Geosci. Model Dev., 9, 25632587, 2016 www.geosci-model-dev.net/9/2563/2016/ doi:10.5194/gmd-9-2563-2016 Author(s) 2016. CC Attribution 3.0 License.
Ruza F. Ivanovic1, Lauren J. Gregoire1, Masa Kageyama2, Didier M. Roche2,3, Paul J. Valdes4, Andrea Burke5, Rosemarie Drummond6, W. Richard Peltier6, and Lev Tarasov7
1School of Earth & Environment, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT, UK
2Laboratoire des Sciences du Climat et de lEnvironnement, LSCE/IPSL, CEA-CNRS-UVSQ, Universit Paris-Saclay, 91191 Gif-sur-Yvette, France
3Earth and Climate Cluster, Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
4School of Geographical Sciences, University of Bristol, University Road, Bristol, BS8 1SS, UK
5Department of Earth and Environmental Sciences, Irvine Building, University of St. Andrews, St. Andrews, KY16 9AL, UK
6Department of Physics, University of Toronto, 60 St George Street, Toronto, Ontario, Canada M5S 1A7
7Department of Physics and Physical Oceanography, Memorial University of Newfoundland and Labrador, St. Johns, NL, Canada A1B 3X7
Correspondence to: Ruza F. Ivanovic ([email protected])
Received: 21 September 2015 Published in Geosci. Model Dev. Discuss.: 21 October 2015 Revised: 5 July 2016 Accepted: 8 July 2016 Published: 29 July 2016
Abstract. The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the climate change events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 000 years. Here, we present the design of a coordinated Core experiment over the period 219 thousand years before present (ka) with time-varying orbital forcing, greenhouse gases, ice sheets and other geographical changes. A choice of two ice sheet reconstructions is given, and we make recommendations for prescribing ice meltwater (or not) in the Core experiment. Additional focussed simulations will also be coordinated on an ad hoc basis by the working group, for example to investigate more thoroughly the effect of ice meltwater on climate system evolution, and to examine the uncertainty in other forcings.
Some of these focussed simulations will target shorter durations around specic events in order to understand them in more detail and allow for the more computationally expensive models to take part.
1 Introduction
1.1 Climate evolution over the last deglaciation
The last deglaciation is a period of major climate change, when Earth transitioned from its last full glacial state to the current interglacial climate. The Last Glacial Maximum (LGM) marked the culmination of the last glacial cycle when vast ice sheets covered large regions of the Northern Hemisphere, stretching over North America and Eurasia (e.g. Boulton et al., 2001; Dyke et al., 2002; Peltier et al., 2015; Svendsen et al., 2004; Tarasov et al., 2012), and the Antarctic Ice Sheet expanded to the edge of the continental shelf (Argus et al., 2014; Briggs et al., 2014; Lambeck et al., 2014 and references therein). Changes in the ice sheets resulted in a total sea-level rise of 115130 m between LGM and the
Published by Copernicus Publications on behalf of the European Geosciences Union.
Transient climate simulations of the deglaciation 219 thousand years before present (version 1) PMIP4 Core experiment design and boundary conditions
2564 R. F. Ivanovic et al.: PMIP4 last deglaciation Core experiment design and boundary conditions
late Holocene (Lambeck et al., 2014; Peltier and Fairbanks, 2006) depending upon the time assumed to correspond to the LGM, and 100 m from 21 to 9 thousand years before
present (ka; the period of focus for this manuscript).
Historically, the EPILOG group dened the LGM as having occurred 2319 ka (21 ka centre point), when climate was generally cool and ice sheets were more or less at their largest, based on ice-core and sea-level records (Mix et al., 2001). It represents the time of maximum terrestrial ice volume. More recently, the last sea-level lowstand has been found to have occurred either around 26 ka (Peltier and Fairbanks, 2006) or 21 ka (Lambeck et al., 2014) with relatively stable (low) sea level between those dates. Nearly all ice sheets were at or close to their maximum extent between 26 and 19 ka (Clark et al., 2009).
During the LGM, global annual mean surface temperatures are estimated to have been around 4.0 0.8 C colder
than today (Annan and Hargreaves, 2013). The Earth began warming towards its present state from around 19 ka (Fig. 1h;Buizert et al., 2014; Jouzel et al., 2007), as summer insolation at northern high latitudes and global atmospheric greenhouse gas concentrations gradually increased (Fig. 1cf; Bereiter et al., 2015; Berger, 1978; Loulergue et al., 2008; Marcott et al., 2014). By 9 ka, although the northern ice sheets had not quite retreated (or disappeared) to their present-day conguration, most of the Northern Hemisphere deglaciation had taken place (Clark et al., 2012; Lambeck et al., 2014; Peltier et al., 2015; Tarasov et al., 2012; Figs. 1g and 2), with both surface air temperatures (Fig. 1hi) and atmospheric greenhouse gases (Fig. 1df) approaching present-day values. However, much of Antarctica remained heavily glaciated well into the Holocene, with the majority of its deglacial ice loss taking place between 12 and 6 ka (Argus et al., 2014; Briggs et al., 2014; Mackintosh et al., 2014). Antarcticas total contribution to post-glacial eustatic sea level is poorly constrained, but recent studies have not supported LGM contributions greater than about 15 m eustatic sea-level equivalent (Bentley et al., 2014; Briggs et al., 2014; Golledge et al., 2013;Mackintosh et al., 2011; Philippon et al., 2006; Whitehouse et al., 2012), emphasising the dominance of North American and Eurasian Ice Sheet dynamics in the global sea-level record during the last deglaciation (Argus et al., 2014; Lam-beck et al., 2014; Peltier et al., 2015). It should be noted that there is some controversy over whether deglacial ice sheet reconstructions close the global sea-level budget (Clark and Tarasov, 2014), with a potential LGM shortfall of missing ice.
The last deglaciation is not only an interesting case study for understanding multi-millennial scale processes of deglaciation, but also provides the opportunity to study shorter and more dramatic climate changes. Superimposed over the gradual warming trend (EPICA Community Members, 2004; Jouzel et al., 2007; Petit et al., 1999; Stenni et al., 2011) are several abrupt climate transitions lasting from a few years to a few centuries (examples of which are given
below) and it remains a challenge to reconstruct or understand the chain of events surrounding these instances of rapid cooling and warming.
Heinrich Event 1 (approx. 16.8 ka; Hemming, 2004) occurred during the relatively cool Northern Hemisphere Heinrich Stadial 1 ( 1814.7 ka). It was characterised by the re
lease of a vast number of icebergs from the North American and Eurasian ice sheets into the open North Atlantic, where they melted. The existence of these iceberg armadas is evidenced by a high proportion of ice rafted debris in North Atlantic sediments between 40 and 55 N, predominantly of
Laurentide (Hudson Strait) provenance (Hemming, 2004 and references therein). There are several competing theories for the cause of Heinrich Event 1. There is a substantial body of evidence suggesting that it occurred during or was precursory to a period of Atlantic Meridional Overturning Circulation (AMOC) slow down (e.g. Hall et al., 2006; Hemming, 2004; McManus et al., 2004) and weak North Atlantic Deep Water (NADW) formation (e.g. Keigwin and Boyle, 2008;Roberts et al., 2010) under a relatively cold, Northern Hemisphere surface climate (Shakun et al., 2012). Even though the interpretation of a cause and effect link between Heinrich Event 1 and the diminished strength of the AMOC remains rather compelling (e.g. Kageyama et al., 2013), it is increasingly being suggested that the melting icebergs might not have caused the recorded AMOC slow down, but may have provided a positive feedback to amplify or prolong AMOC weakening and widespread North Atlantic cooling (e.g. lvarez-Solas et al., 2011; Barker et al., 2015).
