Download An updated view of tipping points and the relevance for long

An updated view of tipping points and
the relevance for long-term climate
goals
November 2014
Authors: Peter Good1, Jason Lowe1, Jeff Ridley1, Jonathan Bamber2,
Tony Payne2, Ann Keen1, Julienne Stroeve3, Laura Jackson1, Meric
Srokosz4, Gillian Kay1, Anna Harper5, Bart Kruijt6, Eleanor Burke1, Ben
Abbott7, Fiona O’Connor1, Tim Minshull8, Carol Turley9, Phillip
Williamson10
1
Met Office Hadley Centre, Exeter, UK
2
School of Geographical Sciences, University of Bristol, UK
3
National Snow and Ice Data Centre, University of Colorado, Boulder, USA
4
National Oceanography Centre, Southampton, UK
5
Department of Mathematics, University of Exeter, UK
6
Alterra, Wageningen UR, Wageningen, the Netherlands
7
Department of Biology and Wildlife, University of Alaska Fairbanks, Fairbanks, AK, USA
8
Ocean and Earth Science, National Oceanography Centre Southampton, University of Southampton, UK
9
Plymouth Marine Laboratory, Prospect Place, Plymouth
10
School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ and NERC
Version: 2.0
Reference: AVOID 2 WPA.5 Report 1
Funded by
Acknowledgements
Carol Turley and Phillip Williamson received support from the UK Ocean Acidification research
programme funded by NERC, Defra and DECC.
This work was supported by AVOID 2 programme (DECC) under contract reference no. 1104872
For more information about the AVOID 2 programme visit www.avoid.uk.net
2
Executive summary
This report summarises the key new literature on the main large-scale systems that may
feature abrupt and/or irreversible changes (specifically, ice sheets, Arctic sea ice, the
Atlantic Meridional Overturning Circulation (AMOC), tropical forests, carbon stored in
terrestrial permafrost or below the ocean in permafrost or as methane hydrates, or the
response to ocean acidification). This represents an update to the review of Good et al.
(2011), and it has been approximately 2 years (18 months) since the submission
deadlines for literature for the IPCC AR5 working group I (working group II); the
corresponding deadlines for acceptance of literature were 18 months (1 year) ago.
The key findings are summarised in Table 1. Overall, this represents substantial progress
since the review of Good et al. (2011) in terms of new observations and improved
understanding of the risks and consequences of significant change in these systems.
Large uncertainties do remain: observed changes may be negligible or partly masked by
internal variability; some biases or missing processes in global climate models make their
results challenging to interpret; and studies of the consequences of these changes are
often from just one or a few models (in part because the potential consequences can be
diverse). Nonetheless, these systems, together, represent substantial potential risks that
need ongoing study. The paleoclimate evidence for threshold behaviour in the deep past
remains strong. This shows that the earth can exhibit thresholds, although it is hard to
interpret in terms of the likelihood of human activity causing these thresholds to be
crossed, and new studies do not change this view.
The risk of interactions between different systems – and with other parts of the climate
system – remains a possibility, but work is very limited here. The next generation of earth
system models, which are in development, may improve this situation. It is also important
to bear in mind potential unknown unknowns: there may be important earth system
thresholds that have yet to be considered.
System
Ice sheets
Key findings
• Ice sheets are the largest potential source of future sea level
rise and are the most uncertain.
• Current sea level rise contributions are: around 0.7mm/yr from
Greenland (which is accelerating); 0.3 from the West Antarctic
Ice Sheet (WAIS).
• From Greenland, the proportion of loss from surface melt
has increased, becoming more consistent with long term
model projections. The bedrock topography of the WAIS lends
itself to an inherently unstable ice sheet. Some degree of
irreversible loss may have begun, although the eventual
magnitude and rate of this irreversible loss is uncertain. Upper
limit on the associated sea-level rise are: 3.3m for the WAIS
and 4-5m for the EAIS.
3
•
•
•
Arctic sea ice
•
•
•
•
•
AMOC
•
•
•
•
•
Tropical forests
•
There are indications that the East Antarctic Ice Sheet
(EAIS) and the northeast Greenland ice stream may be
more sensitive to climate change than previously expected.
Greenland loss could be irreversible, associated with a lowering
of elevation through surface melt. The global-mean warming
threshold for irreversible loss has been estimated to be only
0.8–3.2 °C (best estimate 1.6 °C) above pre-industrial.
New paleoclimate evidence for: 1) periods of relatively
abrupt Antarctic mass loss following the last glacial
maximum; 2) during the early Holocene (sustained
warming ~2K above pre-industrial), WAIS mass loss rates
comparable to present-day, but no WAIS collapse.
There is evidence of ongoing substantial decline in mean ice
cover since 1980 and thickness since ~2005.
An observationally-constrained estimate of the onset year of
nearly ice-free Arctic summers found the range to be 20402060 (for the climate scenario RCP8.5).
The projections from CMIP5 models are more closely aligned
with observations than those from CMIP3, but the spread
across models has not reduced.
There is observational evidence that the rate of decline of
September ice extent has accelerated, although this may in part
be due to natural variability.
It is thought that Arctic sea-ice loss is reversible on cooling,
although in some models abrupt change in sea-ice area does
occur during the loss of winter sea-ice (at global warming of
6.5-7.5°C).
The observed AMOC overturning has decreased from 20042012, linked with decreases in subsurface density in the
sub polar gyre. It is unclear at this stage whether this
AMOC decrease is forced or is internal variability.
Bi-stability (i.e. including a stable 'off state') for the AMOC has
been simulated in a (coarse-resolution) global circulation model
for the first time.
There has been better understanding of the conditions
permitting AMOC bi-stability.
CMIP5 models show some improvement in simulating observed
conditions, but substantial biases remain.
There have been more studies on potential impacts of AMOC
collapse, focussing on the Amazon and Europe (two key areas
sensitive to the AMOC).
Tropical forests represent a large carbon sink (~1.2 Pg/yr over
4
•
•
•
•
•
Terrestrial
permafrost
•
•
•
•
Subsea
permafrost and
ocean methane
hydrates
•
•
1990-2007). They also have important regional biophysical
effects on energy and water cycles, and feature high
biodiversity.
They are subject to complex combined anthropogenic effects
from CO2, climate and land-use.
Major Amazon droughts occurred in 2005, 2010. Their study led
to greater confidence that the Amazon can be adversely
affected by drought: both directly and through fire.
There is more evidence on important regional land-use and
land management effects: notably that evapotransipration is
substantially reduced by deforestation. For some forest regions,
forest fragmentation could be the dominant human driver of
future fire increase.
The south-south-eastern Amazon has been identified as
particularly vulnerable to combined potential changes in landuse and climate. Similar statements have been made for
African rainforests.
New climate models continue to suggest that basin-scale
Amazon dieback from climate alone (as in the HadCM3 model)
is not typical. However, these studies lack some key processes.
Large amounts of carbon are stored in terrestrial permafrost,
which may be destabilised by warming. This release (as CH4 or
CO2) would be effectively irreversible over the near term: a
feedback absent from CMIP5 models.
The amount and rate of future release is highly uncertain.
CMIP5 models feature large biases in permafrost extent.
Observations show Arctic surface air temperatures warming at
twice the global rate and an increase in maximum summer thaw
depth over the past 15 years. Field observations show postthaw release of old carbon.
Under RCP8.5, much of the near-surface permafrost is
projected to thaw by 2100. There is large uncertainty in the
amount of carbon released (0.5% to 50% of top-3m carbon –
from offline calculations). This under-estimates long-term
committed loss, due to lags in carbon release.
These carbon stores may be destabilised by warming. Any
such release would be effectively irreversible.
The presence and location of West Spitsbergen methane
gas plumes have been confirmed. Observations also
confirmed release of methane into shallow waters of the East
Siberian Arctic sea. It is not clear to what extent these plumes
are forced by anthropogenic warming: they may have been
ongoing for thousands of years.
5
•
•
Ocean
acidification
•
•
•
•
•
Few studies exist on the future fate of subsea permafrost and
ocean methane hydrate carbon. Although catastrophic release
cannot be ruled out entirely, current available estimates suggest
that methane release rates to the atmosphere will probably be
low compared to other methane sources.
Methane is also produced in surface water: all Arctic sources
must be known to understand the full implications of Arctic
climate change.
Observations show a clear decrease in seawater pH (increase
in acidity), with a few emerging observations of biological
responses likely to be attributable to this.
Large (>150%) increases in ocean acidity are projected by 2100
under RCP8.5.
The impacts of ocean acidification combine with ocean warming
Over the next few decades, ecosystems are at increasing risk
of being negatively affected. This includes risks to productivity
of fisheries and aquaculture.
A wide range of sensitivities is found, both regionally and
across species. Large areas of the polar oceans could become
corrosive to unprotected shelled organisms within next few
decades.
Table 1. Key findings for each system. Post-AR5 developments are in bold.
6
Table of Contents
Executive summary ........................................................................................................3
1. Introduction .................................................................................................................9
2. Ice Sheets .................................................................................................................. 11
3
4
5
2.1
Introduction ....................................................................................................... 11
2.2
Observed recent changes ................................................................................. 12
2.3
Potential for dangerous change......................................................................... 13
2.4
Potential consequences .................................................................................... 15
2.5
Cautions (uncertainties) .................................................................................... 16
2.6
Comparison with AR5 ....................................................................................... 16
Arctic Sea Ice ........................................................................................................ 17
3.1
Introduction ....................................................................................................... 17
3.2
Observed recent changes ................................................................................. 17
3.3
Potential for dangerous change......................................................................... 18
3.4
Potential consequences .................................................................................... 19
3.5
Cautions (uncertainties) .................................................................................... 20
3.6
Comparison with AR5 ....................................................................................... 20
AMOC .....................................................................................................................21
4.1
Introduction ....................................................................................................... 21
4.2
Observed recent changes ................................................................................. 21
4.3
Potential for dangerous change ...................................................................... 22
4.4
Potential consequences .................................................................................. 23
4.5
Cautions (uncertainties) ................................................................................. 24
4.6
Comparison with AR5 ....................................................................................... 24
Tropical forests .................................................................................................... 25
5.1
Introduction ....................................................................................................... 25
5.2
Observations ..................................................................................................... 26
5.3
Potential for dangerous change......................................................................... 27
5.4
Potential consequences .................................................................................... 29
5.5
Cautions (uncertainties) .................................................................................... 30
5.6
Comparison with AR5 ....................................................................................... 30
7
6
Terrestrial permafrost .......................................................................................... 31
6.1
Introduction ....................................................................................................... 31
6.2
Observed recent changes ................................................................................. 31
6.3
Potential for dangerous change......................................................................... 33
6.4
Potential consequences .................................................................................... 36
6.5
Cautions (uncertainties) .................................................................................... 36
6.6
Comparison with AR5 ....................................................................................... 36
7
Ocean methane hydrates and subsea permafrost .............................................. 37
7.1
Introduction ....................................................................................................... 37
7.2
Recent Observations ......................................................................................... 37
7.3
Potential for dangerous change......................................................................... 39
7.4
Potential consequences .................................................................................... 40
7.5
Cautions (uncertainties) .................................................................................... 40
7.6
Comparison with AR5 ....................................................................................... 40
8
Ocean acidification ................................................................................................ 41
8.1
Introduction ....................................................................................................... 41
8.2
Observed recent changes ................................................................................. 41
8.3
Potential for dangerous change......................................................................... 41
8.4
Potential consequences .................................................................................... 42
8.5
Cautions (uncertainties) .................................................................................... 43
8.6
Comparison with AR5 ....................................................................................... 43
9
Conclusions .......................................................................................................... 44
10
References (grouped by system) .................................................................... 45
10.1 General ............................................................................................................ 45
10.2 Ice Sheets ........................................................................................................ 45
10.3 Arctic Sea Ice .................................................................................................... 48
10.4 AMOC ...............................................................................................................50
10.5 Tropical forests ................................................................................................. 52
10.6 Terrestrial permafrost ........................................................................................ 55
10.7 Ocean methane hydrates and subsea permafrost ............................................. 58
10.8 Ocean acidification ............................................................................................ 59
8
1. Introduction
While some aspects of climate change can be viewed as becoming proportionately larger
with increasing forcings, other aspects may feature more complex, nonlinear behaviour
(e.g. Lenton et al., 2008). This can include abrupt and/or irreversible change, which may
be associated with key thresholds. Such behaviour must be considered differently in
assessments of the potential benefits of mitigation: it implies, for example, that certain
impacts could be significantly different above certain levels of anthropogenic interference.
