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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. 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