Lecture 4. GFDL Terrestrial Carbon Cycling Model
Elena Shevliakova & Chip Levy
Ocean Biogeochemical and Dynamic Land
Carbon Cycle Modeling
(the GFDL Earth System Model)
John Dunne
GFDL/NOAA
Ron Stouffer
Elena Shevliakova
GFDL/NOAA
Princeton University
Sergey Malyshev
Chris Milly
Steve Pacala
Hiram levy
Princeton University
USGS
Princeton University
GFDL/NOAA
(John.Dunne@noaa.gov)
(Elena.Shevliakova@noaa.gov)
GFDL’s earth system model (ESM) for coupled carbon-climate
Climate
Model
Atmospheric circulation and radiation
Sea Ice
Ocean circulation
Earth System
Model
Land Ice
Land physics
and hydrology
Atmospheric circulation and radiation
Chemistry – CO2, NOx, SO4, aerosols, etc
Sea Ice
Ocean ecology and
Biogeochemistry
Ocean circulation
Land Ice
Plant ecology and
land use
Land physics
and hydrology
The Zero Order View of the Carbon Cycle
(Integrated Assessment Models - IAMs for example)
Fossil Fuels
Atmosphere
CO2 = 280 ppmv (560 PgC) + FF
90
±
100-103 yr
Ocean Circ.
+ BGC
37,400 Pg C + FF
4 yr
60±
Biophysics
+ BGC
2000 Pg C
100-102 yr
…equilibrium takes 103-104 yrs
Resolution
• Cubed sphere, Lat x Lon
– 2 ° x 2.5 ° [atm.]
– 1° x 1 ° [land]
• Time step:
~30 Minutes
• Simulation:
centuries
Current land processes represented in
GFDL’s current ESM
in collaboration with Princeton U., U. New Hampshire and USGS
(Schevliakova et al., 2009)
• Plant growth
– Photosynthesis and respiration – f(CO2, H2O, light, temperature)
– Carbon allocation to leaves, soft/hard wood, coarse/fine roots, storage
• Plant functional diversity
– Tropical evergreen/coniferous/deciduous trees, warm/cold grasses
• Dynamic vegetation distribution
– Competition between plant functional types
– Natural fire disturbance – f(drought, biomass)
• Land use
– Cropland, pastures, natural and secondary lands
– Conversion of natural and secondary lands and abandonment
– Agricultural and wood harvesting and resultant fluxes
Land Model Forcings
Lands use changes
Climate
C & N uptake and release
Photosynthesis
Plant and soil respiration
Plant type
LAI, height,
roots
leaching
labile
fine
roots
Land-use management, t ~ 1 year
Biogeography, t ~ 1 year
Mortality, natural and fire t ~ 1 year
sapwood
Carbon gain
leaves
Phenology, t~ 1 month
C & N allocation and growth, t ~ 1 day
Land energy, water, carbon
and nitrogen exchange
wood
Atmosphere
Energy and moisture balance
Canopy and
canopy air
t~ 30 min
{
Soil/snow
Dynamic Land Model LM3
Vegetation dynamics
Humans
Climate statistics
LM3 structure: sub-grid heterogeneity
Vegetation structure in LM3
5 vegetation types
• C3 and C4 grasses
• temperate deciduous
• evergreen coniferous
• tropical
5 vegetation C pools
2 or 4 soil C pools
Sub-grid land use
• 4 land-use types
• up to 15 tiles for different
ages
Natural mortality and fire
Land and atmosphere are
on the same grid
• 2°x 2.5° in ESMs
• Cube-sphere in CM3
Hydrology
Now For Some Detail
Biosphere-atmosphere exchange: photosynthesis and respiration
Photosynthesis: 6 CO2 + 12 H2O + light → C6H12O6 + 6 O2 + 6 H2O
Carbon Dioxide + Water + Light energy → Glucose + Oxygen + Water
Respiration: C6H12O6 + 6O2 → 6CO2 + 6H2O
C4
photosynthesis
C3
photosynthesis
Response to drying, lower CO2: C4 photosynthesis evolves in plants
•
•
•
•
CO2
CO2+H2O --> CH2O (C3) +O2
or
CH2O+O2 --> CO2+H2O
The enzyme Rubisco catalyzes both reactions.
Oxidation increases at lower CO2.
CO2
C3+CO2 --> C4
(CO2 molecule is
loosely bound to C3
compound
C4
C3
C4 --> C3+CO2
CO2+H2O --> CH2O+O2
or
CH2O+O2 --> CO2+H2O
Advantages of C4 photosynthesis
• Higher CO2/O2 ratio where Rubisco catalyzes photosynthesis, less CH2O oxidation
• Plants can take up CO2 at night, when humidity is high, and not lose water
Consequence: C4 plants do better at low CO2, dry climates
C3 plants - trees and some grasses
C4 plants - other grasses, grains (corn, sorghum, millet)
Carbon fixation
C3, C4 and CAM plants
Carbon Engine – Photosynthesis Model
(Farquhar et al. 1980, Collatz et al. 1992, Leuning 1990)
m  An _ pot

g

, Eq 1
 s _ pot
(Ci   )  (1  ( qsat (Tl )  qca ) d 0 )


g s _ pot
 (Cca  Ci ), Eq 2
 An _ pot 
1
.
6







C


i

 J E  a 3Q


,
Ci  2*






C


 for C 3 : A
i


,   Vm (Tl ), Eq 3C 3
n _ pot  min J C  Vm (Tl )

p
p


Ci  K c (Tl ) ref  (1  O2  K o (Tl ) ref ) 


p
p






Vm (Tl )

