecker and Peng (1985 1986 1995) used 1970s
  (GEOSECS) measurements of 14C in the ocean to
  estimate the global mean transfer velocity, ltkgt,
  at 213 cm/hr
• This value of ltkgt has been used in most
  subsequent parameterizations of kw (e.g.
  Wanninkhof 1992) and for modeling ocean CO2
  uptake
• Based on trying to add up the bomb 14C budget,
  suggestions have been made (Hesshaimer et al
  1994 Peacock 2004) are that Broecker and Peng
  overestimated the ocean bomb 14C inventory, so
  that the actual value of ltkgt might be lower by
  25

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Ocean 14C goals

• From all available (17,000) ocean ?14C
  observations, re-assess the amount of bomb 14C
  taken up, estimate the global mean gas transfer
  velocity, and bound how it varies by region
• The 1970s (GEOSECS) observations plus
  measurements from more recent cruises (WOCE)

data Key et al 2004
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Modeling ocean bomb-14C uptake

• Simulate ocean uptake of bomb 14C (transport
  fields from ECCO-1), given the known atmospheric
  history, as a function of the air-sea gas
  transfer velocity
• Find the air-sea gas transfer velocity that best
  fits observed 14C levels

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Results simulated vs. observed bomb 14C by
latitude 1970s

• For a given ltkgt, high n leads to more simulated
  uptake in the Southern Ocean, and less uptake
  near the Equator
• Observation-based inventories seem to favor low n
  (i.e. kw increases slowly with windspeed)

Simulations for ltkgt 21 cm/h and n 3, 2, 1 or
0 Observation-based mapping (solid lines) from
Broecker et al 1995 Peacock 2004
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Simulated-observed ocean 14C misfit as a function
of ltkgt and n

• The minimum misfit between simulations and (1970s
  or 1990s) observations is obtained when ltkgt is
  close to 21 cm/hr and n is low (1 or below)
• The exact optimum ltkgt and n change depending on
  the misfit function formulation used (letters
  cost function contours are for the A cases) , but
  a weak dependence on windspeed (low n) is
  consistently found

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Optimum gas transfer velocities by region

• As an alternative to fitting ltkgt and n globally,
  I estimated the air-sea gas exchange rate
  separately for each region, and fit ltkgt and n
  based on regional differences in windspeed
• Compared with previous parameterizations (solid
  lines), found that kw is relatively higher in
  low-windspeed tropical ocean regions and lower in
  the high-windspeed Southern Ocean (s and gray
  bars)
• Overall, a roughly linear dependence on windspeed
  (n 1 dashed line)

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Simulated mid-1970s ocean bomb 14C inventory vs.
ltkgt and n

• The total amount taken up depends only weakly on
  n, so is a good way to estimate ltkgt
• The simulated amount at the optimal ltkgt (square
  and error bars) supports the inventory estimated
  by Broecker and Peng (dashed line and gray
  shading)

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Other evidence atmospheric ?14C
N

• I estimated latitudinal differences in
  atmospheric ?14C for the 1990s, using observed
  sea-surface ?14C, biosphere C residence times
  (CASA), and the atmospheric transport model MATCH
• The ?14C difference between the tropics and the
  Southern Ocean reflects the effective windpseed
  dependence (n) of the gas transfer velocity

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Observation vs. modeling

• The latitudinal gradient in atmospheric ?14C
  (dashed line) with the inferred ltkgt and n, though
  there are substantial uncertainties in the data
  and models (gray shading)
• More data? (UCI measurements)
• Similar results for preindustrial atmospheric
  ?14C (from tree rings)
• Also found that total ocean 14C uptake
  preindustrially and in the 1990s is consistent
  with the inferred ltkgt

ltkgt (cm/hr)
n
( difference, 9N 54S)
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14C conclusions

