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Interactive C-cycle in
Earth System models
Helge Drange
[email protected]
Mean change vs uncertainty
Most of the effort
Helge Drange
Geophysical Institute
University of Bergen
IPCC (2007)
Mean change vs uncertainty
Most of the impact
Most of the effort
Helge Drange
Geophysical Institute
University of Bergen
Goal:
Improve knowledge and
by that better quantify
and, over time,
reduce uncertainty
IPCC (2007)
Ex: Long lived GHG warming vs aerosol cooling
IPCC (2007)
Helge Drange
Geofysisk institutt
Universitetet i Bergen
Ex: Long lived GHG warming vs aerosol cooling
IPCC (2007)
Helge Drange
Geofysisk institutt
Universitetet i Bergen
Ex: Long lived GHG warming vs aerosol cooling
IPCC (2007)
Helge Drange
Geofysisk institutt
Universitetet i Bergen
Ex: Long lived GHG warming vs aerosol cooling
How and
what if?
Uncertainty about
magnitude (not sign)
of radiative forcing
IPCC (2007)
Helge Drange
Geofysisk institutt
Universitetet i Bergen
Size and stability of Earth’s
carbon reservoirs
Reference numbers (ca)
(i) Human induced emissions of CO2 per year:
10 Gt-C
(ii) Human generated emissions of carbon, 1850-2010:
300 Gt-C
(iii) Fossil reserves:
5000 Gt-C
Helge Drange
Geofysisk institutt
Universitetet i Bergen
Very
likely
Likely
Unlikely
Highly
unlikely
Gruber et al. (2004)
10
100 Gt-C
1000
Very
likely
Land
Terrestrial
biomass
Likely
Unlikely
Permafrost
Highly
unlikely
Gruber et al. (2004)
10
100 Gt-C
1000
Very
likely
Land
Terrestrial
biomass
Likely
Unlikely
Permafrost
Stability being
discussed
Highly
unlikely
Gruber et al. (2004)
10
100 Gt-C
1000
Very
likely
Ocean
Soft tissue
pump
Likely
Unlikely
Methane
hydrates
Highly
unlikely
Gruber et al. (2004)
10
100 Gt-C
1000
Very
likely
Ocean
Soft tissue
pump
Likely
Unlikely
Methane
hydrates
Lack of
knowledge
Highly
unlikely
Gruber et al. (2004)
10
100 Gt-C
1000
Size and stability of Earth’s
carbon reservoirs
Summary:
Large reservoirs of carbon are found on land and in
the ocean. These reservoirs have the potential to
greatly influence Earths climate
(pending on time scale and degree/speed of warming)
Helge Drange
Geofysisk institutt
Universitetet i Bergen
Climate projections
Traditional approach
EMISSIONS
CONCENTRATIONS
CO2, methane, etc.
Off-line scenarios from
population, energy,
economics models
Off-line carbon cycle
and chemistry models
HEATING EFFECT
‘Climate Forcing’
CLIMATE CHANGE
Coupled climate
models
Temp, rain, sea-level, etc.
IMPACTS
Flooding, food supply, etc.
Helge Drange
Geophysical Institute
University of Bergen
Off-line impacts
models
Climate projections
Biogeochemical feedbacks included
EMISSIONS
CONCENTRATIONS
CO2, methane, etc.
Off-line scenarios from
population, energy,
economics models
Off-line carbon cycle
and chemistry models
HEATING EFFECT
‘Climate Forcing’
CLIMATE CHANGE
Coupled climate
models
Temp, rain, sea-level, etc.
IMPACTS
Flooding, food supply, etc.
Helge Drange
Geophysical Institute
University of Bergen
Off-line impacts
models
Climate projections
Earth System Model
EMISSIONS
CONCENTRATIONS
Off-line scenarios from
population, energy,
economics models
Earth System Model
CO2, methane, etc.
HEATING EFFECT
‘Climate Forcing’
Standard for
the IPCC AR5
(due 2013/14)
CLIMATE CHANGE
Temp, rain, sea-level, etc.
IMPACTS
Flooding, food supply, etc.
Helge Drange
Geophysical Institute
University of Bergen
(future ?)
