Transcript Document

The Impact of Methane Clathrate Emissions on the Earth
System
Philip Cameron-Smith1, Subarna Bhattacharyya1, Daniel Bergmann1, Matthew Reagan2, Scott Elliott3 and George Moridis2
1
Lawrence Livermore National Laboratory, 2 Lawrence Berkeley National Laboratory, 3Los Alamos National Laboratory
Location of emission has some
effect on climate
Methane emissions
may change variability
Methane emissions change
interannual autocorrelation
Expected methane sources due to warming
WeWe
developed
a chemistry-climate
of CESM
added a fast chemical
mechanism to CESMversion
that is designed
to
There appears to be difference the interannual
variability between AE, UE, and control
The year-to-year auto correlation in southern
ocean seems to be reduced
Methane conc. increases non-uniformly
Glob
al
Arctic
10x
scenari
os
Annual temperature (K)
A
E
1
0
x
Onset of Clathrate emissions expected to be abrupt
UE1
0x(fi
Uxed)
E
1
0
x
Interannual variability in zonal-mean
temperature changes
Note that methane suppresses the specie that destroys it, so a 3x
increase in total methane emissions (10x clathrates) produces 6-8x
methane concentration increase over our control (present-day).
Temperature increase is modestly dependent on
Emission location
10x
scena
rio
Reagan, et al.,
2011
This is the sediment response to a temperature ramp of 5K for 100
years.
This emission rate is ~20% of global methane emissions.
Most of the emission comes from 300-400m depth.
% methane released to atmosphere
(no methanotrophs)
Fraction of methane that passes through
ocean is uncertain, but could be large
Auto-correlation important for uncertainty
Latitude
LEFT: Zonal mean surface temperature increase over control
(AE=Red, UE=Blue, UE10x(fixedCH4)=Green, 2xCO2=Cyan,
4xCO2CMIP=Magenta). RIGHT: same data, but expressed as
%difference for AE over UE for different regions (GL=globe,
SP=south pole, LL=low latitudes, NP=north pole). The error bars are
the uncertainty in the mean. The UE simulation is slightly warmer
than the AE scenario for almost all latitudes except the Arctic. The
modest difference in the Arctic seems to be a compensation between
increased warming from extra methane in AE, with greater poleward
heat transport in UE.
Variability decreases for El Nino and Sea-ice
AE10x
UE10x
UE10x(fixedCH4)
2xCO2
4xCO2CMIP
Methane is consumed in the ocean by methanotrophs.
But, bubble plumes may inject methane to upper ocean levels which
will allow faster release to the atmosphere.
•
Couple our atmospheric methane model to ocean and
permafrost methane codes.
Determine emission amplification factors, ie the amount of extra
methane released due to the warming from the original methane
emission (cross-amplification between reservoirs will also
occur).
Assess the likelihood of runaway warming (aka, the clathrate
gun).
Participate in future methane related model intercomparisons
(we participated in the Atmospheric Chemistry-Climate Model
Intercomparison Project (ACCMIP), which helped confirm and
debug our model chemical behavior, and resulted in several
papers).
Acknowledgements
We acknowledge the contribution of our collaborators, who have
primary responsibility for the ocean model (S.Elliott & M.Maltrud,
LANL) and sediment model (M.Reagan & G. Moridis, LBNL). We
also acknowledge J.Stolaroff (LLNL) for including us in a review for
technical mitigation measures for methane.
Annual-mean surface ozone increase due to clathrate emission (vmr)
Methane is an important precursor for chemical smog, and the 1x and
10x clathrate emissions increase ozone concentrations by ~5ppb and
~35ppb in polluted regions, respectively. The ozone increase is likely
to be even greater during pollution events.
Future plans
•
•
10x
scenari
os
Seafloor
Months since start of simulation
The dots are the variability in the means of each time window of the
specified length within the 400 year simulations (with different starting
years when possible). The circles are the standard error formula
without any autocorrelation correction. The difference is due to autocorrelation.
•
10x
scen
ario
50 m
depth
150 m
depth
Red Dots: Arctic Emission
Black Dots: Control
Length of time-window (years)
There seem to be changes roughly proportional to the level of global
radiative forcing at several latitudes (indicated by arrows). In many
cases the decreases are clearly related to sea-ice. In the zonal
means, the difference between AE and UE is hard to distinguish from
the uncertainty (1 sigma ~ 0.04). Note: the various 4xCO 2 runs are
very short, so their variability is much more uncertain.
Ozone increases most in polluted regions
Elliott, et al., 2010,
2011
Lattitude
The lag-1 autocorrelation of the annual time series shows the degree
of predictability from one year to the next. It shows the importance of
the long-term climate modes, and is also important for quantifying the
uncertainty in time-series quantities. Red = AE, Blue = UE, black =
control, black-dash = UE10x(fixedCH4), thin colored lines are Monte
Carlo realizations with control statistics, to indicate confidence. The
three methane runs show decreased predictability in southern ocean.
Uncertainty in surface
temperature (K)
Clathrates are methane locked in a water ice structure.
ESAS = East Siberian Arctic Shelf (methane under submerged
permafrost)
10x
scenario
s
Ratio of standard deviations of
zonal-mean surface temperatures to control
Stolaroff, et al.,
2012
The increased methane variability in AE over UE (from the effect of
synoptic weather patterns on the clathrate plumes) seems to affect
the PDFs of the annual temperature. The effect on the Arctic isn’t as
noticeable because it is already a highly variable region.
Note that the mean, std. dev., and skewness all seem to be affected.
10x
scenari
os
Lag-1 autocorrelation coefficient
handle methane . We simulated over 600 years (after spinup) under
present-day conditions with 1x and10x expected clathrate emissions
(AE), and the same amount of extra emission spread uniformly over
the globe (UE). We used an active ocean to see the coupled
chemistry-climate response.
PDF of annual temperatures
Warming may release methane from
large Arctic reservoirs
The spatial pattern of the change in the standard deviation of the
annual mean surface temperatures looks like it is mostly a function of
the radiative forcing in the scenario.
This research used resources of the National Energy Research
Scientific Computing Center, which is supported by the Office of
Science (BER) of the U.S. Dept. of Energy under Contract No. DEAC02-05CH11231
SPARC Meeting, Queenstown, 2014
June 2014
More than 900 organizations in over 200 countries
Climate Action Network calls for phasing out all fossil fuel emissions and phasing in a 100% renewable
energy future with sustainable energy access for all, as early as possible, but not later than 2050.
CAN believes that global average surface temperature warming should be limited to less than 1.5°C above pre-industrial
levels by 2100.
Eventually emissions (carbon) must be brought. to zero.
od security, sea level rise or ocean acidification, are occurring with more intensity than previously anticipated. These
impacts will be disruptive for all countries; especially for the global poor and vulnerable peoples.
September 2014 Sea ice low results
Average monthly Arctic sea ice extent September 1997-2014
Comment. enormous rapid loss of Arctic
summer sea ice albedo cooling continues
Arctic sea ice extent averaged for
the month of September 2014 was
5.28 million square kilometers
(2.04 million square miles), also
the 6th lowest in the satellite
record. This is 1.24 million square
kilometers (479,000 square miles)
below the 1981 to 2010 average
extent NSIDC
Sept Age of Ice
NSIDC
PIOMAS retrospective
sea ice volume model
NSIDC sea ice index
extent + volume
NSIDC
Today climate change rate
PETM climate change rate
PETM worst mass
die off on Earth
End Permian extinction