Jj 

2




 J E  a 4Q,




for
C
4
:
A

min
J

V
(
T
),

  Vm (Tl ), Eq 3C 4 ,

n _ pot
C
m
l
J


 CO 2  18000Vm (Tl ) Ci 

A system of three equations with three unknowns, the stomatal conductance; gs,the intercellular
concentration of CO2, Ci (mol/mol); and the net photosynthesis, An(mol CO2/m2s), defines the
plant uptake of CO2 and the rate of non-water-stressed transpiration for a thin canopy layer dLAI’
at a temperature Tl(K)receiving an incident photosynthetically active radiation flux Q(LAI’)
(Einstein/m2s) and surrounded by canopy air with vertically uniform specific humidity qca(kg/kg)
and CO2 concentration Cca(mol/mol):
Parameters
a is the leaf absorptance of photosynthetically active radiation,
α3 and α4 are the intrinsic quantum efficiencies,
Vm is the maximum velocity of carboxylase in molCO2/m2s,
Γ*= αco2 [O2] KC /(2KO) is the compensation point,
KC and KO are the Michaelis-Menten constants for CO2 and O2,
[O2] is the atmospheric oxygen concentration,
pref=105 Pa is the reference pressure and p is an atmospheric pressure.
The temperature dependence of the Michaelis-Menten constants, the maximum
velocity of carboxylase, and the compensation point are described by Arrhenius
function where T is the temperature (˚K) and E0 is a temperature sensitivity factor
(Foley et al. 1996)
Equation 13 gives the leaf stomatal conductance for vegetation if the soil water is not
limiting. It links the rate of stomatal conductance for water gs to the net photosynthesis
(An), intercellular concentration of CO2 (Ci), and humidity deficit between intercellular
space and external environment (qsat(Tl) - qca). This equation is a simplification of
Leuning’s (1985) empirical relationship assuming that contribution of cuticular
conductance is negligible.
Equation 14 is a one-dimensional gas diffusion law The factor of 1.6 is the ratio of
diffusivities for water vapor and CO2. We assume that the diffusion of CO2 is mostly
limited by stomatal conductance and not by leaf boundary layer conductance.
Equations 15C3 and 15C4 are based on the mechanistic model of photosynthesis by
Farquhar et al. (1980) and its extensions by Collatz et al. (1991, 1992).
The net photosynthesis is the difference between the gross photosynthesis and leaf
respiration. The gross photosynthesis for C3 plants is the minimum of three limited
rates: the light limited rate JE, the Rubisco limited rate JC, and the export limited rate of
carboxylation Jj. Similarly, in Collatz et al. (1992) the gross photosynthesis rate for C4
plants is the minimum of the light limited rate JE, the Rubisco limited rate JC, and the
CO2 limited rate JCO2. Leaf respiration is computed as Rleaf = γVm(Tl). Although the
formulation of Collatz et al (1991) is widely used in dynamic vegetation and land
surface models, it requires computationally expensive iterative solutions. The
simplifying assumption made in equation 13 that cuticular conductance is negligible,
allows an analytical solution for the three unknowns.
Present Day Simulated Vegetation and Soil C pools
Soil C
observation-based
estimates
model potential veg,
current climate
Veg C
LM3 generates present-day spatial distribution of vegetation and soil carbon
LM3 is designed to diagnose and predict the land use sink
LM3 Predicted Carbon Loss Due To Land Use Change
total
natural
Carbon Loss from 1700 to 2000
natural
kg
Total carbon loss: 228 Gt
Current Pasture Fraction
Current pasture area: 3.1 billion ha
crops
secondary
pasture
/m2
Ecosystem carbon, kg
Current Crop Fraction
Current crop area: 1.4 billion ha
Why secondary vegetation is important ?
No wood harvesting
HYDE
C flux, GT C/yr
SAGE/HYDE
HYDE
SAGE/HYDE
Land-use scenarios from Hurtt et al. 2006
Stand alone LM3V forced by the atmospheric data from the GFDL AM2 model, CO2=350 ppm
Shevliakova et al. 2009
Why do we need a model of vegetation dynamics and C cycle?
Current Models Predict a Big Sink From CO2 Fertilization
2050
Uncertainty about the magnitude of CO2 fertilization is the key factor
determining whether vegetation is a net carbon source or sink
Change in Vegetation Biomass, kgC/m2
No CO2 fertilization
-460Pg
CO2 Fertilization at 700 ppm
+200 Pg
GFDL Slab-Ocean Climate Model SM2.1coupled to Dynamic Land model LM3V
Atmospheric CO2 concentration: 700 ppm
Shevliakova et al. 2006
Transient land C flux and storage, Historic and A1B Future (ESM2.1)
phot_286
GtC
phot_hist
A1B_phot_fert
A1B_phot_286
• Even under assumption of CO2 fertilization, C storage declines after 2100
•Under assumption of “no CO2 fertilization ” land biosphere will undergo a
catastrophic loss of C
Terrestrial Sink