During the subsequent 14.214.7 ka interval, Northern Hemisphere temperatures are seen to have risen by as much as 14.4 1.9 C in just a few decades (Buizert et al., 2014;
Goujon et al., 2003; Kindler et al., 2014; Lea et al., 2003;
Severinghaus and Brook, 1999), with a dramatic shift in some components of Greenland climate taking place in as little as 1 to 3 years (Steffensen et al., 2008). This abrupt event is termed the Blling Warming or Blling Transition (Severinghaus and Brook, 1999). At roughly the same time ( 14.6 ka), there was a rapid jump in global sea level of
1222 m in around 350 years or less, known as Meltwater Pulse 1a (MWP1a; Deschamps et al., 2012). It is not known exactly which ice mass(es) contributed this 40 mm yr1 (or greater) ux of water to the oceans (e.g. Lambeck et al., 2014; Peltier, 2005). Some studies have mainly attributed it to a southern source (Bassett et al., 2005, 2007; Carlson, 2009; Clark et al., 1996, 2002; Weaver et al., 2003), whereas more recent work has suggested that at most, less than 4.3 m eustatic sea-level equivalent of meltwater could have come from Antarctica (Argus et al., 2014; Bentley et al., 2010, 2014; Briggs et al., 2014; Golledge et al., 2012, 2013, 2014;Licht, 2004; Mackintosh et al., 2011, 2014; Whitehouse et al., 2012) and that Northern Hemisphere ice was the primary contributor (Aharon, 2006; Gregoire et al., 2012; Keigwin et al., 1991; Marshall and Clarke, 1999; Peltier, 2005;Tarasov et al., 2012; Tarasov and Peltier, 2005). Exactly how
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Phases 1 2 3
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Figure 1. The last deglaciation: forcings and events. (a) The three phases of the Core experiment version 1 (Sect. 4). (b) Climate events/periods discussed in the text; Last Glacial Maximum (LGM; 2319 ka as according to the EPILOG denition; Mix et al., 2001), Heinrich Stadial 1 (HS1), Heinrich Event 1 (H1), Blling Warming (BW) and Meltwater Pulse 1a (MWP1a), Antarctic Cold Reversal (ACR) and the Younger Dryas cooling (YD). (c) June insolation at 60 N and December insolation at 60 S (Berger, 1978). (d) Atmospheric carbon dioxide concentration (recent composite of EPICA Dome C, Vostok, Taylor Dome, Siple Dome and West Antarctic Ice Sheet Divide records,
Antarctica; Bereiter et al., 2015); black dashed line shows preindustrial concentration. (e) Atmospheric methane concentration (EPICA Dome C, Antarctica; Loulergue et al., 2008); green dashed line shows preindustrial concentration. (f) Atmospheric nitrous oxide concentration (Talos Dome, Antarctica; Schilt et al., 2010); brown dashed line shows preindustrial concentration. (g) Volume of the ice sheets according to the ICE-6G_C reconstruction (solid lines; Argus et al., 2014; Peltier et al., 2015) and the GLAC-1D reconstruction (dashed lines; Briggs et al., 2014; Tarasov et al., 2012; Tarasov and Peltier, 2002). Associated meltwater scenarios melt-uniform and melt-routed (see Sect. 2.5) are consistent with these; all ice mass loss shown is supplied as freshwater to the ocean. (h) Greenland temperature reconstruction with 1 shaded (averaged GISP2, NEEM and NGRIP records; Buizert et al., 2014). (i) Antarctic D (EPICA Dome C; Jouzel et al., 2007).
Panels (df, hi) are given on the AICC2012 timescale (Veres et al., 2013).
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Figure 2. Northern Hemisphere ice sheet elevation at 21, 18, 15, 12 and 9 ka for (a) the ICE-6G_C reconstruction at 10 arcmin horizontal resolution, elevation is plotted where the fractional ice mask is more than 0.5 (Peltier et al., 2015); (b) the GLAC-1D reconstruction at 1
(longitude) 0.5 (latitude) horizontal resolution, elevation is plotted where the fractional ice mask is more than 0.5 (Briggs et al., 2014;
Tarasov et al., 2012; Tarasov and Peltier, 2002; this study); (c) the difference in elevation above sea level between the two reconstructions where there is ice present in both (ICE-6G_C minus GLAC-1D).
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the Blling Warming and MWP1a are linked, or what triggered either, remains uncertain.
Ice-core records of D indicate that from around 14.5 to12.8 ka, the general trend of increasing Southern Hemisphere warming, temporarily stalled (Jouzel et al., 2007; ice-core chronology from Veres et al., 2013) for a period known as the Antarctic Cold Reversal (Jouzel et al., 1995). Southern Hemisphere cooling is thought to have been relatively widespread, extending from the South Pole to the southern mid-latitudes, with glacial readvance (or stall in glacial retreat) recorded to have peaked 13.014.2 ka in Patagonia (Garca et al., 2012; Kaplan et al., 2011; Strelin et al., 2011) and 13.0 ka in New Zealand (Putnam et al., 2010;
Rother et al., 2014). There are several hypotheses for the cause of the Antarctic Cold Reversal. For example, some have linked it to a change in ocean circulation induced by the delivery of Antarctic ice melt to the Southern Ocean (Menviel et al., 2010, 2011), or possibly as a bipolar response to AMOC recovery and Northern Hemisphere warming during the Blling Warming (Menviel et al., 2011; Stocker, 1998).Using a Coupled Model Intercomparison Project Phase 5 (CMIP5) level coupled atmosphereocean model, Peltier and Vettoretti (2014) and Vettoretti and Peltier (2015) have recently shown that ice-core inferred Southern Hemisphere cooling and Northern Hemisphere warming could have been caused by a non-linear salt oscillator mechanism. Others have argued that a change in Southern Hemisphere winds and ocean circulation is the explanation; for example, a simultaneous northward migration of the southern Subtropical Front and northward expansion of cold water originating in the Southern Ocean (Putnam et al., 2010). The ongoing disagreement over the timing, duration and extent of the Antarctic Cold Reversal means that its cause is difcult to pin down.
The next event of particular interest is the Younger Dryas cooling, when Northern Hemisphere temperatures are thought to have dropped by several degrees at 12.811.7 ka and most prominently in high latitudes (Buizert et al., 2014;Heiri et al., 2007; Lea et al., 2003; Liu et al., 2012; Simon-sen et al., 2011; Steffensen et al., 2008). The event presents a conceptual paradox; the magnitude of the cooling is dif-cult to reconcile with rising atmospheric CO2 (approximately
+10 ppm compared to the earlier Blling period 14.5 ka;
Bereiter et al., 2015) and increasing boreal summer insolation (Berger and Loutre, 1991). It is possible that changes in the atmospheric hydrological cycle, such as a shift in source moisture region, could be partly responsible for the 18O sig
nal, requiring a smaller temperature anomaly to match the records (Liu et al., 2012). For the climate cooling itself, a rerouting of North American freshwater discharge to the Arctic and/or Atlantic oceans might have caused a reduction in NADW formation (Broecker et al., 1989; Condron and Winsor, 2012; Tarasov and Peltier, 2005). Simulating this period within the context of the preceding climate evolution could be key to understanding exactly what the surface climate and deep ocean changes were during the Younger Dryas, and how
these relate to contemporaneous proxy records (e.g. Buizert et al., 2014).