Clear evidence of threshold behaviour in the earth system is seen in the paleoclimate
record (McNeall et al., 2011). For example, central Greenland temperatures inferred from
ice cores (Figure 1) show relatively abrupt changes, even though the forcing over this
period has evolved smoothly. These changes are thought in part to be associated with
changes in the ocean’s thermohaline circulation (e.g. Broecker, 2003), although strong
paleoclimate evidence for threshold behaviour in major ice sheets and methane
reservoirs in particular also exists (McNeall et al., 2011).
Figure 1. Central Greenland temperature in the last 49,000 years, from the GISP2 ice
core record (reproduced from McNeall et al., 2011; data from Alley, 2000).
Major systems that may feature threshold behaviour include (Good et al., 2011): ice
sheets, Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), tropical
forests, carbon stored in terrestrial permafrost or below the ocean in permafrost or as
methane hydrates, or the response to ocean acidification. The risk of significant change in
these systems is not necessarily linked to large-scale warming alone. Patterns of
precipitation can be important for the AMOC and tropical forests; tropical forests are also
9
strongly affected by anthropogenic land-use and a direct effect of carbon dioxide, while
ocean acidification arises directly from increased atmospheric CO2 (although its impacts
combine with those of ocean warming).
Consequences of change in these systems range from amplified global warming through
altered climate patterns, elevated sea-level and direct loss of biodiversity and ecosystem
services (Table 3; see individual sections below for details). These systems can in
principle interact with each other (Lenton et al., 2008), although this is explored in only a
few studies. Examples mentioned below include a possible effect on Amazon productivity
from AMOC collapse (although the sign of change is uncertain), and reduced stability of
permafrost carbon through loss of Arctic sea-ice.
Good et al. (2011) reviewed the literature on these systems (excluding ocean
acidification) as an update to the fourth IPCC assessment report (up to October 2010).
Here we provide a further update, focussing on the same systems, with the addition of
ocean acidification. We report primarily on new literature subsequent to that reviewed by
Good et al. (2011). We also highlight any key post-AR5 developments: it has been
approximately 2 years (18 months) since the submission deadlines for literature for the
IPCC AR5 working group I (working group II); the corresponding deadlines for
acceptance of literature were 18 months (1 year) ago.
This review was prepared using an iterative approach, by specialists both within and
external to the Met Office Hadley Centre. Initial drafts of each section were prepared by
the Met Office, then sent to external experts for review and editing (except that for Ocean
Acidification; prepared by experts in the National Oceanography Centre in Southampton,
and the Plymouth Marine Laboratory). The sections were revised accordingly by the Met
Office, then sent to the external experts for a second review.
Each system is addressed in a separate section below, each with the following
subsections: Introduction (the key issues for that system); Observations (relevant realworld observations); Potential for dangerous change (literature addressing the question of
how likely significant change is); Consequences (of significant change); and Cautions
(key scientific uncertainties).
10
2. Ice Sheets
2.1
Introduction
Ice-sheet mass loss from the Greenland and Antarctic ice sheets, is of concern due to its
impact on global sea level (Alley et al, 2005), and potential amplification of global
warming over long timescales as low-albedo land surface is exposed (Hansen et al.,
2008). The ice sheets are the largest potential source of future sea level rise on many
time-scales as well as the most uncertain. They contain enough ice to raise mean sea
level by some 65 m. In addition, rapid mass loss may have an influence on ocean
circulation.
In a state of equilibrium, an ice sheet loses mass through the melting and calving of its
outlet glaciers at the same rate as it gains mass through the accumulation of snowfall
(Alley et al, 2005). Increased ice sheet mass loss occurs through two main mechanisms
(van den Broeke, 2009). Increased surface melt is largely driven by higher air
temperatures. ‘Dynamic thinning’ (i.e. losses due to increased solid ice discharge into the
ocean) involves glacier acceleration and consequent increases in iceberg calving for
marine-terminating glaciers. This may be induced by increased surface melt but also by
ocean-related processes such as changes in ocean heat content and/or circulation
beneath floating ice or at the terminus.
Ice shelves, the floating portions of outlet glaciers, play a key role in modulating the mass
balance of the Antarctic ice sheet. They buttress the inland glaciers helping to control the
rate of ice leaving the continent and entering the ocean (Dupont & Alley, 2005). Ice
shelves are exposed to the underlying ocean and may weaken as ocean temperatures
rise. If they melt rapidly or break away, ice flow accelerates, causing net ice-sheet mass
loss (De Angelis & Skvarca, 2003). Much of the West Antarctic Ice Sheet (WAIS) is
grounded on bedrock below sea level on retrograde slopes (deeper inland). This
configuration is believed to be inherently unstable and sensitive to small changes in the
grounding line (where the ice begins to float; Mercer, 1968, Schoof, 2007).
There is a temperature threshold above which ice sheets are no longer viable (Gregory
and Hubrechts, 2006, Robinson et al 2012). This is because, as temperatures increase,
so does melting, which results in a lowering in surface elevation, causing further warming
(atmospheric temperature decreases with altitude). This positive feedback is known as
the small ice cap instability (Crowley & North 1988).
Key issues addressed by recent studies include: what the observed ice-sheet loss implies
for the rate of future sea-level change, the potential long-term sea-level rise, and the
possibility of abrupt or irreversible changes.
11
2.2
Observed recent changes
Currently, ice loss from the Amundsen Sea sector of the West Antarctic Ice Sheet (WAIS)
contributes 0.28 mm yr-1 to global sea-level rise. Pine Island glacier (Favier et al., 2014)
and Thwaites glacier (Joughin et al., 2014) are the principal outlets of the WAIS that have
rapidly thinned, retreated, and accelerated. The spatial pattern of thinning suggests that
the loss of grounded ice is the direct result of increased basal melting of the ice shelf, as
a consequence of the inflow of warm water from the southern Pacific (Jacobs et al., 2011;
Ha et al., 2014). In addition there have been synchronous advances and retreats of the
tide-water glaciers of the East Antarctic Ice Sheet (EAIS) (Miles et al., 2013), associated
with changes in the Southern Annular Mode (SAM). Such changes suggest that ice loss
from the EAIS is more sensitive to climate change than had previously been expected.
Figure 2. Accelerating Greenland mass loss over the period 2000-2012 (from Enderlin et al.,
2014). Cumulative mass change (black) due to discharge change (blue) with respect to 1996 and
(red) surface mass balance change with respect to the 1961–1990 mean. Shading indicates
uncertainty. Discharge uncertainty is shown but is visually indistinguishable.
The Greenland ice sheet (GrIS) is losing mass as a result of both increased surface
melting and runoff and increased ice discharge from marine-terminating outlet glaciers
(Rignot et al., 2008, 2011; Sasgen et al., 2012; van den Broeke et al., 2009). The
Greenland mass loss 2000-2012 contributed about 0.7 mm yr-1 of sea level rise. The rate,
has however, been accelerating over this time period such that for 2009-2012, it was 1.05
mm/yr (Figure 2; Enderlin et al, 2014). The relative contribution of ice discharge to total
loss decreased from 58% before 2005 to 32% between 2009 and 2012. As such, 84% of
the increase in mass loss after 2009 was due to increased surface runoff as opposed to
increased discharge (Figure 2; Enderlin et al, 2014). These observations support recent
model projections that surface mass balance, rather than ice dynamics, will likely
dominate the ice sheet's contribution to 21st century sea level rise (e.g. Goelzer et al ,
2013).
12
The glaciers in the southeast and northwest of Greenland sped up between 2000 and
2005 and have since stabilised or slowed (Enderlin et al, 2014). The slowdown in the
southeast has been compensated for by the northeast Greenland ice stream, which
extends more than 600 km into the interior of the ice sheet, and is now undergoing
sustained dynamic thinning, linked to regional warming, after more than a quarter of a
century of stability. This sector of the Greenland ice sheet is of particular interest,
because the drainage basin area covers 16% of the ice sheet and numerical model
predictions suggest no significant mass loss for this sector, leading to a possible underestimation of future global sea-level rise (Khan et al, 2014). The geometry of the bedrock
and monotonic trend in glacier speed-up and mass loss suggests that dynamic loss of
grounded ice in this region will continue in the near future (Khan et al., 2014).
2.3
Potential for dangerous change
The ice sheets can lead to dangerous climate change through accelerated discharge of
freshwater to the ocean, and their potential irreversibility. Accelerated discharge,
particularly from the marine ice sheet instability, has implications for the predictability of
future sea level rise. If ice sheets have thresholds beyond which changes become
irreversible, then these have implications for plans regarding the early mitigation of
climate change.