Cumulative Emissions Reductions Necessary to Stabilize at 500 PPM
Fossil Carbon Emissions Reductions
(Gt/y)
170
145
Hypotheses for the
terrestrial sink:
120
95
CO2 Fertilization Sink
Land Use Sink
70
2. Climate Change
45
3. Land Use
20
-5
2000
1. CO2 Fertilization
2010
2020
2030
2040
2050
Year
Solving the carbon problem is twice as hard if the missing sink is caused by
land use instead of CO2 fertilization.
Ocean processes represented in
GFDL’s current ESM
• Coupled C, N, P, Fe, Si, Alkalinity, O2 and clay cycles
• Variable Chl:C:N:P:Si:Fe stoichiometry
• Phytoplankton functional groups
– Small (cyanobacteria) / Large (diatoms/eukaryotes)
– Calcifiers and N2 fixers
• Herbivory - microbial loop / mesozooplankton (filter feeders)
• Carbon chemistry/ocean acidification
• Atmospheric gas exchange/deposition and river fluxes
• Water column denitrification
• Sediment N, Fe, CaCO3, clay interactions
Coupled elemental cycles in the
GFDL global biogeochemical model
Carbon
Oxygen
Phosphorus
DOM cycling
Particle sinking
Atm. Deposition
CaCO3 only
Nitrogen
Iron
Alkalinity/CaCO3
Gas exchange
Solubility pump
Loss from system
River Input
Silicon
Lithogenic
Sediment Input
Scavenging
Ocean ecology in the GFDL global
biogeochemical model
N2-fixers
Recycled
nutrients
Small phyto.
Protists
Filter feeder
DOM
New
nutrients
Large phyto.
Detritus
CO2 Flux
Observations (present)
Model (pre-industrial)
20 Yr Time Series of Southern Hemisphere CO2 Flux
(total and oceanic)
Where are we in the ESM model development process?
Plan to use ESMs for next IPCC (AR5)
– Thousands of years to spin-up and 300-yr runs into the future
– 4 new future scenarios of GHGs and land-use change
– ~40 experiments planned
Atm CO2 anomaly in a control integration
CO2 Anomaly Time Series
Scientific Questions For The Land Model
• How did recent changes in climate, CO2 and land use shape
the present day distribution of land carbon and nitrogen
sources and sinks?
• What are the influences of land cover changes on
continental precipitation and runoff?
• What are the implications of climate change for the
distribution and functioning of terrestrial vegetation? This is
particularly important for agriculture. (Why?)
• What are the terrestrial biosphere feedbacks on climate?
• What is the role of plant diversity in the global
biogeochemical cycles and climate system?
Scientific Questions For The Earth System Model
• How will climate interactions with the Land Model influence
CO2 levels in the atmosphere over the short term?
• How will land use interactions with the Land Model influence
CO2 levels in the atmosphere over the short term?
• What role will CO2 fertilization play in controlling CO2
levels?
• Will ocean biogeochemistry control the long-tem level of
CO2 in the atmosphere and what will it be?
• Two longer-term land wild cards: soil C release in a warmer
Arctic; CH4 release in a warmer Arctic
The End
Summary
• The GFDL land model:
– represents a range of biosphere-climate interactions and
feedbacks;
– captures effects of both climate change and land use on
vegetation dynamics and structure;
– simulates historic and future distribution of Carbon sources
and sinks;
– Will characterize coupled Carbon-Nitrogen dynamics in plants
and soils.
• Upcoming improvements include increased biodiversity, seasonal
fire, N and P cycles, and ecological data assimilation for formal
parameter estimation.
• Currently there is considerable uncertainty about the magnitude
of climate effects on biosphere and its feedbacks.
GFDL LM3 Functionality
•
•
•
•
•
Land surface parameterization:
– energy, water, and momentum exchange
Hydrological processes:
– River flow, water resource development and use, extreme
events
Ecological processes:
– vegetation functioning, structure, distribution, disturbance*
(natural and anthropogenic), and succession*
Carbon cycling
– CO2 fluxes, vegetation and soil carbon pool
Land use and management*
* These are relatively unique features
A Computer Model is:
• a theoretical/numerical construct that represent a set of
particular processes and phenomena
– a set of variables – input, output, state, parameters
– a set of logical and quantitative relationships between
them
– a set of assumptions
• Idealized logical framework to test hypotheses and to ask
scientific questions
Historic C emissions from anthropogenic pools simulated by LM3
Malyshev et al., 2009
Above Ground Biomass (AGM) vs Annual mean Temperature
Lichstein et al. in prep (2009)
AR5 RCPs
(van Vuuren et al. 2008)
• New scenarios are developed for the next IPCC
assessment
(pre-ind. to present day +2.3 W/m2, IPCC AR4)