In this description, we have sought to capture some of the last deglaciations main climatic events, but there are others that could shape the focus of further study in the working group. For example, early on in the period there is evidence of around 10 m sea-level rise taking place in 500 800 years around 2019 ka (Clark et al., 2004; Clark and Mix, 2002; De Deckker and Yokoyama, 2009; Yokoyama et al., 2001a, b). Whilst the event itself remains somewhat controversial (Cabioch et al., 2003; Hanebuth et al., 2000, 2009;Peltier and Fairbanks, 2006; Shennan and Milne, 2003), it could be the expression of accelerating deglacial ice melt following the Last Glacial Maximum. More recently, the Barbados record of relative sea-level history indicates that following the Younger Dryas cooling episode, there may have been another meltwater pulse (Fairbanks, 1989; Peltier and Fairbanks, 2006), referred to as Meltwater Pulse 1b. Signi-cant debate surrounds the magnitude and timing of Meltwater Pulse 1b (Bard et al., 1996; Cabioch et al., 2003; Cutler et al., 2003; Edwards et al., 1993; Shennan, 1999; Stanford et al., 2011) and even its existence, because similar to the 19 ka event, it is not seen in all sea-level records spanning the interval (e.g. Bard et al., 1996, 2010; Hanebuth et al., 2000). However, evidence of rapid Antarctic retreat around the time of the event could provide a possible cause for this late deglacial rapid sea-level rise (Argus et al., 2014).
1.2 Transient modelling of the last deglaciation
Transient modelling of the last deglaciation is valuable for examining dynamic and threshold behaviours (Braconnot et al., 2012) endemic to the Earths non-stationary climate system, especially iceoceanatmosphere interactions. It is the best tool for reaching a comprehensive understanding of complex and interrelating climate processes with specic regard to chains of events.
Such simulations are useful for examining the effect of temporally varying climate forcings across the globe and in different environmental systems: what geographical patterns arise and how are they connected, how do these vary through time from seasonal to millennial timescales, and how long does it take before a change in forcing is manifested in a climate response? The spatial coherency of specic events can be investigated to identify processes for simultaneous change as well as lead/lag mechanisms. For example, Roche et al. (2011) investigated patterns of spatial variability in the deglaciation as caused by long-term changes in orbital parameters, atmospheric greenhouse gas concentrations, and ice sheet extent/topography. The results indicated a simultaneous onset of hemispheric warming in the north and south, showing that obliquity forcing was the main driver of the early deglacial warming. In the same investigation, it was found that sea-ice covered regions were the rst parts of the world to exhibit signicant rises in tem-
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perature, implying that a better knowledge of sea-ice evolution could be key to fully understanding the trigger for widespread deglaciation and warming feedbacks. A further example of the insights available into leadlag relationships provided by long, transient climate simulations under glacial boundary conditions is provided by the previously referenced DansgaardOeschger oscillation-related analyses of Peltier and Vettoretti (2014) and Vettoretti and Peltier (2015), which appear to mimic the Heinrich Stadial 1 to Blling transition.
Through comparison to geological time series data, transient simulations enable the ngerprinting of specic climate processes to nd out what mechanisms (in the model) can cause recorded climate signals. Comparing complex, global-scale models to combined geological records can provide multiple ngerprints in different variables from different archives and in different locations to help narrow down plausible scenarios. For example, Menviel et al. (2011) ran a suite of simulations, varying oceanic meltwater uxes through the last deglaciation in order to identify which freshwater-forcing scenarios reproduce the Atlantic Ocean circulation state implied by sedimentary records of AMOC strength/depth and ventilation age (Gherardi et al., 2005; Mc-Manus et al., 2004 with ages shifted as per Alley, 2000;Thornalley et al., 2011) as well as the Northern Hemisphere surface climate (Alley, 2000; Bard, 2002; Bard et al., 2000;Heiri et al., 2007; Lea et al., 2003; Martrat et al., 2004, 2007).It was argued that such climate simulations could be used to improve constraints on the timing, duration, magnitude and location of meltwater inputs to the global ocean.
Liu et al. (e.g. 2009) used climate ngerprinting to identify possible mechanisms for the abrupt Blling Warming event, nding that in their model, a forced cessation of freshwater inputs to the North Atlantic (representing ice sheet melt) superimposed on a steady increase in atmospheric CO2 caused an abrupt resumption in the strength of the AMOC (almost matching a record produced by McManus et al., 2004). This in turn induced a rapid warming in Northern Hemisphere surface climate (close to records from Bard et al., 2000; Cuffey and Clow, 1997; and Waelbroeck et al., 1998) and an increase in tropical rainfall over the Cariaco Basin (comparable to Lea et al., 2003), whilst Antarctic surface temperatures remained relatively stable (similar to Jouzel et al., 2007). Using a suite of simulations from the same model, Otto-Bliesner et al. (2014) went on to suggest that a combination of rapid strengthening of NADW seen by Liu et al. (e.g. 2009) and rising greenhouse gas concentrations was responsible for increased African humidity around14.7 ka, matching the model output to a range of regional climate proxies (including deMenocal et al., 2000; Tierney et al., 2008; Tjallingii et al., 2008; Verschuren et al., 2009;Weijers et al., 2007).
Thus, climate proxy ngerprinting can be useful for understanding the spatial coherency of climatic changes and their underlying mechanisms. However, correlation between model and geological data does not guarantee that the correct
processes have been simulated; there is always the problem of equinality, whereby the same end state can be reached by multiple means. In a process sense, this may be particularly uncertain when a model does not reproduce the full chain of events that led to a distinguishable climatic signal.For example, mechanisms for many of the major changes in oceanic freshwater inputs proposed by Liu et al. (2009) and Menviel et al. (2011) have not yet been directly simulated (e.g. by dynamic ice sheet models). In both studies, they are imposed as model boundary conditions. Further simulations with different forcing scenarios and from a range of models would help to address such uncertainties.
Transient simulations of the last deglaciation also provide necessary boundary conditions for modelling a variety of Earth system components that may not be interactively coupled to the climate model being used. For example, Gregoire et al. (2015) drove a dynamic ice sheet model with climate data produced by a similar set of simulations to Roche et al. (2011). Using a low-resolution general circulation model, individual climate forcings including orbit, greenhouse gases, and meltwater uxes were isolated so that their relative contribution to melting the modelled North American ice sheets could be examined. The work concluded that the last deglaciation was primarily driven by changes in Northern Hemisphere insolation, causing around 60 % of the North American Ice Sheet melt, whilst increasing CO2 levels were responsible for most of the remaining changes (Gregoire et al., 2015). The sufciency of these two forcings for North American glaciation/deglaciation had previously also been identied with fully coupled glaciological and energy balance climate models (Tarasov and Peltier, 1997). Gregoire et al. (2012) were also able to highlight a saddle-collapse mechanism, whereby gradual warming trends could result in abrupt ice sheet melting events, when a threshold in ice mass balance was crossed, which could have occurred during MWP1a and the 8.2 kyr event.
A further example is given by Liu et al. (2012), who carried out an asynchronous (or ofine) coupling between simulated sea surface temperatures and an isotope-enabled atmospheric model to investigate the Younger Dryas cooling event ( 12 ka). The results revised the presupposed Green
land temperatures at this time by 5 C, demonstrating that changes in moisture source must be an important consideration for the robust interpretation of Greenland ice-core 18O
records and our understanding of high-latitude climate sensitivity. More recently, the same methodology was applied to understanding Chinese cave records of the East Asian Summer Monsoon 210 ka (Liu et al., 2014), not only to better interpret what the speleothem 18O tells us about regional hydroclimate variability, but also to understand the wider tele-connections controlling those patterns.
In addition, there are now transient simulations of the last deglaciation from climate models that have been interactively coupled with dynamic ice sheet models (Bonelli et al., 2009;Heinemann et al., 2014) and isotope systems (Caley et al.,
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2014). Furthermore, a fast Earth system model of intermediate complexity (EMIC), which includes an interactive ice sheet model has been used to look at Earth system dynamics (the role of orbital cycles, aeolian dust, subglacial regolith properties, the carbon cycle, and atmospheric trace gases) on much longer, glacialinterglacial timescales > 120 ka and encompassing the last deglaciation (Bauer and Ganopolski, 2014; Brovkin et al., 2012; Ganopolski et al., 2010; Ganopolski and Calov, 2011). However, the older, uncoupled climate ice sheet model approach discussed above remains useful because it enables a wider suite of models to be employed than would otherwise be feasible due to limited computational efciency (e.g. of state-of-the-art, high-resolution/complexity models) or software engineering capability. It may also allow for the same Earth system component model (e.g. of ice sheets or 18O) to be driven by multiple climate models, in order to examine the range of responses and assess (climate) model performance.