Off-line impacts
models
Land processes
Biogeochemical
processes on land
Arneth et al., Nature Geosci. (2010)
Biogeochemical
processes on land
Arneth et al., Nature Geosci. (2010)
Biogeochemical
processes on land
Arneth et al., Nature Geosci. (2010)
Biogeochemical
processes on land
Arneth et al., Nature Geosci. (2010)
Tropospheric O3  NPP
Biogeochemical
processes on land
Arneth et al., Nature Geosci. (2010)
Soil NOx +BVOC  O3 formation & CH4 lifetime
Biogeochemical
processes on land
Similar for the ocean.
Key challenge: To identify
and understand zero-order
processes
(on the spatial and temporal
scale of interest)
Arneth et al., Nature Geosci. (2010)
BVOC  Biogenic secondary aerosols
Early findings
Helge Drange
Geophysical Institute
University of Bergen
Enhanced warming with interactive carbon cycle?
 w/interactive CO2
Standard SRES A2
(IPCC AR4)
Helge Drange
Geophysical Institute
University of Bergen
Friedlingstein et al. (2006)
Enhanced warming with interactive carbon cycle?
 w/interactive CO2
Standard SRES A2
(IPCC AR4)
Tendency for more CO2 remaining in the
atmosphere, and for additional warming
 w/interactive CO2
Standard SRES A2
(IPCC AR4)
Helge Drange
Geophysical Institute
University of Bergen
Friedlingstein et al. (2006)
CO2 flux from ocean to atmosphere
(from EU project ENSEMBLES)
6
4
Hadley
IPSL
MPI
INGV
Bjerknes
Model mean
Gt-C / yr
2
0
-2
-4
-6
1850
1900
Johns et al., Clim. Dynamics (2011)
1950
2000
2050
2100
CO2 flux from ocean to atmosphere
(from EU project ENSEMBLES)
6
4
Hadley
IPSL
MPI
INGV
BCCR
Model mean
Gt-C / yr
2
Reduced ocean uptake of CO2 is
mainly caused by increased
temperature in the ocean
surface waters
 Reduced CO2 solubility
 Enhanced stratification and
reduced vertical mixing
Partly also reduced
biological production
0
-2
-4
-6
1850
1900
Johns et al., Clim. Dynamics (2011)
1950
2000
2050
2100
CO2 flux from land to atmosphere
(from EU project ENSEMBLES)
6
4
Hadley
IPSL
MPI
INGV
Bjerknes
Model mean
Gt-C / yr
2
0
-2
-4
-6
1850
1900
Johns et al., Clim. Dynamics (2011)
1950
2000
2050
2100
Two degrees target
Helge Drange
Geophysical Institute
University of Bergen
Permissible emissions with interactive CO2
SP550
SP1000
Stabilization at SP550 requires a cumulative 24%
reduction of permissible emissions due to positive
carbon cycle feedback (23% for SP1000)
Helge Drange
Geophysical Institute
University of Bergen
MIROC integrated Earth System Model (Kawamiya et al.)
Ω (saturation state of calcite)
Ocean acidification (and timescales involved)
Helge Drange
Geophysical Institute
University of Bergen
Ilyina & Zeebe (2012)
Short-term confusion &
long-term gain
(or academic learning phase vs practical applicability)
Helge Drange
Geophysical Institute
University of Bergen
Increased complexity will, generally, lead to
(an apparent) growth in model uncertainty,
but overall improvement over time
Simulated
quantity
Uncertainty
Communication
challenge!
Observed (true) value
Time
2012
AOGCM  ESM
A few practical and pragmatical marks
✔
Projections, commitments, long-term changes and irreversibility…
calls for ESMs
✔
Model verification
Common experience that dynamic biogeochemisty in AOGCMs
uncover weaknesses in the model's physics, dynamics and/or numerics
obs
Model evaluation
Availability of relevant observations in stead of lot's of “tuning” parameters
obs
Interdisciplinarity
Math/phys based sciences + biology/chemistry/geology/social sci’s
!
Model compexity vs
Model resolution, long integrations, ensemble integrations
!
Model diversity
Few very complex and interacting models vs many simplified models
!
Model spin-up
Physical vs biogeochemical model