Antarctic ice shelf thinning or disintegration may be triggered by oceanic (Pritchard, et al.,
2012) and atmospheric (Doake & Vaughan, 1991) warming. At present, the grounding
line of Pine Island Glacier, in West Antarctica, is crossing a retrograde bedrock slope that
lies well below sea level, raising the possibility that the glacier is susceptible to the marine
ice-sheet instability mechanism (Mercer, 1968). An ice flow model (Favier et al., 2012)
shows that Pine Island Glacier's grounding line is probably engaged in an unstable 40 km
retreat (Figure 3; Favier et al., 2014). The associated mass loss increases substantially
over the course of the simulations from an average value of 0.05 mm yr-1 observed for the
1992-2011 period, up to and above 0.28 mm yr-1, equivalent to 3.5-10 mm mean sealevel rise over the next 20 years (Favier et al., 2014). They find that mass loss remains
elevated from then on, ranging from 0.16 to 0.33 mm yr-1. New paleoclimate evidence
(Johnson et al., 2014) for the early Holocene (a period of sustained warming about 2K
above pre-industrial) has revealed mass loss from the Pine Island Glacier at a rate
comparable to present-day loss, but no collapse. Simulations for the adjacent Thwaites
glacier, also in the Amundsen Sea embayment, indicate future mass losses are moderate
<0.25 mm yr-1 over the 21st century but generally increase thereafter (Jouglin et al.,
2014). Except possibly for the lowest-melt scenario, the simulations indicate that earlystage irreversible collapse has already begun. Less certain is the time scale, with the
onset of rapid (>1 mm yr-1 of sea-level rise) collapse in the different simulations within the
range of 200 to 900 years. The total potential contribution to SLR from the WAIS as a
consequence of the marine instability mechanism mentioned above is about 3.3 m
(Bamber et al, 2009) but the rate of mass loss remains uncertain. For example a small
amount of melt in the East Antarctic could release irreversible flow amounting to 4 – 5m
13
of sea level rise. For Antarctica as a whole, there is new evidence (Weber et al., 2014)
for periods of relatively abrupt Antarctic mass loss following the Last Glacial Maximum,
possibly associated with a positive feedback involving ocean heat transport.
Figure 3. Evidence (from Favier et al., 2012) that the Pine Island Glacier's grounding line is
probably engaged in an unstable 40 km retreat, due to the retrograde bedrock slope. Left: map of
bedrock elevation, with the grounding lines for 2009 (white) and 2011 (purple) shown. Right:
bedrock height (solid black line) and geometry of the glacier centreline produced by the Elmer/Ice
ice-flow model at time (t) = 0 (dotted line) and after 50 years of a melting scenario (red line).
Changes in the total ice discharge from the GrIS are the summation of changes in ice
flow from individual marine-terminating outlet glaciers in response to a complex, and
poorly understood, interaction between atmospheric and oceanographic forcing and ice
flow dynamics (Straneo et al., 2013; Joughin et al., 2012). Surface melt has been
spreading and intensifying in Greenland, with the highest ever surface area melt and
runoff recorded in 2012 (Nghiem et al., 2012). How surface melt water reaches the
ocean, and how fast it does so, is poorly understood. Firm - partially compacted snow
from previous years -potentially has the capacity to store significant amounts of melt
water in liquid or frozen form, and thus delay its contribution to sea level (Nghiem et al.,
2012). Ocean modelling has indicated that the fresh water from Greenland is unlikely to
have had any oceanographic consequences to date (Marsh et al., 2010). However, with
increased melt rates it is likely that more fresh water will enter the interior of the Labrador
Sea, where winter mixed-layer depth is sensitive to small changes in salinity. A reduction
of overturning in the Labrador Sea can lead to a local sea level rise of 5 cm with a lesser
sea level fall in the Irminger Sea (Swingedouw et al., 2013). It is possible that the
freshening of the sub-polar North Atlantic could also affect the strength of the meridional
overturning circulation and, as a consequence, heat transport poleward (Smith and
Gregory 2009) – a negative feedback on GrIS decline. Although Greenland ice mass loss
will decline once the marine terminating glaciers have retreated to above sea-level, the
surface mass balance will by then be the dominant mechanism for mass loss.
14
A recent simplified study suggests that the low end regional temperature threshold for
irreversible GrIS loss is only 0.8-3.2 ºC above pre-industrial (with a best estimate of 1.6
ºC). Without a subsequent decrease in temperature, the ice sheet is unsustainable
(Robinson et al 2012). Whether irreversible GrIS decay occurs or not, depends both on
the amplitude and the duration of the climate anomaly. However, because of the long
timescale for reversing global warming, even if anthropogenic greenhouse-gas emissions
are stopped (Lowe et al., 2009; Bowerman et al., 2011), GrIS decay might occur even if
the critical temperature threshold is not crossed by much (Robinson et al., 2012).
2.4
Potential consequences
The eventual (partial) collapse of the WAIS seems likely, leading to a global sea level rise
of up to 3.3 m (Bamber et al., 2009) with an additional contribution from parts of East
Antarctica that will be affected by WAIS drawdown. The restraint offered by the Pine
Island glacier ice shelf is dependent on its basal melt rate, which in turn is controlled by
heat transport in the underlying ocean cavity (Assmann et al., 2013). Timescales for this
collapse may be millennial or less (Cofaigh, 2012). How an ice shelf interacts with the
ocean and melts now and into the future can alter the mass discharge from the Antarctic
Ice Sheet in general and the WAIS in particular, affecting global sea level. There is
currently a lack of climate model simulations, with interactive ice sheets, which could
provide estimates of the timescale of the WAIS collapse (IPCC AR5).
Surface melt from the GrIS may influence local ocean circulation and consequently local
sea level change, perhaps by 5 cm, in the North-West Atlantic (Swingedouw et al., 2013;
Howard et al., 2014).
Substantial topographic change associated with melt of the Greenland ice sheet can be
expected on the 200-500 years timescale (Ridley et al., 2005; Vizcaíno et al., 2008). The
reduction in the topographic barrier to westerly flow will lead to a wider impact on the
Northern Hemisphere climate. In addition the local albedo change will cause vegetation
changes which will have a feedback on the rate of deglaciation (Stone & Lunt, 2013).
On centennial to millennial time scales Antarctic Ice Sheet melt can moderate warming in
the Southern Hemisphere, by up to 10ºC regionally, in a 4 x CO2 scenario (Swingedouw
et al., 2008). This behaviour stems from the formation of a cold halocline in the Southern
Ocean, which limits sea-ice cover retreat under global warming and increases surface
albedo, reducing local surface warming. In addition, Antarctic ice sheet melt, by
decreasing Antarctic Bottom Water formation, restrains the weakening of the Atlantic
meridional overturning circulation, which is an effect of the bi-polar oceanic seesaw
(Pedro et al., 2011). Consequently, it appears that Antarctic ice sheet melting strongly
interacts with climate and ocean circulation globally. It is therefore necessary to account
for this coupling in future climate and sea-level rise scenarios.
15
2.5
Cautions (uncertainties)
While substantial progress in understanding has been made, it is still unclear what the
recent observed changes imply for long-term future ice-sheet loss (Nick et al., 2009). New
observations suggest that there may be a natural cycle of increase and decrease in the
rates of mass loss from coastal glaciers (Murray et al., 2010), so short-term trends should
not necessarily be extrapolated into the future (Wouters et al 2013). Indeed many
Greenland glaciers which accelerated in the early 2000s have since slowed (Moon et al.,
2012; Enderlin et al., 2014.
2.6
Comparison with AR5
Of the key findings summarised in Table 1, the main new points since AR5 are:
observational evidence (Enderlin et al., 2014) that, from Greenland, the proportion of
loss from surface melt has increased, becoming more consistent with long term
model projections; evidence (Favier et al., 2014) that some degree of irreversible loss
from the WAIS may have begun; and indications (Miles et al., 2013; Khan et al., 2014)
that the East Antarctic Ice Sheet (EAIS) and the northeast Greenland ice stream may be
more sensitive to climate change than previously expected.
16
3
Arctic Sea Ice
3.1
Introduction
Arctic sea ice extent has declined annually at a rate of over 4% per decade since modern
passive microwave satellite records began in 1979. The rate of decline is faster in the
summer season (13% per decade for September). There is also evidence that the ice has
thinned, due to both a reduction in the amount of the Arctic Ocean covered by (thicker)
multiyear ice, and the thinning of the remaining multiyear ice.
There are a number of potential impacts of reductions in sea ice extent, including climatic
changes (for example changes to the weather in the UK, Europe, and globally), socioeconomic changes (for example new shipping routes, and offshore mineral exploration),
and changes to and loss of habitats for Arctic wildlife.
Figure 4. Declining Arctic sea ice. (Left) Observed time series of September minimum extent;
(right, from Laxon et al., 2013) ice thickness for (top right) 2003–2007 average ICESat ice
thickness for October/November and (bottom right) CryoSat thickness for October/November
2010.
3.2
Observed recent changes
There is increasing evidence that the rate of decline of September ice extent has
increased during the more recent part of the observational period (Figure 4, left; Comiso
et al, 2008; Stroeve et al., 2012). For example the mean rate of September ice extent
decline from 1979 to 1995 was 0.6 x 106 km2 per decade, compared to 1.9 x 106 km2 per
decade between 1996 and 2012. However, there are suggestions that the ‘acceleration’
in the rate of decline is due to natural variability (Ding et al., 2014; Miles et al., 2014). A
record low seasonal minimum (September) ice extent of 3.63 x 106 km2 was observed in
17
2012, and the last eight years (to 2014) have seen the eight lowest September ice
extents recorded during the satellite era (from the National Snow and Ice Data Centre
website, www.nsidc.org).
There is evidence of the ice cover thinning from a number of radar and laser satellite
altimeter missions, submarine and other in situ time-series (Figure 4, right) but there is
still a need to build a consistent long term series through cross-calibration of the satellite
sensors and blending with earlier submarine and in situ observations. A combination of
IceSat and submarine data was used to estimate a decrease of mean ice thickness in the
central Arctic from 3.64m to 1.89m over the period 1980 to 2008 (Kwok and Rothrock,
2009) which gives an approximate rate of thinning of 60cm per decade. Recent data from
the CryoSat-2 satellite suggests that between 2010 and 2012 the equivalent rate of
thinning was 75 cm per decade (Laxon et al., 2013), but uncertainties remain based on
differences in methods used to retrieve ice thickness from these satellites
(Zygmuntowska et al., 2014).
Figure 5. Reversibility of Arctic sea ice loss in a set of model simulations where CO2 is
increased, stabilised and then reduced (Ridley et al., 2012).
3.3
Potential for dangerous change
A new observationally-constrained estimate of the onset year of nearly ice-free Arctic
summers (for the climate scenario RCP8.5) found the range to be 2040-2060 (Massonnet
et al., 2012).
Although some anomalously low September sea ice extents have been observed (for
example in 2007 and 2012), models strongly suggest that the ice can recover (e.g.,
Figure 5; Tietsche et al., 2011; Armour et al., 2011; Ridley et al., 2012). Sea ice loss is
reversible in current models because the sensitivity of sea ice to global temperature rise
does not depend on the thinning of the Arctic ice cover (Amour et al 2011, Ridley et al.,
2012, Li et al., 2013). An adjoint study suggests that only large forcing anomalies prior to
the spring melting onset in May can influence the September sea ice characteristics while
18
even small changes in the atmospheric variables during subsequent months can
significantly influence September sea ice state (Koldunov et al., 2013). They find that sea
ice volume change is sensitive to atmospheric temperature change in the central Arctic in
June and July. If there are sudden transitions in the sea ice area it occurs during the loss
of winter sea ice, which precipitously declines once the Arctic ice cover becomes too thin
to be sustained at global temperature rises 6.5 - 7.5°C (Ridley et al., 2008, Li et al.,
2013).
Some climate projections show 5-10 year periods of strong ice loss (Holland et al, 2006,
Vavrus et al, 2012, Doscher and Koenigk, 2013), which can arise when large natural
climate variability in the Arctic reinforces the anthropogenic decline (Holland et al, 2008).