With sufcient computational power to make long simulations of the last deglaciation a feasible undertaking, it is timely to coordinate new efforts to ensure that a framework exists to (i) utilise the cutting edge science in climate modelling and palaeoclimate reconstruction, and (ii) robustly intercompare simulations run with different models by different groups and palaeoclimatic data.
1.3 Establishing a new PMIP working group
For more than 20 years, the Paleoclimate Modeling Inter-comparison Project (PMIP) has been internationally coordinating multi-model simulations with complex climate models in order to evaluate model performance and better understand (past) climate changes (Braconnot et al., 2007, 2012;PMIP website, 2007). Currently entering its fourth phase, PMIP is a growing organisation that continues to contribute towards other coordinated efforts to understand present-day climate change, including the CMIP (Taylor et al., 2011a; e.g. 2011b) and the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports (e.g. the Fifth Assessment Report; Flato et al., 2013; Masson-Delmotte et al., 2013). It encompasses a broad range of models, from very fast, lower resolution EMICS, through a range of coupled general circulation models to the latest generation of higher-resolution and complexity Earth system models. Thus, the main challenges for the fourth phase of PMIP include designing experiments that are suitable for all of its participants, addressing sufciently fundamental questions to be of interest to the EMIC community, dening adequately focussed scope for the feasible participation of the latest generation of Earth system models, and prescribing exible model setups that can be implemented in this range of models, whilst maintaining the ability to robustly compare results. In addition, a continuing challenge for PMIP is to assemble suitable palaeoclimatic data sets for comparison to model results.
One of the most recent working groups to be established in PMIP is the Last Deglaciation Working Group. With the aim of coordinating transient simulations of the last deglaciation, the challenge of including the full range of PMIP models is at the forefront of our experiment design. The experiment will be partitioned into three phases (Fig. 1b and Sect. 4), which will form milestones for managing its long duration (12 000 years) as well as for scheduling any shorter, alternative simulations to the Core.
The aim of this paper is to outline the model set-up for the transient Core experiment for the last deglaciation, specically for the sub-period of 219 ka. Prescribed boundary conditions include orbital parameters, atmospheric trace gases and ice sheets. In association with the ice sheet reconstructions, we also provide bathymetric, orographic and land-sea mask evolution as well as make recommendations for freshwater forcing (or global ocean salinity changes) through the period.
1.4 Approach
One of the roles of PMIP has been to systematically study the ability of climate models to retrodict different past climates for which there are observational data from geological archives (e.g. Braconnot et al., 2000, 2007, 2012;Haywood et al., 2010; Joussaume et al., 1999; Kageyama et al., 2006; Kohfeld and Harrison, 2000; Masson-Delmotte et al., 2006; Otto-Bliesner et al., 2009; Weber et al., 2007).In this vein, many palaeoclimate model intercomparison projects have been designed to facilitate the robust comparison of results from the same experiment (i.e. simulation set) across a range of different models, usually taking a prescriptive approach to model set-up to ensure that any differences observed in the results are attributable to differences in model structure and not to differences in chosen boundary conditions and climate forcings. However, as Schmidt et al. (2011) pointed out, the choice of one particular conguration from a range of plausible boundary conditions and forcings is often arbitrary and does not account for uncertainties in the data used for developing the forcings/boundary conditions. Moreover, in designing the PMIP last deglaciation experiment, we have attempted to strike a balance between establishing a framework within which to assess model differences and performance, and taking the opportunity to utilise the full range of PMIP climate models (Earth system, general circulation and intermediate complexity) to examine uncertainties in deglacial forcings, trigger mechanisms and dynamic feedbacks. In short, when we do not precisely know the climate forcing for an event, or the temporal evolution of model boundary conditions, it is more efcient to compare the results from models that use different forcings with geological and palaeoclimatic data than to run one scenario with all models and all scenarios with all models. The aim is to use the results of the comparison to narrow down the range
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of uncertainty in the forcings/boundary conditions and reach a better understanding of underlying climate mechanisms.
Consequently, forcings/boundary conditions that are relatively well established (atmospheric trace gases and orbital parameters) are tightly constrained in the Core experiment design. Others are given with multiple precisely described possibilities to choose from (ice sheet reconstructions) and the remainder (e.g. freshwater/salinity, aerosols and vegetation) are left to the discretion of individual participants. Recommendations will be made for the latter grouping of forcings/boundary conditions, for example, freshwater/global salinity uxes that are consistent with the provided ice sheet evolutions, and the use of preindustrial aerosol and/or vegetation values when they are not model prognostics, but a exible approach is advantageous not only scientically (i.e. for examining the climatic response to uncertain forcings, see above), but also practically (for accommodating the wide range of participating models). Further to this, it will be left to the expert user to decide how often to make manual updates to those boundary conditions that cannot evolve automatically in the model, such as bathymetry, orography and land-sea mask. This is also necessary because of the specic technical and resource requirements associated with setting up and running each participant model.
In addition to the Core, we will coordinate a series of experiments that are designed to
i. explore uncertainties in the boundary conditions and climate forcings;
ii. test specic hypotheses for mechanisms of climate change and to explain individual events;
iii. focus on shorter time periods (for example, abrupt events) and thus include computationally expensive models for which a 12 000 year simulation is unfeasible.
These optional simulations will be referred to as focussed experiments, and participants are encouraged to contribute towards the design and coordination of these simulations within the working group (there is a dedicated wiki page to coordinate these: PMIP Last Deglaciation Working Group, 2016; https://pmip4.lsce.ipsl.fr/doku.php/exp_design:degla
Web End =https://pmip4.lsce.ipsl.fr/doku.php/exp_design:degla ).
The start date for the experiment has been chosen to be in line with PMIPs historical denition of the LGM: 21 ka (Abe-Ouchi et al., 2015; e.g. Braconnot et al., 2000; Kohfeld and Harrison, 2000). However, we are aware that some groups may prefer to begin their simulations from the earlier date of 26 ka (around the last sea-level lowstand; Clark et al., 2009; Lambeck et al., 2014; Peltier and Fairbanks, 2006) and both orbital and atmospheric trace gas parameters will be provided from this earlier date. Although the working groups focus will at least initially be 219 ka, boundary conditions for the Core simulations will be provided from 21 ka to the preindustrial (26 ka to the preindustrial for orbital insolation and trace gases).
The following is not meant to be an exhaustive review of climate forcing reconstructions through the last deglaciation.Instead, our intention is to consolidate the current knowledge in a practical experiment design for a range of climate models. Within this coordinated context, the aim is to explore the forcings and underlying feedback mechanisms for the rapid climate events that punctuated the gradual warming and deglaciation of the Earth.
The paper is structured so that Sect. 2 outlines the model boundary conditions and climate forcings for the Core experiment. Section 3 presents how we will ensure the feasible participation of a range of climate models with different complexity and computational efciency, as well as the plan to run additional, targeted, hypothesis- and sensitivity-led simulations. Section 4 discusses the three phases of the long Core experiment.