• The power law relationship with the air-sea gas
  transfer velocity kw that best matches
  observations of ocean bomb 14C uptake has
• A global mean ltkgt212 cm/hr, similar to that
  found by Broecker and Peng
• A windspeed dependence n 0.90.4 (about linear),
  compared with 2-3 for quadratic or cubic
  dependences
• This is consistent with other available 14C
  measurements

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The ocean is now releasing 13C to the atmosphere
1977-2003
Scripps (CDIAC)

• Notation d13C 13C/12C ratio relative to a
  carbonate standard
• The atmospheric 13C/12C is steadily declining
  because of the addition of fossil-fuel CO2 with
  low d13C this fossil-fuel CO2 is gradually
  entering the ocean

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and the amount can be estimated

• Budget elements
• the observed d13C atmospheric decline rate (arrow
  1)
• biosphere disequilibrium flux (related to the
  carbon residence time) (5)
• fossil fuel emissions (6)
• biosphere (4) and ocean (2) net carbon uptake
  (apportioned using ocean DIC measurements)
• I calculated that air-sea exchange must have
  brought 7017 PgC 13C to the atmosphere in the
  mid-1990s, half the depletion attributable to
  fossil fuels

PgC carbon-13
Pg carbon
Randerson 2004
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but the air-sea d13C disequilibrium is of
opposite sign at low vs. high latitudes
Sea-surface d13C ()
Air-sea d13C disequilibrium ()
data GLODAP (Key 2004)
Temperature-dependent air-sea fractionation ()

• Reflects fractionation during photosynthesis
  temperature-dependent carbonate system
  fractionation
• The dependence of kw on windspeed must yield the
  inferred global total flux

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Simulated 1990s air-sea d13C flux vs. ltkgt and n

• At high n, the 13C flux into the Southern Ocean
  largely offsets the 13C flux out of the tropics
• The observed rate of decline of atmospheric d13C,
  combined with the known fossil fuel emissions,
  suggests a large 13C flux out of the ocean
  (dashed line and gray shading), which requires n
  lt 2

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The air-sea CO2 flux is also of different sign at
high vs. low windspeed regions

• Sea-surface pCO2 is high in the tropics (? flux
  out of ocean) and low in the midlatitudes (? flux
  into ocean)

Takahashi et al 2002
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Implications for ocean CO2 uptake

• We can apply the new parameterization of gas
  exchange to pCO2 maps
• uptake by the Southern Ocean is lower than
  previously calculated (fitting inversion results
  better)
• outgassing near the Equator is higher (reducing
  the required tropical land source)

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3) Conclusions

• 14C and 13C measurements constrain the mean
  air-sea gas transfer velocity and its
  spatial/windspeed dependence, averaged over large
  regions and several years
• The new parameterization promises to increase the
  usefulness of ocean pCO2 measurements for
  answering where carbon uptake is occurring and
  how it changes with time (e.g. tropical land vs.
  ocean)

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3) Questions to pursue

• Might a polynomial match the relationship of the
  gas transfer velocity with windspeed better than
  a power law (e.g. kw is not expected to be zero
  in calm seas)?
• Are there other easily measured quantities, such
  as mean square surface slope or fractional
  whitecap coverage, that predict gas transfer
  velocities better than windspeed?
• Does the dependence on windspeed change if we use
  the same high-resolution winds that drive model
  ocean mixing?
• What are the implications for trace gas budgets?

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Thats all for now
USRA
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Acknowledgements

• Tapio Schneider and Jim Randerson
• Jess Adkins, Paul Wennberg, Don Burnett, Andy
  Ingersoll, Yuk Yung, Jared Leadbetter
• François Primeau, Stan Tyler, Sue Trumbore,
  Xiaomei Xu, John Southon
• Seth Olsen, David Noone, Carrie Masiello, Diego
  Fernández, Ross Salawitch, John Miller, Parvadha
  Suntharalingam, Moustafa Chahine, Qinbin Li
• Lisa Welp, Nicole Smith Downey, Zhonghua Yang
• Betty and Gordon Moore Foundation and NASA for
  graduate fellowships
• The Earth System Modeling Facility for computing
  support