These abrupt reductions do not require the existence of a tipping point in the system, or
imply irreversible behaviour (Amstrup et al, 2010, Lenton, 2012). Atmospheric
teleconnection patterns in models suggest that the tropical Pacific modulates Arctic sea
ice variability via Rossby wave trains (Wettstein & Deser, 2014). Interannual to decadal
variability in summer Arctic ice extent is projected to increase as the sea ice cover thins,
and so large anomalies in the September ice extent may become more frequent (Holland
et al, 2008, Goosse et al, 2009).
Reducing worldwide soot emissions could act to slightly delay Arctic sea-ice decline.
Soot can reduce the albedo relative to that of pure snow, leading to earlier snowmelt.
Most Arctic black carbon on sea ice originates from fossil fuel burning (Doherty et al.,
2010). One model study showed that increased Arctic shipping alone would not
contribute significantly to black carbon deposition (Browse et al., 2013), although this
study did not include the (unknown) contribution from gas flaring.
3.4
Potential consequences
In addition to the potential impacts of reduced sea ice cover mentioned in the
introduction, links have been shown between rapid ice loss and cloudiness (Vavrus et al.,
2011), and high latitude land temperatures (Lawrence et al., 2008). Reduced sea ice near
the coasts leave coastal permafrost open to erosion by wave action (Bamhart et al.,
2014).
There have been suggestions that the trend in September sea ice extent has an influence
on mid-latitude winter weather systems (Francis et al., 2009). However, the conclusions
about Arctic-mid-latitude circulation linkages must be tempered by the results from two
recent modelling experiments (Screen et al. 2013; Peings and Magnusdottir, 2014) which
found that the response of the mid-latitude atmospheric circulation to observed sea ice
loss was not statistically significant. The models' responses to sea ice consisted of a local
near-surface response in the Arctic and a weak strengthening of the stratospheric polar
vortex in late winter. The Arctic-mid-latitude connection is nonlinear and likely involves
convective processes over the Arctic's open water during autumn as well as baroclinic
and barotropic processes on the larger scale (Petoukhov and Semenov, 2010).
19
Reductions in the Arctic sea ice extent and volume have an impact on the Arctic fresh
water export and the downstream impacts on the deep water formation (Jahn & Holland,
2013). Simulations suggest a shift toward more and more fresh water export in the liquid
phase (increased river discharge and sea ice melt), as well as a general increase in the
total fresh water export. The phase change of the export is important for downstream
effects, as the fresh water in liquid and solid form reaches different regions. In these
simulations the increase in freshwater stratifies the Labrador Sea reducing the North
Atlantic overturning circulation.
The decline of Arctic sea ice and snow cover contributes to polar amplification, which
means the high latitudes warm faster than the mid-latitudes. It is suggested that northern
hemisphere cold season climate variability is expected to be reduced as a consequence
of declining ice cover (Screen, 2014). This occurs because the northerlies warm faster
than the southerlies.
3.5
Cautions (uncertainties)
Although model skill continues to improve overall (IPCC AR5 Ch 9), AR5 models still
show a wide range of rates of ice decline. Further work is required to understand the
differences in model behaviours, including the extent to which differences are due to the
sea ice representation itself, or to the atmosphere and ocean model components.
3.6
Comparison with AR5
Apart from further observations of low summer sea-ice area, the key points summarised
in Table 1 are largely unchanged since the publication of AR5.
20
4
AMOC
4.1
Introduction
The Atlantic Meridional Overturning Circulation (AMOC) transports large amounts of
heat northwards in the Atlantic Ocean, resulting in a milder climate in Europe and the
North Atlantic than would otherwise be seen (for a recent review of AMOC behaviour
see Srokosz et al., 2012). The IPCC AR5 report concludes that it is very likely that
the AMOC will weaken over the 21st century, although there is a large spread in
predicted weakening. A large or rapid reduction in the AMOC would likely have
substantial impacts for global climate, although a collapse of the AMOC by 2100,
however, was judged as very unlikely (Collins et al, 2013). These top-level
assessments have not changed since the previous IPCC assessment.
4.2
Observed recent changes
The RAPID-MOCHA array has been observing the AMOC at 26°N since 2004 and
has nearly a decade of data now (Rayner et al, 2011). This dataset has revealed
large variability on timescales from daily to interannual. This included a large (30%),
temporary decrease in AMOC strength over winter 2009-2010 (McCarthy et al, 2012)
which resulted in cooling in the upper North Atlantic Ocean in 2010 (Cunningham et
al, 2013). This decrease was well outside the range predicted for interannual AMOC
variability in coupled ocean-atmosphere models (McCarthy et al., 2012). Roberts et
al (2013) reproduced this AMOC decrease using an initial condition ensemble of
ocean simulations driven by observed surface forcing (albeit with too weak an
AMOC), suggesting that the atmosphere had a dominant role in the temporary AMOC
decrease.
◦
Figure 6. Observed decline in Atlantic overturning. Anomalies in overturning at 26 N, relative
to the mean over the same period (from Smeed et al., 2014).
The AMOC overturning has also decreased from 2004-2012 (Figure 6); the majority
of this was due to a weakening of the geostrophic flow (Smeed et al, 2014). This
trend has been associated with decreases in subsurface density in the subpolar gyre,
21
similar to those seen in climate models when there is a reduction in the AMOC
(Robson et al, 2014). It is unclear at this stage whether the decrease is forced.
Statistical tests on the observations (Smeed et al., 2014) suggested that the AMOC
decrease is significant. Roberts et al (2014) found similar trends as part of natural
variability in 2 out of 14 global climate models, and in all models considered when
corrections are made to include more realistic high frequency variability. They
concluded that more than a decade of observations are required to detect an
anthropogenic weakening of the same trend as observed. A decreasing trend in the
transport of the deep western boundary current at 16oN (one component of the
AMOC) over a similar period was also observed by Send et al (2011).
4.3
Potential for dangerous change
Paleoclimate studies have suggested that abrupt changes to climate may have been
caused by the AMOC switching from an “on” state, where it transports heat
northwards in the Atlantic, to an “off” state (Rahmstorf, 2002). It is thought that these
abrupt changes may be related to the existence of bistability (where both “on” and
“off” states of the AMOC can exist for a given forcing) as predicted by theoretical
models of the Atlantic (Stommel, 1961). The potential for real-world bistability has
recently been supported by experiments with a coarse resolution global circulation
model (Figure 7; Hawkins et al, 2011), although that model showed bi-stability only
for greater freshwater forcing than in the present day.
There have been many studies suggesting that the stability of the AMOC might be
affected, or even controlled, by whether the AMOC imports or exports fresh water
from the Atlantic, since this can indicate the presence of a positive or negative
advective feedback. De Vries and Weber (2005) found that the fresh water transport
by the AMOC into the Atlantic (Fov) was an important indicator of stability in their
experiments, however the precise role it plays is still unclear. The experiments of
Hawkins et al (2011) found that Fov indicated the transition between states rather
than bistability itself. Other factors have also been found to be important in
determining AMOC stability. For example, Jackson (2013) found that, while Fov does
partially indicate the sign of the advective feedback in a GCM, the transport of fresh
water by the gyres can also play a crucial role. Swingedouw et al (2013) also found
that gyre transports can affect the magnitude of AMOC reduction. The presence of
eddies in an eddy resolving model can also affect the response of the fresh water
transport (den Toom et al, 2013).
22
Figure 7. Bi-stability of the AMOC simulated by a low-resolution GCM (from Hawkins et al.,
2011). The strength of the simulated AMOC at 26°N, in a set of simulations with imposed
freshwater hosing, for increasing hosing (red) and decreasing hosing (blue).
Various recent studies have shown that the AMOC exports fresh water in
observations (suggestive of bistability) (Hawkins et al, 2011, Bryden et al, 2011)
whereas in many GCMs the AMOC imports fresh water (suggestive of monostability;
Drijfhout et al 2011). However, some of the state-of-the-art GCMs from the Coupled
Model Intercomparison Project 5 (CMIP5) now do have the correct sign of AMOC
freshwater transport though none have yet been shown to have a stable off state or
show abrupt collapses of the AMOC (Weaver et al 2012). It is possible, though, that
these models may have other biases that affect the stability of the AMOC.
4.4
Potential consequences
A collapse in the AMOC would cause a large relative cooling over the North Atlantic,
which would have wide-ranging impacts. As well as previously documented impacts
on the physical system (such as cooling in the northern hemisphere and a shift in the
Intertropical Convergence Zone which cause substantial changes in tropical
precipitation, Vellinga and Wood, 2008), there have been a couple of recent studies
detailing the impacts on the carbon cycle and vegetation. Bozbiyik et al (2011)
showed that a reduction in the AMOC has a large impact on the Amazon with
reduced precipitation causing large reductions in vegetation. Parsons et al (2014), on
the other hand, found that a reduction in the AMOC caused an increase in vegetation
over the Amazon, due to a change in precipitation seasonality (despite a reduction in
annual mean precipitation).
Other studies have concentrated on impacts over Europe. Woollings et al (2012)
showed that models with a greater reduction in AMOC strength due to increased
greenhouse gases have greater increases in strength of the North Atlantic storm
track, implying an increase in the number of winter storms across Europe. Recent
23
studies examining the atmospheric conditions associated with anomalously warm or
cold Atlantic temperatures in observations similarly found increases in winter storms
(Peings and Magnusdottir, 2014) and found changes in seasonal precipitation
patterns across Europe (Sutton and Dong 2012).
4.5
Cautions (uncertainties)
Several studies have shown that many GCMs have biases in the fresh water
transport of the AMOC (importing instead of exporting fresh water), and that this
might affect the simulated stability of the AMOC. The source of this bias is unclear.
Jackson (2013) attributed the bias to an over-evaporative Atlantic in the model and
notes the difference from observations in salinity profiles in the South Atlantic. Liu et
al (2014) suggested that the presence of a double Atlantic ITCZ (a common GCM
bias) results in a tropical salinity bias that stabilises the AMOC. Another source of
uncertainty is the transport of saline water from the Indian Ocean to the Atlantic by
eddies that are shed from the Agulhas current. Current GCMs do not resolve the
scales required to correctly represent these eddies, but a recent study by Biastoch
and Böning (2013) used a high resolution nested model to resolve this region. They
found that a southwards shift of the southern hemisphere westerlies (as is expected
to occur under anthropogenic climate change) results in a decrease in salinity
transport into the Atlantic, however this change in salinity is small and has little
impact on the AMOC. The lack of eddy-resolving resolutions in current GCMs might
also have an impact on the transient response of the AMOC to increased freshwater
input (Weijer et al 2012).
There is also substantial uncertainty about the future inputs of freshwater into the
Atlantic, particularly since the climate models lack dynamic ice sheet models which
could substantially speed up the input of freshwater from the Greenland ice sheet.