2 Core experiment (21 to 9 ka), version 1
The Core simulations of the last deglaciation (version 1) will focus on the period from 21 to 9 ka, although there will also be the option to spin-up the simulation with time-evolving orbital and trace gas parameters from 26 ka and all boundary conditions will be available from 21 ka to the preindus-trial. Recommendations for the initialisation state at 21 ka are summarised in Table 1 and described below (Sect. 2.1).Prescribed boundary conditions include insolation via the Earths astronomical parameters (Sect. 2.2), atmospheric trace gases (Sect. 2.3), ice sheets (Sect. 2.4), meltwater uxes (Sect. 2.5), and orography/bathymetry (Sect. 2.6), as summarised in Table 2. Boundary condition data for version 1 of the Core experiment are provided on the PMIP4 wiki (PMIP Last Deglaciation Working Group, 2016; https://pmip4.lsce.ipsl.fr/doku.php/exp_design:degla
Web End =https://pmip4.lsce. https://pmip4.lsce.ipsl.fr/doku.php/exp_design:degla
Web End =ipsl.fr/doku.php/exp_design:degla ).
2.1 Last Glacial Maximum spin-up
There is a choice of two possibilities for starting the last deglaciation Core simulations. Either the simulation should be initialised from the end of a spun-up, PMIP-compliant LGM (21 ka) simulation, or a simulation with transient orbital and trace gas forcing should be run from an earlier time period (orbital and trace gas parameters will be provided from 26 ka onwards). Whichever method is applied, we require that it is comprehensively documented along with information on the models state of spin-up at 21 ka (e.g. time series of surface climates, maximum strength of the North Atlantic Meridional Overturning Circulation stream function, net radiation at the top of the atmosphere).
2.1.1 Equilibrium-type spin-up (21 ka)
For setting up an equilibrium-type spin-up, please make sure to use the following constraints, which may differ from other PMIP 21 ka simulation protocols:
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Table 1. Summary of recommended model boundary conditions to spin-up the last deglaciation Core experiment version 1 (pre 21 ka); see text for details. Participants are not required to follow the recommendation for these boundary conditions, but must document the method used, including information on the simulations state of spin-up at the point when the Core is started. Data are available from PMIP4 last deglaciation wiki (PMIP Last Deglaciation Working Group, 2016). Boundary condition group headings are in bold.
Spin-up type Boundary condition Description
Last Glacial Maximum Insolation(LGM; 21 ka) Solar constant Preindustrial (e.g. 1361.0 0.5 W m
Eccentricity 0.018994
Obliquity 22.949
Perihelion180 114.42
Vernal equinox Noon, 21 March
Trace gasesCarbon dioxide (CO2) 190 ppm
Methane (CH4) 375 ppb
Nitrous oxide (N2O) 200 ppb
Chlorouorocarbon (CFC) 0
Ozone (O3) Preindustrial (e.g. 10 DU)
Ice sheets, orography and 21 ka data from either: coastlines ICE-6G_C (references in text)
GLAC-1D (references in text)
Bathymetry Keep consistent with the coastlines, using either:
Data associated with the ice sheet Preindustrial bathymetryGlobal ocean salinity +1 psu, relative to preindustrial
Transient orbit and trace Orbital parameters All orbital parameters should be transient, gases (2621 ka) as per Berger (1978) 2621 ka
Trace gases Adjusted to the AICC2012 (Veres et al., 2013)Carbon dioxide (CO2) Transient, as per Bereiter et al. (2015)
Methane (CH4) Transient, as per Loulergue et al. (2008)
Nitrous oxide (N2O) Transient, as per Schilt et al. (2010)
All others As per LGM (21 ka) spin-up type.
Insolation should be set so that eccentricity is 0.018994, obliquity is 22.949 , perihelion180 is 114.42 , the date of the vernal equinox is 21 March at noon. These data are consistent with previous PMIP LGM boundary conditions (PMIP LGM Working Group, 2010).The solar constant is the same as for the preindustrial (e.g. 1361.0 0.5 W m2, Mamajek et al., 2015; as per
CMIP6 version 3.1, Matthes et al., 2016).
Prescribed atmospheric trace gases should be as follows: CO2 at 190 ppm, CH4 at 375 ppb, N2O at 200 ppb (Fig. 3), with CFCs at 0 and O3 at the PMIP3-CMIP5 preindustrial value (e.g. 10 DU). This is to be compatible with the time-evolving boundary conditions for theCore simulations (Sect. 2.3). Note that the LGM atmospheric CO2 and CH4 concentrations have changed slightly from earlier LGM experiments (e.g. PMIP3, which used 185 ppm and 350 ppb, respectively; PMIPLGM Working Group, 2010). However, N2O remains at 200 ppb, which is more representative of the longer glacial period than the 187 ppb concentration recorded at 21 ka (Fig. 3c). These updates are in line with the lat-
2)
est ice-core age model (AICC2012; Veres et al., 2013) and records (Bereiter et al., 2015; Schilt et al., 2010), which are also used for the transient forcings described below (Sect. 2.3).
Prescribed ice sheets should use either the GLAC-1D or ICE-6G_C (VM5a; hereafter simply ICE-6G_C) reconstruction at 21 ka (see Sect. 2.4). The associated topography and coastlines should be used as per the chosen ice sheet reconstruction. Beyond maintaining consistency with the coastlines, it is optional whether or not to implement the associated bathymetry and participants should adapt the bathymetry according to their models capabilities (for example, depending on whether the spatial resolution allows for it or makes this a useful adaptation). These data will be provided with the ice sheet reconstructions. Whichever ice sheet reconstruction is chosen for the LGM spin-up should be carried through to the Core transient simulation.
Global ocean salinity should be +1 psu, compared to
preindustrial, to account for the increased terrestrial ice mass at the LGM (PMIP LGM Working Group, 2015).
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Table 2. Summary of required model boundary conditions for the last deglaciation Core experiment 219 ka version 1; optional boundary conditions are labelled as such. Data are available from PMIP4 last deglaciation wiki (PMIP Last Deglaciation Working Group, 2016). See text for details. Boundary condition group headings are in bold.
Boundary condition Description
Initial conditions Recommended (optional) to use either:(pre-21 ka) Last Glacial Maximum (LGM; 21 ka) equilibrium simulation, including +1 psu global ocean salinity
Transient orbit and trace gases (2621 ka) and all other boundary conditions xed as per equilibrium LGM See Table 1 for details. The method must be documented, including information on the state of spin-up
Insolation
Solar constant Preindustrial (e.g. 1361.0 0.5 W m
2)
Orbital parameters Transient, as per Berger (1978)
Trace gases Adjusted to the AICC2012 age model (Veres et al., 2013):
Carbon dioxide (CO2) Transient, as per Bereiter et al. (2015)
Methane (CH4) Transient, as per Loulergue et al. (2008)
Nitrous oxide (N2O) Transient, as per Schilt et al. (2010)
Chlorouorocarbon (CFC) 0
Ozone (O3) Preindustrial (e.g. 10 DU)
Ice sheet Transient, with a choice of either: ICE-6G_C reconstruction (references in text) GLAC-1D reconstruction (references in text)
How often to update the ice sheet is optional Orography and coastlines Transient. To be consistent with the choice of ice sheet.
Orography is updated on the same time step as the ice sheet. It is optional how often the land-sea mask is updated, but ensure consistency with the ice sheet reconstruction is maintainedBathymetry Keep consistent with the coastlines and otherwise use either:
Transient data associated with the chosen ice sheet; it is optional how often the bathymetry is updated Preindustrial bathymetryRiver routing Ensure that rivers reach the coastline
It is recommended (optional) to use one of the following: Preindustrial conguration for the model Transient routing provided with the ice sheet reconstruction (if available) Manual/model calculation of river network to match topographyFreshwater uxes At participant discretion. Three options are melt-uniform, melt-routed and no-melt (see text). It is recommended (optional) to run at least one Core simulation with a scenario consistent with the chosen ice sheet reconstruction to conserve salinity (e.g. as provided). See text for full details (Sect. 2.5)
Other (optional)
Vegetation and land cover Prescribed preindustrial cover or dynamic vegetation model Aerosols (dust) Prescribed preindustrial distribution or prognostic aerosols
Any other boundary conditions should be set to be consistent with the Core transient simulation to follow (Sect. 2.22.7).