Separate studies including additional freshwater inputs from the Greenland ice sheet
find that projected changes do not have major impacts on the AMOC, although there
is uncertainty about future changes in freshwater fluxes from Greenland (Bamber et
al, 2012)
4.6
Comparison with AR5
Of the key findings summarised in Table 1, the main development since the publication of
AR5 has been the updated observations of overturning from the RAPID-MOCHA array
(Smeed et al, 2014), which shows a decline over the period 2004-2012 (although it is
unclear at this stage whether or not this is forced).
24
5
Tropical forests
5.1
Introduction
Over the period 1990-2007, tropical intact forests took up carbon at the rate of 1.2 ± 0.4
Pg C year-1, which accounted for approximately half of the global carbon sink, compared
with 0.50 ± 0.08 Pg C year-1 by the boreal forests (Pan et al. 2011), and around 1.0 ± 0.8
Pg C year-1 from land-use change since 2000 (AR5 WGI). Tropical forests regulate and
supply to society a range of services, which bring benefits at global to local scales. As
well as sustaining high biodiversity they influence climate through biogeochemical
(carbon cycle) and biophysical (water and energy) mechanisms.
Tropical forests are subject to combined effects from atmospheric CO2, climate and landuse change, which interact in complex ways (e.g. Coe et al., 2013). Land-use effects
includes direct deforestation, but also accidental 'leakage' fires which extend over larger
areas. Forest fragmentation (an important by-product of deforestation) lengthens the
forest edge and so increases the rate of erosion by fire ignited near the forest
border. Deforestation increases albedo and reduces evapotranspiration, altering climate
both locally and downwind; aerosols from deforestation fires may also reduce rainfall
(Marengo et al., 2011). Climate change could alter vegetation productivity and mortality,
both directly, and indirectly, by modifying fire behaviour, while increased atmospheric
CO2 can increase tree growth, but also increase tree mortality due to lianas (vines). The
full vegetation response to CO2 and climate changes may take decades to be completely
realised (Jones et al., 2009).
Research has largely, but not exclusively, focused on the Amazon: due in part to early
climate model projections of climate-driven Amazon dieback (Cox et al., 2000). Since
then there have been efforts to look in closer detail at forest sensitivity or resilience to
changing climate and carbon dioxide levels. While forests are generally increasing the
amount of carbon which they store annually (Lewis et al., 2009a; Phillips et al., 2009),
severe droughts in the last decade have provided the opportunity to examine forest
response to extreme dry conditions. In addition to forest and climate monitoring,
throughfall exclusion and prescribed-burn experiments have allowed in-situ study of the
effects of longer-term drought and fire. Numerical studies have also increased in number
and progress has been made in putting the early results into context.
Research carried out since the IPCC AR4 has improved understanding of the risk of
climate-driven forest loss in the Amazon region. The AR5 finds that large-scale dieback
due to climate change alone is unlikely by the end of this century (medium confidence).
However, it states with medium confidence that “severe drought episodes, land use, and
fire interact synergistically to drive the transition of mature Amazon forests to lowbiomass, low-statured fire-adapted woody vegetation” (Scholes et al., 2014).
25
5.2
Observations
Observations of tropical forest extent, structure and associated environmental drivers are
limited by the inaccessibility of these remote regions. Over Africa, forest extent and
deforestation rates have now been mapped accurately from satellite data (Mayaux et al.,
2013), while forest structure, and its relation to environmental drivers, has been detailed
in a study of 260 land plots (Lewis et al., 2013).
There is greater confidence that Amazon forests are adversely affected by drought. A
new, more detailed analysis of contamination in MODIS satellite retrievals (Morton et al.,
2014) has suggested that Amazon forests probably do not exhibit large-scale green up
during the dry season as was previously suggested (Huete et al., 2006). Over the
Amazon, severe droughts of 1997, 2005 and 2010 (Figure 8a) have been studied in more
detail (Phillips et al. 2009, Lewis et al. 2011, Marengo et al. 2008a, 2011, Potter et al.
2011, Tomasella et al. 2013). These have been linked to sea surface temperature
anomalies in the tropical Pacific and Atlantic, and biomass burning (Marengo et al., 2011;
Shiogama et al., 2013), although unforced internal atmospheric variability probably played
a large role (Shiogama et al., 2013). Both observed responses to these droughts, and
long-term drought experiments, have shown elevated mortality rates, especially for larger
trees (Phillips et al. 2010, Nepstad et al., 2007, da Costa et al. 2010) and temporary shifts
from ecosystem carbon sink to carbon source (Phillips et al. 2010, Lewis et al. 2011, Gatti
et al. 2014, da Costa et al. 2013). The consequences of drought have been shown to
include abrupt increases in fire-induced tree mortality (Brando et al., 2014). Negative
effects from a single drought event can persist for several years (Figure 8b; Phillips et al.,
2010, Saatchi et al. 2013). Consistent with that, mortality rates after a few years of
experimental drought is higher than that during the first year (Nepstad et al., 2007, da
Costa et al. 2010), and even during the anomalously wet year of 2011, the Amazon was
still estimated to be carbon neutral overall (Gatti et al. 2014).
Over larger spatial scales, relationships between moisture stress and both vegetation
distributions (Zelazowski et al. 2011) and drought mortality (Phillips et al., 2010) have
been quantified more thoroughly, with a focus on the maximum climatological water
deficit (Malhi et al., 2009) – which is strongly related to dry season length (Zelazowski et
al. 2011).
26
A)
B)
Figure 8. a) The 2005 and 2010 Amazon droughts. Anomalies in Maximum Climatological Water
Deficit (MCWD – a measure of dry season drought severity) over the Amazon basin, for the 2005
and 2010 droughts (from Lewis et al., 2011). b) Persistent effects of the 2005 drought. Anomalies
in QSCAT backscatter (a satellite-derived measure of forest canopy water content) over the southwestern amazon (see inset), from Saatchi et al., 2013.
There have been further observational studies confirming substantial reductions in
evapotranspiration (Lathuilliere et al., 2012) in deforested regions, with evidence for
rainfall reductions, especially through delayed wet-season onset (Butt et al., 2011).
5.3
Potential for dangerous change
A recent review of wider sources of evidence (Coe et al. 2013) identified South/SouthEast Amazonia as particularly vulnerable to combined changes in land-use and climate.
27
This is due to high deforestation rates both locally and in the upwind savanna region, the
fact that it is susceptible to small climate shifts (being in a transitional climate zone
between forest and savanna) and greater climate model agreement on future drying in
this region (compared to the West Amazon). A review for African rainforests (Malhi et al.
2013) highlighted similar points: while deforestation rates have historically been relatively
low over Africa, there is potential for significant future increases; and African forests have
climate close to the limit of rainforest sustainability. Models tend to predict drying(wetting)
over western(central) equatorial Africa (James et al., 2014). James et al. (2014) note that
drying over west equatorial Africa can be large in some models, although the forest
response is hard to predict.
There have been further studies based on global climate models (Good et al. 2013,
Huntingford et al., 2013). As suggested by Malhi et al. (2009), these studies have found
that the basin-scale climate-driven Amazon dieback in the Cox et al. (2000) study is not
typical of most contemporary global climate models. However, missing processes and
biases (subsection e below) in these models are such that dieback is much harder to rule
out than implied by these models alone. Huntingford et al. (2013) showed that an
updated parameterisation of vegetation maintenance respiration response to temperature
significantly increased tropical forest resilience. Shiogama et al. (2011) suggested that
drying over the central/eastern Amazon is more likely if climate model performance in
present-day CMIP3 simulations is accounted for. A comparison between CMIP3 and
CMIP5 model results found greater degree of inter-model agreement in a projected
lengthening and a deepening of the dry season in Amazonia (Joetzjer et al. 2013),
although it is not clear whether this arises from a statistically significant improvement in
model performance.
The observations and field experiments summarised above have given greater
confidence that forests are significantly affected by drought, emphasising the importance
of extreme climate events in causing extensive tree losses (through drought and heat
mortality and increased fire).
Figure 9. Large effect of forest fragmentation from deforestation on projected area burnt over
the Xingu Headwaters (Mato Grosso) from a model study (Soares-Filho et al., 2012). The top
28
two lines have business-as-usual deforestation, and with (thin solid) and without (thick
dashed) climate change. The lower two lines exclude deforestation.
In terms of land-use, it has become clearer that as well as direct deforestation, the
indirect effects of deforestation on forest fragmentation, and on climate downwind, must
be considered in regulatory policies. As well as the observational studies above, one
model study found that forest fragmentation from land-use change could be more
important than climate change for fire behaviour over some parts of the Amazon (Figure
9; Soares-Filho et al., 2012). Land management practises can be important, therefore.
While a 70% decline has been reported in deforestation in the Brazilian Amazon between
2005 and 2013 (Nepstad et al. 2014), maintaining low levels of deforestation in a
sustainable manner remains a challenge (Nepstad et al. 2014). Despite the reduction in
deforestation since 2005, the number and annual area burnt by fires has increased in the
south-south-eastern Amazon, possibly due to increased fragmentation and drought
(Alencar et al., 2011; Aragao and Shimabukuro, 2010).
Various positive feedbacks (fire-vegetation and climate-vegetation; e.g. Hirota, 2011;
Staver, 2011, Hoffmann, 2012) exist that could lead to abrupt reductions in forest cover,
for relatively small change in external forcings, and inhibit reversibility, but the processes
are poorly characterised. The scale over which abrupt change might extend depends on
the strength of positive feedbacks compared to spatial gradients in climate. One new
model study (Higgins et al., 2012) found that, while transitions between vegetation states
may be abrupt locally, over continental and larger scales the effect on the carbon cycle is
much more gradual (because the timing of transitions varies with location). Another
model study (Moncrieff et al., 2014) found that the area over which alternative stable
states are possible could be large in present-day conditions, but declined substantially
with future CO2 increases. Hoffmann et al. (2012) noted that forest-fire feedbacks can be
sensitive to tree growth-rates – and hence to climate change.
5.4
Potential consequences
There has been new understanding of the implications for the global carbon cycle of
deforestation and forest drought. Tropical deforestation between 1990 and 2007
produced ~40% of global fossil fuel emissions (Pan et al. 2011). From a set of >1 million
forest (tropical and extra-tropical) inventory plots, Pan et al. (2011) estimated that close to
the whole residual terrestrial carbon sink is contained in the world’s forests and that the
tropical intact forest sink may have diminished from 1.3 ± 0.3 Pg C year-1 in the 1990s to
1.0 ± 0.5 Pg C year-1 in 2000-2007. Part of the reduction in the sink in the latter period is
thought to be due to the severe drought in the Amazon in 2005, which had an effect large
enough to affect the pan-tropical sink (Pan et al. 2011). Estimate long-term losses, from
tree mortality, following the 2005 and 2010 droughts stand at 1.6 and 2.2 Pg C,
respectively (Phillips et al. 2009, Lewis et al. 2011). There is increasing recognition that
extreme events could have a large impact on the global carbon cycle and offset or
counteract potential increases in biomass (Reichstein et al. 2013).
29
In comparison to the global effects of biogeochemical processes, biophysical effects of
forest loss are more prominent at local to regional scales. There are direct effects on the
local energy and water cycles owing to different properties of the new land cover type,
including albedo, water demand and evapotranspiration rates (Coe et al. 2013). Rainfall
(Sampaio et al. 2007; Butt et al. 2011) and other aspects of basin hydrology (Marengo et
al. 2008a, b, Tomasella et al. 2013) are also likely to be affected, which in turn have
implications for human activities and well-being.
It has been suggested that policies aimed at reducing emissions from deforestation and
maintaining the integrity of the carbon sink should take into account both biophysical and
biogeochemical impacts, although these two forms are hard to compare as they act over
different scales (Anderson-Teixeira et al. 2012).
5.5
Cautions (uncertainties)
Accurate projections are partly limited by the availability of observations. Inaccessibility
of tropical forests increases reliance on remote sensing data, but also makes verifying
remote sensing data (notably, precipitation and vegetation productivity data) challenging.
New studies have shown that great caution is required in interpreting satellite retrievals of
variability in greenness (Morton et al., 2014). At present, the tropical forest biome
constitutes the largest terrestrial carbon sink, but it is also associated with the largest
uncertainties (Pan et al. 2011).
There is substantial uncertainty in the CMIP5 projections of future precipitation in tropical
forest regions, (IPCC 2013), although there is greater degree of inter-model agreement in
some seasonal changes, such as a lengthening and a deepening of the dry season in
Amazonia (Joetzjer et al. 2013). However, the representation of present-day Amazon
precipitation still contains large biases. Large uncertainties are also associated with the
modelled response of vegetation to temperature (Galbraith et al., 2010; Huntingford et al.,
2013) and to CO2 (Rammig et al. 2010). Processes of direct mortality from fire and
drought (and effects of fire on aerosol) are often either unrealistic or absent from models
(e.g. da Costa et al., 2010), and the range of plant functional types is limited.
5.6
Comparison with AR5
While this review presents some details absent from AR5, the key points summarised in
Table 1 are largely unchanged since the publication of AR5 WGII (in part because the
deadlines for literature cited in AR5 WGII were 6 months later than those for WGI).
30
6
Terrestrial permafrost
6.1
Introduction
Permafrost (perennially frozen) soils in the northern high latitudes store ~1700 Gt of
mainly relict carbon (Hugelius et al., 2013, Tarnocai et al., 2009). This is more than twice
as much carbon than is currently in the atmosphere. Around 1000 Gt is stored in the top
3m of soil. Whilst this is currently relatively stable, anthropogenic warming could lead to
thawing permafrost and destabilise some of this carbon. The amount and rate of release
is highly uncertain (Schuur and Abbott, 2011; Burke et al., 2012; Schuur et al., 2013) as is
its potential fate once it enters the carbon cycle (Vonk and Gustafsson, 2013).In particular
the coupling between the carbon cycle and the hydrological cycle could significantly
attenuate or accelerate any greenhouse gas emissions in the form of either methane or
CO2 (Vonk and Gustafsson, 2013). Release of permafrost carbon could potentially cause
a significant positive feedback onto the climate in the future (Burke et al., 2012). However
quantitative projections of the strength of this feedback are highly uncertain mainly
because there is insufficient understanding of the relevant soil processes during and after
thaw (IPCC; 2013). This process is irreversible over the near term because of the long
timescales required to establish these stores.
6.2
Observed recent changes
Increasing near surface air temperatures over the past century and changes in the timing
and thickness of snow cover have caused arctic and sub arctic permafrost to warm
(IPCC; 2013). In the Arctic, temperatures are warming at approximately twice the global
rate with a warming of about 2 degrees C since the mid 1960s
(http://www.arctic.noaa.gov/reportcard/permafrost.html), During 2013 the highest
temperatures since records began in the 1970s were observed at 20m depth at two
northernmost
permafrost
sites
in
North
America
(http://www.arctic.noaa.gov/reportcard/permafrost.html). In addition, observations of the
maximum summer thaw depth or active layer thickness show an increase over the
Russian
and
European
North
during
the
past
15
years
(http://www.arctic.noaa.gov/reportcard/permafrost.html). Landscape disturbances, or
thermokarst, have also been observed (Jorgenson et al., 2006). These are caused by
ground subsidence that results from ice rich soils thawing (Kokelj, and Jorgenson, 2013).
The soil surface collapses into the volume previously occupied by ice. This can either
result in lake formation in lowlands or increased drainage in uplands.
These physical changes in soil temperature and hydrology will impact the global carbon
cycle. Both laboratory (Schadel et al., 2014) and field measurements (Schuur et al., 2009;
Hicks Pries et al., 2013; Dorrepaal et al., 2009) demonstrate the release of old carbon
after permafrost has thawed. Walter Antony et al (2012) documented seeps of geologic
31
methane focused along the boundaries of permafrost thaw. They suggest these seeps
are enhanced by the degradation of the cryosphere cap.
Figure 10. Extent of permafrost for each of the CMIP5 models (reproduced from Koven et al.,
2013) under the current climate (using years 2005-2015 from the RCP4.5 scenario), as well
as for the observational map of Brown et al. (1998).
32
6.3
Potential for dangerous change
Climate models agree that Arctic warming will continue at a rate greater than the global
mean warming with an increase of 5 -11 degrees C above the global mean temperature
under RCP8.5 by 2100 (IPCC, 2013, Ch 12). This increased temperature will result in a
significant loss of permafrost. Slater and Lawrence (2013) used indirect estimates of
permafrost driven by climatic indices from the CMIP5 models and projected a loss of
permafrost of around 1.67 ± 0.7 million km2 per degree of global mean temperature
change. In other words, they projected a loss of near-surface permafrost of 75 - 95 % for
RCP8.5 by 2100. It should be noted that significant air temperature and snow depth
biases exist in some of the models' climate simulations which impact their representation
of present-day permafrost extent (Figure 10; Koven et al., 2013). This contributes to the
uncertainty inherent in any projected loss. Under RCP8.5, sustainable permafrost will
likely remain only in the Canadian Archipelago, Russian Arctic coast, and east Siberian
uplands (Slater and Lawrence, 2013).
Figure 11. Estimated permafrost-carbon climate response (γPF) that would have been
calculated if permafrost-carbon were included within CMIP5 climate models. The boxes
represent the 25th–75th quantile, the whiskers the 5th–95th quantile, and the points the
outliers. The models shaded in gray are the three models that have present-day permafrost
similar to that observed (From Burke et al., 2013).
33
Although permafrost carbon was not included in any CMIP5 models, several simple
approaches have been adopted to estimate the potential loss of carbon in a future climate
(Figure 11; Table 2). In order to compare it with other feedbacks, the permafrost carbon
feedback can be converted to an equivalent radiative forcing (Burke et al., 2013). Cias et
al. (2013) estimated this feedback to be between 0 and 0.16 Wm-2K-1. This is less than
the land carbon response to climate but probably the largest biogeochemical feedback
not in the CMIP5 models. The study of MacDougall et al. (2012) is, to the author’s
knowledge, the only one to represent the closed permafrost carbon feedback loop where
the land surface can respond to the temperature change caused by the released
permafrost carbon.
Table 2 shows a large uncertainty on the amount of carbon released by 2100, with
estimates ranging from ~ 0.5 % up to ~ 50 % of the current permafrost carbon pool in the
top 3m on the northern circumpolar permafrost zone. There is some delay between the
thawing of the permafrost and the release of carbon, so the release by 2100 underestimates the committed long-term loss. For example, Schneider von Deimling et al.
(2012) simulated carbon release under the RCP8.5 scenario through to 2300. In their
simulations there was no change in near-surface permafrost after 2200. However, there
was an additional loss of 62 – 104 Gt C released during the 23rd century. This illustrates
the delayed impact of thawed permafrost on the carbon cycle.
Yedoma regions contain between 58 and 371 Gt of highly biolabile organic carbon stored
below the top 3m that was incorporated into the permafrost during ice age conditions
(Strauss et al., 2013; Vonk et al., 2013). Though this carbon is stored deep under the
surface, it is vulnerable to release after thaw because high-ice content makes this region
susceptible to thermokarst (Schuur et al., 2008).
There is considerably uncertainty as to the net carbon balance when permafrost thaws
(Schuur et al. 2013). Warmer conditions and the release of nutrients from decomposing
organic matter can stimulate plant growth, offsetting a portion of carbon released from
thawed soil (Trucco et al., 2012). However, Hicks Pries et al. (2013) suggest that old soil
respiration will eventually outpace any increases in productivity. In some locations
continued wet conditions may inhibit decomposition rates but cause increased CH4
emissions (Elberling et al., 2012). In addition, the transfer of carbon from terrestrial
ecosystems to aquatic ecosystems can cause both spatial dislocation and temporal
acceleration or attenuation of greenhouse gas emissions depending on the conditions in
the recipient aquatic ecosystems (Vonk and Gustafsson, 2013).
34
Method
Scenario
Carbon
release by
2100 (Gt)
Temperature
change (°C)
Temperature
change (°C)
using TCRE
Burke et al., 2012
Simple parameterisation of permafrost carbon
within a simple climate model
RCP8.5
50-250
0.08 – 0.36
0.08-0.83
Schaefer
2011
Permafrost carbon pool included within a land
surface model
A1B
70-150
0.12 – 0.5
Koven et al., 2011
Vertical distribution of soil carbon simulated
within a land surface scheme
A2
55-69
0.09 -0.23
Schneider
Deimling et
2011
von
al.,
Simple parameterisation of permafrost carbon
within a simple carbon climate model
RCP8.5
33-114
0.04-0.23
0.055 – 0.38
MacDougall et al.,
2012
Permafrost carbon pool included below the
land surface within a intermediate complexity
coupled carbon climate model
RCP8.5
68-508
0.11 – 0.69
0.11 – 1.69
Burke et al.,2013
Superposition of observed soil carbon onto
CMIP5 model-based estimates of permafrost
RCP8.5
9 - 90
0.015 – 0.3
Schuur et al., 2013
Expert assessment
RCP 8.5
162-288
0.27 – 0.96
Zhuang et al., 2006
Process based emission model
< 17
< 0.06
et
al.,
Table 2 Summary of studies estimating the permafrost carbon release by 2100 and their associated estimate of the impact on the global mean
temperature. The last column shows the temperature change estimated from Collins et al. (2014) which relates the global mean temperature
anomaly to the cumulative total anthropogenic CO2 emissions (TCRE) for the different climate models and future scenarios.
35
6.4
Potential consequences
Release of permafrost carbon could potentially cause a significant positive feedback onto the
climate in the future (Burke et al., 2012). There may also be some regional consequences from
permafrost thaw. Permafrost regions are easy to overlook since they are often far from direct
human influence and have been understudied relative to other ecosystems (Schuur et al.,
2013). Although a relatively small population is directly affected by permafrost thawing it has the
potential to affect infrastructure such as buildings, road and rail links and pipelines and even
cause the relocation of some indigenous communities. (Larsen et al., 2014). In addition
terrestrial and freshwater ecosystems are being impacted by permafrost thaw.