On the freshwater budget, PMIP advises groups to carefully check the fresh water budget in their LGM experiments in order to avoid unnecessary drifts of the ocean salinity. It can be necessary to route the snow which has fallen in excess on the ice sheets to the ocean. Given the change in coastlines, it is also sometimes necessary to relocate the large river estuaries on the coast (PMIP LGM Working Group, 2015). Tarasov and Peltier (2006) provided a glaciological example of the possible re-routings for North America. As they become available, routing maps for the Last Glacial Maximum continents will be provided on the PMIP4 last deglaciation wiki (PMIP Last Deglaciation Working Group, 2016).
The integration time required for spinning up the LGM climate state should be decided on a case-by-case basis by
the user (see comments by Kageyama et al., 2016, on spin-up and duration of experiments). Groups may choose to initialise their equilibrium-type simulation from other PMIP LGM runs. However, caution is advised. Some of the boundary conditions for previous PMIP LGM simulations are different to the set-up outlined here, specically in relation to ice sheets and trace gases concentrations, and therefore need to be adapted to match these requirements. The protocol for the PMIP4-CMIP6 (being nalised at the time of writing) is currently compatible with the LGM spin-up described here.Therefore, provided that either the ICE-6G_C or GLAC-1D ice sheet reconstruction is used for both the LGM spin-up and transient run, the PMIP4-CMIP6 LGM simulation can be used to initialise transient simulations of the last deglaciation without alteration. Please provide time series data for the diagnosis of model (dis)equilibrium at 21 ka (introduction to Sect. 2.1).
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280
180
2.1.2 Transient orbital and trace gas parameters (2621 ka)
If this is the preferred option to initialise the Core, it is recommended that the simulation is set up as per Sect. 2.1.1, but with time-evolving orbital and trace gas parameters instead of xed ones. Specically for orbit, the eccentricity, obliquity, perihelion180 and date of the vernal equinox values listed above should be replaced with their transient equivalents, as per Berger (1978). For the atmospheric trace gases, carbon dioxide, methane and nitrous oxide values should be replaced with the transient equivalents provided on the PMIP4 last deglaciation wiki (PMIP Last Deglaciation Working Group, 2016), which are set according to Bereiter et al. (2015), Loulergue et al. (2008) and Schilt et al. (2010), respectively, on the AICC2012 chronology (Veres et al., 2013);Fig. 3.
In this case, all other boundary conditions should remain xed in line with the LGM equilibrium-type experiment design until 21 ka, when the fully transient Core simulations begin. This transient spin-up can be initialised from a spun-up previous LGM, cold ocean, preindustrial or observed present-day ocean simulation.
2.2 Insolation (219 ka)
As per Sect. 2.1, the solar constant should be xed to the established preindustrial conditions (e.g. 1361.0 0.5 W m2;
Mamajek et al., 2015; Matthes et al., 2016) throughout the run, which is in line with the PMIP preindustrial experiment set-up (PMIP LGM Working Group, 2015). However, the orbital parameters should be time evolving through the deglaciation to follow Berger (1978); see e.g. Fig. 1c.
2.3 Atmospheric trace gases (219 ka)
For the deglaciation, chlorouorocarbons (CFCs) should be xed at 0, and O3 should be set to PMIP3-CMIP5 preindustrial values (e.g. 10 DU), as used for the LGM. When a model is not running with dynamic atmospheric chemistry, the remaining trace gases should be time evolving, with CO2 following Bereiter et al. (2015), CH4 following Loulergue et al. (2008) and N2O following Schilt et al. (2010), all adjusted to the AICC2012 chronology (Veres et al., 2013); see Fig. 1df.
The atmospheric CO2 concentrations provided by Bereiter et al. (2015) is a composite data set, combining previous Antarctic ice-core records and composites (for the period 260 ka: Ahn and Brook, 2014; Lthi et al., 2008; MacFarling Meure et al., 2006; Marcott et al., 2014; Rubino et al., 2013; Siegenthaler et al., 2005) on the AICC2012 timescale of Veres et al. (2013) to produce a high-resolution record that is consistent with the other, lower-resolution trace gas records used in this experiment (CH4 and N2O as discussed above). Groups are free to decide on the temporal resolu-
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-24 -22 -20 -18 -16 -14 -12 -10
Core N O: TALDICE on AICC2012 EDC on EDC1
260
CO (ppm)
240
2 220
200
700
CH 4(ppbv)
600
500
400
2
280
260
NO (ppbv)
240
2 220
200
180 -26 -24 -22 -20 -18 -16 -14 -12 -10Time (ka)
Figure 3. Atmospheric trace gases through the last deglaciation from Antarctic ice cores. (a) Core experiment carbon dioxide according to a recent composite record from EPICA Dome C (EDC), West Antarctic Ice Sheet Divide (WDC), Vostok, Taylor Dome and Siple Dome (thick black line; Bereiter et al., 2015), which was produced on the AICC2012 chronology (Veres et al., 2013). Also shown for comparison is an older composite record from EDC, Vostok and Taylor Dome (thin blue line; Lthi et al., 2008, adjusted to the AICC2012 chronology), as well as the original EDC CO2 record (green line; Monnin et al., 2004) and the recent, higher-resolution WDC CO2 record (dark red line; Marcott et al., 2014);
which were incorporated into the newer composite by Bereiter et al. (2015). (b) Methane according to the EPICA Dome C (EDC)
record (Loulergue et al., 2008), shown both on the original EDC1 chronology (green line; Spahni et al., 2005) and adjusted to the more recent AICC2012 chronology for the Core experiment (thick black line; Veres et al., 2013). (c) Nitrous oxide according to the
Talos Dome (TALDICE) record (Schilt et al., 2010), adjusted to the AICC2012 chronology for the Core experiment (thick black line; Veres et al., 2013). For comparison, the earlier EPICA Dome C (EDC) record on the EDC1 chronology is also shown (green line; Spahni et al., 2005). The nearest measured N2O concentration to 21 ka is from 21.089 ka; hence, there is a small offset between the slightly earlier concentration (187 ppb) used for the Core and the interpolated value plotted at 21 ka. For panels (ac) 21 ka concentrations according to the AICC2012 age model (red dots) are shown in contrast to previous PMIP3 LGM concentrations (blue dots; PMIP LGM Working Group, 2010). If using an equilibrium-type spin-up for the start of a transient Core simulation at 21 ka (Sect. 2.1.1), use 190 ppm CO2, 375 ppb CH4 and 200 ppb N2O.
and Peltier, 2002) and whilst it is mostly published, there are some new components; therefore, a short description follows. The Eurasian and North American components are from Bayesian calibrations of a glaciological model (Tarasov et al., 2012; this study), the Antarctic component is from a scored ensemble of 3344 glaciological model runs (Briggs et al., 2014) and the Greenland component is the hand-tuned glaciological model of Tarasov and Peltier (2002) updated to the GICC05 age chronology (Rasmussen et al., 2006). All four of the GLAC-1D ice sheet components employ dynamical ice sheet models that have been constrained with relative sea-level data. Where available, they have also been constrained by geologically inferred deglacial ice margin chronologies, pro-glacial lake levels, ice-core temperature proles, present-day vertical velocities, past ice thickness, and present-day ice conguration. Details of exactly how these constraints were derived and applied are given in the relevant references above. The four components (North America, Eurasia, Antarctica and Greenland) were combined under glacial isostatic adjustment (GIA) post-processing for a near-gravitationally self-consistent solution (Tarasov and Peltier, 2004), which was tested against complete GIA solutions. The topography in the global combined solution was adjusted in Patagonia and Iceland following ICE-5G (Peltier, 2004), but the changes in these ice caps are not reected in the ice mask.