6.5
Cautions (uncertainties)
Large scale modelling of the physical state of permafrost is improving, but many of the CMIP5
models have a poor representation of the physics of permafrost (Koven et al., 2013). In addition
there are considerable uncertainties in the soil carbon stocks; the lability of the soil carbon and
therefore its decomposition rate; and the fate of the carbon once it becomes part of the active
carbon cycle. Burke et al. (2012) did an assessment of uncertainties in their simple model of the
permafrost carbon response to climate change and found that uncertainties in the amount of
carbon present in the permafrost affected soils had a strong influence on the uncertainties.
The current state of the art model needs improved representation of processes such as fire;
wetland hydrology; thermokarst development; river and coastal erosion; heat release by
microbial respiration; nutrient availability; and cryoturbation.
6.6
Comparison with AR5
The key findings reported for this system in Table 1 have not changed significantly since AR5.
36
7
Ocean methane hydrates and subsea permafrost
7.1
Introduction
Methane hydrates are crystalline structures containing large amounts of carbon in the form of
methane. They are stable under high pressure and low temperature conditions. As a result,
methane hydrates tend to be found within marine sediments on the continental margins in water
depths exceeding 500 metres (and in deep terrestrial permafrost). In the marine environment,
the sediment volume in which methane hydrates are stable is defined by the methane hydrate
stability zone (MHSZ). Given the sensitivity of the MHSZ to temperature and pressure (Sloan
and Koh, 2008), methane hydrates have been associated with large fluctuations in atmospheric
methane and climate change at the Paleocene-Eocene thermal maximum (PETM) 55 Myr ago
(Dickens et al., 1995) and during Quaternary climate change events (Kennett et al., 2000).
Although a hydrate contribution to the latter now seems unlikely (Sowers, 2006), large-scale
hydrate dissociation remains the most widely accepted explanation for carbon isotopic shifts
during the PETM.
Subsea permafrost is the result of exposure of the sea bed at the time of the last glacial
maximum (LGM) to very cold temperatures when sea level was lower than in the present day.
Since the LGM, sea level has risen and the permafrost has become submerged. It can be found
in large areas of the Arctic shelves, down to a water depth of 100 metres. Hydrate may be
stable beneath such permafrost.
Of particular concern is the vulnerability of these stores to anthropogenic climate change (e.g.
O’Connor et al., 2010), particularly in the Arctic, where temperatures are expected to rise faster
than the global mean, and especially in shallow water, where there is a greater chance that
methane gas will reach the atmosphere. Hydrate destabilisation due to rising temperatures
may be partly offset by increases in pressure due to sea-level rise, which make hydrate more
stable. Any methane release to the atmosphere could impose a positive feedback that would
amplify anthropogenic climate change (Harvey and Huang, 1994; Prather et al., 2001). Some
studies have suggested that a catastrophic release could occur (e.g. Shakhova et al., 2010b).
Carbon release from these stores is effectively irreversible over the near term, because of the
long timescales and particular conditions required to form these stores.
7.2
Recent Observations
Observations of methane gas bubbling through the water column above the West Spitsbergen
continental shelf were first reported by Westbrook et al. (2009). They hypothesised that
warming of the West Spitsbergen current over the preceding 30 years had caused
destabilisation of the methane hydrates in the underlying sediment, resulting in the release of
methane gas into the water column. None of the methane plumes were observed to reach the
atmosphere. Since then, several expeditions have confirmed the presence and location of these
plumes (e.g. Figure 12; Thatcher et al., 2013), and the surface waters above them have been
shown to be supersaturated in methane (Berndt et al., 2014). Seismic evidence indicates that
methane gas release is associated with a retreating MHSZ in that region (Sarkar et al., 2012).
Modelling results also suggest that the time delay between the onset of bottom water warming
and methane gas release is determined by the permeability and porosity of the sediment, the
depth of the hydrate within the sediment, and the rate of bottom water warming. In particular,
37
this time lag could be less than 30 years in water depths shallower than the present upper limit
of the MHSZ (Thatcher et al., 2013).
Figure 12. Sonar image showing bubble plumes at the seabed for data collected during the JR211
Research Cruise to West Svalbard (From Thatcher et al., 2013).
However, it is not clear to what extent these plumes are forced by anthropogenic warming.
Berndt et al. (2014) showed that seasonal variations in bottom water temperatures of 1-2 ⁰C
can cause periodic hydrate formation and dissociation, resulting in gas plume release. They
also provide evidence that the release of gas plumes has been taking place for at least 3000
years. They suggest that observations of large methane emissions cannot be considered proof
that hydrate destabilisation in that region is accelerating as a result of decadal-scale bottom
water temperature increases although they acknowledge that catastrophic destabilisation
cannot be ruled out.
Another region of extensive study is the shallow waters of the East Siberian Arctic Sea (ESAS),
in which subsea permafrost and permafrost-associated hydrates occur in the shallow water
sediments. A comprehensive series of field campaigns from 2003 to 2008, reported by
Shakhova et al. (2010a), confirmed previous observations that methane gas is being released
from the ESAS sediments into the overlying water column (e.g. Shakhova et al., 2005). A large
proportion of the bottom waters and half the surface waters in that region were supersaturated
in methane and atmospheric observations indicated that gas venting to the atmosphere was
occurring at an areal rate of 6.3-9.7 Tg methane per year, comparable to estimates from the
entire global ocean source. Although the magnitude of the ESAS source doesn’t greatly alter
the present-day budget of atmospheric methane, and the ultimate source of the methane is
unknown, any methane trapped within or beneath the permafrost could be vulnerable to future
temperature changes in the Arctic. Degradation of subsea permafrost and methane gas release
have also been observed at the Beaufort Sea continental shelf (Brothers et al., 2012) and the
South Kara Sea shelf (Portnov et al., 2013). More recently, Shakhova et al. (2014) have
indicated that the ESAS subsea permafrost has been degrading over thousands of years and
that bubbles and storms facilitate the venting of the resulting methane gas release from the
overlying water column into the atmosphere.
38
Methane is also produced aerobically in surface water (Scranton and Brewer, 1977) and the
Arctic Ocean open surface waters, well away from continental shelves, are supersaturated with
respect to methane (Damm et al., 2010). Recent atmospheric observations of Arctic Ocean
methane emissions, taken during the HIAPER Pole-to-Pole Observations Programme (HIPPO;
Wofsy et al., 2011) and encompassing latitudes up to 82 ⁰N, found atmospheric layers of
enhanced methane concentrations near the surface water (Kort et al., 2012). These
enhancements were attributed to local emissions from the surface water and were
predominantly found over areas associated with open leads and regions of limited sea-ice
cover. The emission rates themselves were comparable in magnitude to those found from the
degradation of subsea permafrost from the ESAS shelves (Shakhova et al., 2010a) but in this
case, the source of the methane was not attributed to either subsea permafrost or methane
hydrates but to aerobic methane production. Kort et al. (2012) suggest that these emissions
could be sensitive to seasonal and future sea-ice changes. They also argue that present-day
Arctic emissions from all sources should be understood before changes as a result of climate
change can be fully quantified.
7.3
Potential for dangerous change
There have been few studies on the future fate of these stores. It has been estimated that
catastrophic release (e.g. Shakhova et al., 2010b) could have a significant economic impact
(Whiteman et al., 2013). However, this economic analysis used a value of the potential methane
flux that appears to be three orders of magnitude too high (Shakhova et al., 2013; Nisbet et al.,
2013). To date, there are few studies examining the future fate of Arctic methane hydrates
and/or subsea permafrost. Marin-Moreno et al. (2013), for example, examined the fate of
methane hydrates and subsequent methane release from the continental slope off West
Svalbard using climate projections from two climate models and two representative
concentration pathways (RCPs). They found that if their calculations could be extrapolated
along the continental slope across the entire Eurasian Margin, methane emissions at the
seabed over the next three centuries would be up to 6-33 Tg methane per year. This flux is of
similar order to the corrected value of Shakhova et al. (2013) for the East Siberian Arctic Shelf.
Furthermore, Hunter et al. (2013) used projections of both temperature and sea-level rise for
RCP4.5 and RCP8.5 to examine the future fate of global methane hydrates. They found that
under the worst climate change scenario (RCP8.5), methane emissions at the seabed could
reach 30-50 Tg methane per year by 2100. They argued that the flux to the atmosphere would
be significantly reduced and of the order of 1 Tg methane per year. These estimates suggest
that despite numerous observations of methane gas reaching the atmosphere from methane
hydrate dissociation, estimates for the rate of methane gas reaching the atmosphere over the
coming centuries will be low relative to other emission sources e.g. wetlands (Denman et al.,
2007). However, it should be noted that neither of these studies considered subsea permafrost.
39
7.4
Potential consequences
The potential consequences of the degradation of subsea permafrost and/or the destabilisation
of methane hydrates largely depend on the timescale of the subsequent methane release, the
rate of release, the water depth at which the methane is released and the extent to which
methane reaches the atmosphere. If a substantial portion of the released methane is oxidised in
the water column, it could cause the spatial extent of suboxic waters to expand as well as
increasing the acidity of the sea water and affecting nutrient supplies (Biastoch et al., 2011).
If released into the atmosphere, methane will also impose a direct and indirect radiative forcing
on the climate. Indirect forcings include that from tropospheric ozone (e.g. Shindell et al., 2005)
and the subsequent impact on the strength of the land carbon sink due to ozone damage (Sitch
et al., 2007), stratospheric water vapour (Hansen et al., 2005), and sulphate aerosol (Shindell et
al., 2009). These direct and indirect forcings are discussed further in O’Connor et al. (2010).
Increased atmospheric methane also raise the methane lifetime, via a self feedback; so
increasing the associated global warming (Prather et al., 2001).
7.5
Cautions (uncertainties)
Due to their remoteness, there are large uncertainties in the amount of carbon in these stores,
and in the magnitude and rate of any potential future release to the atmosphere (O’Connor et
al., 2010). The present-day budget of Arctic emissions is also uncertain, and there is a lack of
evidence of an anthropogenic influence. Modelling of subsea permafrost in particular is
controversial.
7.6
Comparison with AR5
Since AR5, the presence and location of West Spitsbergen methane gas plumes have been
confirmed (Berndt et al., 2014). However, there have also been suggestions that these plumes
(Berndt et al., 2014), and others in the East Siberian Arctic sea (Shakhova et al. 2014) may
have been ongoing for thousands of years.
40
8
Ocean acidification
8.1
Introduction
Rising atmospheric CO2 causes changes in ocean carbonate chemistry through a process
termed ocean acidification (IPCC, 2013; AR5 WGI). Since the industrial revolution, the ocean
has absorbed about 27% of the emitted anthropogenic carbon dioxide (Le Quéré et al. 2013),
causing a mean decrease in surface ocean pH of ~0.1 (corresponding to nearly a 30% increase
in hydrogen ion concentration) (AR5 WGI, high confidence). This decrease in pH, as well as
other changes to ocean carbonate chemistry, will continue at unprecedented rates as CO2
emissions to the atmosphere continue. Although the IPCC AR4 report included an assessment
of the impacts of ocean acidification for the first time (Fischlin et al. 2007) the AR5 WGI and
WGII reports gave more detailed assessments, based on the nearly 8-fold increase in relevant
research (from 69 papers in 2007 to 530 in 2013) during the period 2007-2013 (CBD 2014).