Compared to ICE-6G_C, GLAC-1D is derived with fewer degrees of freedom given the internal constraints of glacial physics and assumptions in the climate forcing (which in part depends on climatologies derived from PMIP2 and PMIP3 results). GLAC-1D incorporates additional constraints that are inapplicable to purely geophysically constrained models. These include inferred pro-glacial lake levels for North America as well as proximity to the present-day observed Antarctic Ice Sheet after a transient, multi-glacial cycle simulation with the underlying ice-earth model. Furthermore, GLAC-1D is subject to the critical physical feedbacks/constraints of ice (and bed) thermodynamics and bed surcial geology on ice streaming, which has a major impact on ice sheet topography. However, all these extra constraints and physics come at the cost of a 10 to 22 m shortfall in GLAC-1D relative to far-eld relative sea-level proxies (a 10 to 15 m shortfall compared to ICE-6G_C). This is part of the so-called missing ice problem (Clark and Tarasov, 2014), with the upper bound also accounting for the local viscous slab effect of Austerman et al. (2013). Both ICE-6G_C and GLAC-1D are subject to as yet unquantied uncertainties, such as the impact of lateral inhomogeneity in the viscous structure of the Earth.
The two reconstructions incorporate similar constraints for North American ice sheet extent (i.e. Dyke, 2004). For Eurasia, ICE-6G_C follows the ice extent provided by Gyllencreutz et al. (2007), whereas GLAC-1D uses data from Hughes et al. (2015). The reconstructions only differ slightly in their ice extent evolution (Figs. 2 and 4), for example the
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tion of trace gas model inputs based on these records and if lower resolution is employed, the method used to smooth or create a spline through the data should be fully documented.Exploring the inuence of CO2 resolution on the climate system may form the basis of a coordinated additional simulation that will be optional for participant groups. The details of the set-up for such focussed simulations (also discussed in Sect. 3) will be discussed and determined at a later date.
It is noted that the N2O value from Schilt et al. (2010) and Veres et al. (2013) does not match the previously dened LGM N2O concentration (Sect. 2.1.1): 187 ppb compared to 200 ppb (Fig. 3c). This is because the N2O record is highly variable during the last glacial lowstand (2621 ka), with a range of 33 ppb (183216 ppb) and a mean of 201 ppb.
Thus, 200 ppb seems a reasonably representative N2O concentration for the spin-up phase of the simulation, although the Core simulations will start with the more chronologically accurate value of 187 ppb.
2.4 Ice sheet reconstructions (219 ka)
For the Core experiment, ice sheet extent and topography should be prescribed from one of two possible reconstructions: ICE-6G_C (Figs. 2a and 4a) and GLAC-1D (Figs. 2b and 4b).
The ICE-6G_C model has been designed such that its total mass and local thickness variations provide excellent ts to most of the data that may be invoked to constrain it. In particular the total mass is constrained by the globally averaged (eustatic) rise of sea level that is well approximated by the coral-based record of relative sea-level history from the island of Barbados in the Caribbean Sea (Peltier and Fairbanks, 2006). On the other hand, the local variations of ice thickness are constrained to t not only the very large number of radiocarbon dated histories of relative sea level change from the regions that were once ice covered, but also by the voluminous records of present-day vertical motion of the crust that are now available from North America, Eurasia and Antarctica, based upon space-based Global Positioning System measurements. This t is obtained through iterative space domain renement, as fully described by Argus et al. (2014) and Peltier et al. (2015). Furthermore, the reconstruction includes a history of Antarctic glaciation that correctly includes the expansion of ice cover in the Ross Sea and Weddell Sea embayments and out to the shelf break at the LGM. Stuhne and Peltier (2015) assess the compatibility of ICE-6G_C with current understanding of ice dynamical processes using data assimilation methods. The model is unique internationally insofar as the range of observational constraints that it has been shown to reconcile. Since the ICE-6G_C reconstruction is fully published (Argus et al., 2014;Peltier et al., 2015), the reader is directed to this literature for further detailed information.
The GLAC-1D reconstruction is combined from different sources (Briggs et al., 2014; Tarasov et al., 2012; Tarasov
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Figure 4. Southern Hemisphere ice sheet elevation at 21, 12 and 9 ka for (a) the ICE-6G_C reconstruction at 10 arcmin horizontal resolution, ice elevation is plotted where the fractional ice mask is more than 0.5 (Argus et al., 2014; Peltier et al., 2015); (b) the GLAC-1D reconstruction at 1 (longitude) 0.5 (latitude) horizontal resolution, ice elevation is plotted where fractional ice mask is more than 0.5 (Briggs et al.,
2014; Tarasov et al., 2012; Tarasov and Peltier, 2002); (c) the difference in elevation above sea level between the two reconstructions where there is ice present in both (ICE-6G_C minus GLAC-1D).
Barents Sea deglaciates earlier in GLAC-1D than in ICE-6G_C (Fig. 2). The main differences between the reconstructions are in the shape and volume of individual ice sheets. In particular, the North American Ice Sheet reaches an elevation of 4000 m in ICE-6G_C, but is only 3500 m high in GLAC-1D. Similarly, the shape and thickness of the Barents Sea Ice Sheet are not the same in the two reconstructions.
The ICE-6G_C data set is provided at both 1 horizontal resolution and 10 arcmin horizontal resolution, GLAC-1D is provided at 1 (longitude) 0.5 (latitude) horizontal reso
lution. Both data sets include ice extent and topography at intervals of 1000 years or less through the deglaciation. Specif-
ically, the ICE-6G_C reconstruction is provided at 1000-year intervals for the period spanning 2621 ka and 500-year intervals for 210 ka. For GLAC-1D, the data are at 100-year intervals for 210 ka. In both reconstructions, ice extent is provided as a fractional ice mask.
Ice surface elevation (topography) should be implemented as an anomaly from present-day topography and added to the models present-day topography after regridding onto the model resolution, following the previous LGM experimental protocol (PMIP LGM Working Group, 2010, 2015). Land surface properties will need to be adjusted for changes in ice extent. Where ice retreats, land surface should be initialised
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as bare soil if a dynamic vegetation model is used, otherwise use prescribed vegetation (see Sect. 2.7) with appropriate consideration of soil characteristics. Where ice is replaced by ocean, it is advised to follow the procedure for changing coastlines described in Sect. 2.7. Inland lakes can be prescribed based on the ice sheet and topography reconstructions, but this is not compulsory. It is also optional whether to include changes in river routing basins (i.e. catchments) and outlets, which can either be calculated from the provided topography and land-sea mask data (see Sect. 2.6), or can be manually set to follow routing maps provided on the PMIP4 last deglaciation wiki (PMIP Last Deglaciation Working Group, 2016).
Groups are free to choose how often to update ice extent and elevation. This could be done at regular intervals (e.g. the sub-1000-year time slices provided) or at specic times during the deglaciation, as was done in the TraCE-21 ka experiment (Liu et al., 2009). Changes in ice extent can have a large impact on climate through ice albedo changes and feedbacks. We thus recommend that when possible, ice sheets are not updated at times of abrupt regional or global climate change, particularly the events that the working group will focus on, as this could articially introduce stepped shifts in climate. Groups are also advised to consider that ice sheet associated boundary conditions (ice extent and elevation, land-sea mask, bathymetry) may need to be updated more often at times of rapid ice retreat. The timing and way in which land ice changes are implemented must be documented.
Alternative ice sheet reconstructions or simulations can be used to test the sensitivity of climate to this boundary condition. Simulations with coupled ice sheetclimate models are also welcomed. Although these will not form part of the Core, for which ICE-6G_C or GLAC-1D should be used, they will be coordinated as important supplementary focussed simulations.
For technical notes advising on the implementation of the ice sheet reconstructions in palaeoclimate models, see Kageyama et al. (2016).