8.2
Observed recent changes
There are three oceanic monitoring sites with decadal data for ocean carbonate chemistry: all
clearly show decreasing seawater pH and carbonate ion concentration concurrent with rising
atmospheric CO2 (AR5 WG1, WGII).
Few field observations conducted in the last decade demonstrate biological responses
attributable to ocean acidification. The strongest evidence is provided by recent shell thinning in
planktonic foraminifera in the Southern Ocean (Moy et al. 2009) and in pteropoda (Bednaršek et
al. 2012; 2014) in the Southern Ocean and the California Current System. In addition, the
combination of long term pH decline and coastward shifts in upwelling CO2-rich waters off the
northeast Pacific (Feely et al. 2008) has caused larval oyster fatalities in aquaculture (IPCC
AR5 WGII, high confidence; Barton et al. 2012); shifts from mussels to fleshy algae and
barnacles (IPCC AR5 WGII, medium confidence; Wootton et al. 2008); and changes in growth
rate and competitive dominance in coralline algae (McCoy & Pfister, 2014). Such impacts
provide early insights into future effects of ocean acidification. Observations from volcanic
marine CO2 seeps which act as natural analogues show macrophytes (seaweeds and sea
grasses) out-compete calcifying organisms as pH declines, with major decreases in overall
biodiversity (Hall-Spencer et al. 2008; Fabricius et al. 2011).
8.3
Potential for dangerous change
Uptake of CO2 has fundamentally changed ocean carbonate chemistry in all parts of the ocean
particularly at high latitudes (AR5 WGI, high confidence). The current rate of ocean acidification
is unprecedented within the last 65 million years (AR5, high confidence; Ridgwell and Schmidt
2010) possibly the last 300 million years (AR5, medium confidence; Hönisch et al. 2012) and it
will take tens of thousands of years for future ocean pH to return to near pre-industrial
conditions (Archer 2005). Such changes represent a substantial risk to complex marine food
webs and ecosystems, and some effects may be irreversible (e.g. species loss).
Further anthropogenic release of CO2 and its uptake by the ocean will inevitably increase ocean
acidification. Earth System Models project a global increase in ocean acidification for all RCP
scenarios (Figure 13), with decreases in mean surface ocean pH by the end of 21st century in
41
the range of 0.06 - 0.07 (RCP 2.6), 0.14 - 0.15 (RCP 4.5), 0.20 - 0.21 (RCP 6.0) and 0.30 - 0.32
(RCP 8.5). The RCP 8.5 outcome represents an increase in acidity of >150% compared with
pre-industrial values (IPCC AR5 WGI; Bopp et al. 2013, Joos et al. 2011).
Figure 13. CMIP5 model simulations (from IPCC AR5 WGI) for global ocean surface pH. Time
series of projections and a measure of uncertainty (shading) are shown for scenarios RCP2.6 (blue)
and RCP8.5 (red). Black (grey shading) is the modelled historical evolution using historical
reconstructed forcings. The mean and associated uncertainties averaged over 2081−2100 are given
for all RCP scenarios as coloured vertical bars.
Unless CO2 emissions are rapidly reduced, large areas of the Arctic Ocean will become
corrosive to unprotected shelled organisms within a couple of decades, and the Southern
Ocean will follow soon afterwards (Steinacher et al. 2009; Turley et al. 2010). Productive
upwelling waters along Western coastlines of continents, already naturally rich in CO2 and low
in pH, are especially vulnerable due to the additional anthropogenic CO2 from the atmosphere
(AR5 WGI, medium confidence; Feely et al. 2008; Hauri et al. 2013).
8.4
Potential consequences
Impacts of ocean acidification range from changes in organism physiology and behaviour to
population dynamics (AR5 WGII, medium to high confidence) and will affect marine ecosystems
for centuries if emissions continue (AR5 WGII, high confidence). Laboratory and field
experiments as well as field observations show a wide range of sensitivities and responses
amongst organisms (AR5 WGII, high confidence; Kroeker et al. 2013, Wittmann and Pörtner,
2013).With the exception of those that calcify, most plants and microalgae respond positively to
elevated CO2 levels by increasing photosynthesis and growth (AR5 WGII, high confidence).
However, ocean acidification is accompanied by another climate related stressor – ocean
warming. Rising sea temperatures may result in the loss of kelp forests in southern Europe,
while decreasing pH could result in the reduction in coralline algae (maerl) in boreal and Arctic
regions (Brodie et al. 2014). Such changes in coastal benthic flora and habitat structure would
have profound effects on ecosystems. Within other organism groups, vulnerability decreases
with increasing capacity to compensate for elevated internal CO2 concentration and falling pH
(low to medium confidence). Among vulnerable groups that sustain fisheries, highly calcified
42
corals, molluscs and echinoderms, are more sensitive than crustaceans (AR5 WGII, high
confidence; Gattuso et al. 2014 a) and fish (AR5 WGII low confidence; Williamson and Turley
2012; Gattuso et al. 2014 a). During the next decades, ecosystems, including cold- and warmwater coral communities, are at increasing risk of being negatively affected by ocean
acidification, especially in combination with warming (AR5 WGII, medium to high confidence,
respectively; Gattuso et al. 2014 a and b; IGBP, IOC & SCOR, 2013; CBD, 2014).
Declining pH and carbonate ion concentrations and warming temperatures, represent risks to
the productivity of fisheries and aquaculture, and the security of regional livelihoods given the
direct and indirect effects of these variables on physiological processes (e.g., skeleton
formation, gas exchange, reproduction, growth, and neural function) and ecosystem processes
(e.g., primary productivity, reef building, and erosion) (AR5 WGII, high confidence).
As atmospheric CO2 emission increase, ocean acidification will continue with significant
consequences for coastal ecosystems, estuaries and upwelling regions (AR5 WGII, high
confidence). Allowable cumulative CO2 emissions are greatly reduced when ocean acidification
is included as one of the targets when compare to those inferred from the temperature target
alone (Steinacher et al. 2013).
8.5
Cautions (uncertainties)
Knowledge about the effect of elevated CO2 on marine systems is only recently emerging and
there are substantial uncertainties (Gattuso et al. 2011). This includes the scaling-up of impacts
from organisms to communities, food webs and ecosystems ‒ and the goods and services that
ecosystems provide to society (Turley and Gattuso, 2013), and impacts on ocean carbon and
nitrogen cycles (Gattuso et al. 2011). There is uncertainty as to how upwelling systems in
different regions are likely to change with changing climate. Future coastal conditions are
difficult to simulate in models because of the interactions with sediment processes and riverine
inputs (Artioli et al. 2014).
8.6
Comparison with AR5
Although understanding has improved, the key findings for this area (Table 1) have not
changed significantly since AR5 (in part because the deadlines for literature cited in AR5
WGII were 6 months later than those for WGI).
43
9
Conclusions
This report reviews the major new advances reported in the scientific literature, focussing
on progress since October 2010 (i.e. representing an update to the review of Good et al.,
2011). The key findings are summarised in Table 1. Overall, this represents substantial
progress since the review of Good et al., 2011, although large uncertainties remain in all
sectors. Compared to AR5, a large number of studies have added further detail
understanding. For some systems (Arctic sea ice, tropical forests, terrestrial permafrost
and ocean acidification), however, the key headline messages (Table 1) have not changed
significantly since AR5. For tropical forests and ocean acidification, this is partly because
the literature deadlines for AR5 WGII were 6 months later than for WGI. For the other
systems, key messages that postdate AR5 are highlighted in bold in Table 1. Some of the
potential consequences of major change in these systems are summarised in Table 3 (see
individual sections for more detail).
System
Potential consequences of change
• Amplified sea level rise
Ice sheets
• Over very long timescales, potential amplification of warming
• Change in AMOC through meltwater
• Socio-economic changes (new shipping routes)
Arctic sea ice
• Changes in northern hemisphere climate
• Reduced stability of permafrost
• Loss of habit for Arctic wildlife
• Change in AMOC by altering ocean salinity
• Change in large-scale climate patterns, with potential
AMOC
implications for Europe and the Amazon in particular.
• Reduction in terrestrial carbon sink (amplifying global
Tropical forests
warming)
• Change in regional climate
• Loss of biodiversity
• Amplified terrestrial carbon emissions (amplifying global
Terrestrial
warming)
permafrost
• Impacts of permafrost thaw on local infrastructure and
ecosystems
• Amplified terrestrial carbon emissions (amplifying global
Subsea permafrost
warming)
and ocean methane
hydrates
• Impacts on biodiversity, fisheries and aquaculture
Ocean acidification
Table 3. Summary of some potential consequences of change in the systems studied.
44
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10.3 Arctic Sea Ice
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Comiso, J. C., and F. Nishio, 2008: Trends in the sea ice cover using enhanced and compatible
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Ridley, J. K., J. A. Lowe, and H. T. Hewitt, 2012: How reversible is sea ice loss? Cryosphere, 6,
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Vavrus, S., M. Holland, and D. Bailey, 2011: Changes in Arctic clouds during intervals of rapid
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Wettstein, J. J., C. Deser, 2014: Internal Variability in Projections of Twenty-First-Century Arctic
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10.4 AMOC
Bamber, J., M. vanden Broeke, J. Ettema, J. Lenaerts, and E. Rignot (2012), Recent large
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Bozbiyik A., Steinacher M., Joos F., Stocker T. & Menviel I. 2011 Fingerprints of changes in the
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Bryden, H. L., King, B. A., and McCarthy, G. D. (2011). South Atlantic overturning circulation at
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Liu, Wei, Zhengyu Liu, Esther C. Brady, (2014): Why is the AMOC Monostable in Coupled
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McCarthy, G., E. Frajka-Williams, W. E. Johns, M. O. Baringer, C. S. Meinen, H. L. Bryden, D.
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Parsons, L. A., Yin, J., Overpeck, J. T., Stouffer, R. J., and Malyshev, S. (2014). Influence of the
Atlantic meridional overturning circulation on the monsoon rainfall and carbon balance of
the American tropics. Geophys. Res. Lett., 41(1) doi:2013GL058454
Peings, Y and G. Magnusdottir (2014). Forcing of the wintertime atmospheric circulation by the
multidecadal fluctuations of the North Atlantic Ocean. Environ. Res. Lett. 9, 034018
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Rayner, D., Hirschi, J. J. M., Kanzow, T., Johns, W. E., Wright, P. G., Frajka-Williams, E.,
Bryden, H. L., Meinen, C. S., Baringer, M. O., Marotzke, J., Beal, L. M., and
Cunningham, S. A. (2011). Monitoring the Atlantic meridional overturning circulation.
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Roberts, C. D., et al. (2013), Atmosphere drives recent interannual variability of the Atlantic
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Roberts, C. D., L. Jackson, and D. McNeall (2014), Is the 2004–2012 reduction of the Atlantic
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