2.5 Ice meltwater
The Core experiment protocol is exible on whether or not to include prescribed ice melt (i.e. freshwater uxes) delivered from the ice sheets to the ocean and how to do it. It is recommended to run at least one version of the Core experiment with ice melt included, since around 110 m of ice-volume equivalent sea level is thought to have melted 269 ka (e.g. Lambeck et al., 2014) and considering the historical importance attached to the inuence of (de)glacial freshwater uxes on climate (e.g. Broecker et al., 1989; Condron and Winsor, 2012; Ganopolski and Rahmstorf, 2001; Liu et al., 2009; Rahmstorf, 1995, 1996; Teller et al., 2002; Thornalley et al., 2010; Weaver et al., 2003). However, it is also important to note the ongoing debate over the extent to which catastrophic freshwater uxes brought about abrupt deglacial
climate change; several alternative or complementary mechanisms have been proposed (e.g. Adkins et al., 2005; lvarez-Solas et al., 2011; Barker et al., 2010, 2015; Broecker, 2003;Hall et al., 2006; Knorr and Lohmann, 2003, 2007; Roche et al., 2007; Rogerson et al., 2010; Thiagarajan et al., 2014).Moreover, a thorough investigation of the extent to which non-freshwater-forced climate evolution matches the geological records has merit in its own right; can abrupt deglacial changes be simulated without icemeltwater? To what extent can observed patterns be attributed to better constrained forcings, such as atmospheric CO2 and Earths orbit? It is for all of these reasons that a exible protocol is required.
Freshwater forcing scenarios consistent with the ice sheet reconstructions and which hence conserve salinity throughout the deglacial experiment are provided in two formats (the melt scenarios described below). In addition, there is the option to run without any ice meltwater (no-melt) to provide a robust reference for simulations that include uncertain melt-water uxes. Thus, at least one Core simulation should be run using one of the following ice sheet meltwater scenarios:
Melt-uniform: a globally uniform freshwater ux (or salinity target) through time, designed to conserve ocean salinity based on changing terrestrial ice mass.Fluxes consistent with the ice sheet reconstructions are provided.
Melt-routed: a distributed routing that is consistent with the geographic evolution of the ice sheet reconstructions (GLAC-1D and ICE-6G_C; Sect. 2.4) and gives the ux through time at individual meltwater river outlets along the coast. Again, versions of this scenario are provided.
No-melt: no ice meltwater is included in the core; neither a globally integrated ocean salinity target (melt-uniform) nor a distributed routing at the coastlines (melt-routed) is implemented. This is best implemented as a sensitivity-type experiment to account for model specicness and meltwater ux uncertainty when also implementing melt scenarios in accompanying versions of the Core simulation.
Multiple Core simulations exploring more than one of these scenarios are welcomed.
Data for the melt scenarios will be available from the PMIP4 last deglaciation wiki (PMIP Last Deglaciation Working Group, 2016). The data for melt-uniform are available at the time of writing (following the respective ice volume changes from ICE-6G_C and GLAC1-D; Fig. 1g), data for melt-routed will be made available as they are produced (anticipated by August/September 2016). These melt scenarios represent a best-estimate approach to resolving the yet unknown geographically and temporally precise freshwater uxes of the last deglaciation, and they are also consistent with the ice sheet reconstructions employed in the core. As such, they provide robust and justiable boundary conditions
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for simulations that will be assessed against palaeoclimate reconstructions.
However, participants do not have to use the (recommended) versions of melt-uniform or melt-routed that are consistent with ICE-6G_C and GLAC-1D, and can instead use their own scenarios to explore uncertainty in the ice sheet meltwater ux forcing. This is because the working group aims to use the full suite of PMIP climate models to examine forcing/boundary condition uncertainty (see discussion of model intercomparison project approaches in Sect. 1.4).Please note that in some ice melt (including no-melt) scenarios, global water budget may not be balanced through time.Therefore, it is advised to also use at least one scenario that falls within geological constraints (such as the ICE-6G_C or GLAC-1D consistent scenarios for melt-uniform and melt-routed).
Regardless of which scenario is employed, it is important that meltwater uxes are prescribed as time-evolving model boundary conditions; rather than as stepwise adjustments at the same time as the ice sheets are updated, for example.Unless they are intentional conditions of the scenario, there should be no sudden jumps in the freshwater being applied.Furthermore, we invite participants to upload the boundary condition data for other freshwater ux scenarios along with appropriate documentation as/when they become available, and to contribute towards the coordination of focussed experiments (see Sect. 3) that will test specic hypotheses associated with model and climate sensitivity to the location, duration and magnitude of freshwater uxes.
2.6 Topography, bathymetry, coastlines and rivers
Participants are recommended to note the advice set out by Kageyama et al. (2016) for implementing these boundary conditions in PMIP4-CMIP6 Last Glacial Maximum and Pliocene equilibrium-type experiments.
Changes in the ice sheets and their glacial eustatic and iso-static inuence affected continental topography and ocean bathymetry, which in turn shifted the coordinates of river mouths and the coastal outline throughout the deglaciation.Hence, time-varying topographic, bathymetric and land-sea mask elds that match the chosen ice sheet from Sect. 2.4(i.e. ICE-6G_C or GLAC-1D) should be used; moreover, these are provided within the ice sheet reconstruction data sets.
Topography should be updated at the same time as the models ice sheet is updated; this is mainly implicit to implementing the ice sheet reconstruction because the major oro-graphic changes through the deglaciation relate directly to ice sheet evolution. This said, due to glacial isostatic adjustment components in the ice sheet reconstructions, there is evolution in continental topography that is not directly the lowering/heightening of the ice surface, and it is up to individuals whether they incorporate this or mask only the changes in ice sheet orography.
Ocean bathymetry will be provided. When deemed possible, this boundary condition should be varied through time.Where differences in the land-sea mask require extra land to ll up coastal regions, or land to be cut away into ocean as sea-level rises (see next paragraph on coastlines), the model must be changed accordingly, because it is important to adequately represent the changing land-sea mask; for example, in order to include overlying grounded ice.
Following on from this, coastlines will need to be varied according to changes in global sea level (and each models horizontal grid resolution). It will be left to the discretion of participants to decide how often to update either boundary condition, and when deciding on their frequency it is recommended that groups consider the implications for opening/closing seaways and their effect on ocean circulation and climate. Furthermore, the frequency need not be regular and may instead focus on key events in the marine (gateway) realm. However, whenever possible and foreseeable, groups are encouraged to avoid making stepwise changes to model boundary conditions that would interfere with signals of abrupt climate change; particularly those events that the working group aims to focus on (Heinrich Event 1, the Blling Warming, MWP1a, the Younger Dryas etc.) unless the forcing (e.g. opening of a gateway) is assumed to be linked with the event.
If groups wish, model river networks can be remapped to be consistent with this and updated on the same time step as the ice sheet reconstruction, either manually or by the model. However, it is appreciated that the technical challenges associated with such a methodology would be impractical for many. Therefore, following the recommendation of the PMIP3 LGM Working Group (2010) and Kageyama et al. (2016), river pathways and basins should be at least adjusted so that fresh water is conserved at the Earths surface and care should be taken that rivers reach the ocean at every time step that the bathymetry is adjusted; for example, when sea levels were lower, some river mouths may need to be displaced towards the (new) coastline to make sure they reach the ocean.
2.7 Vegetation, land surface and other forcings
In this section, recommendations are made for last deglaciation vegetation, land surface and aerosol (dust) parameters in the model.
There are three recommended options for setting up the Core experiments vegetation and land surface parameters, they can either be (i) computed using a dynamical vegetation model (e.g. coupled to the atmospheric component of the model), (ii) prescribed to match the CMIP5 preindustrial setup (Taylor et al., 2011a, b) with xed vegetation types and xed plant physiology (including leaf area index) or (iii) prescribed to match the CMIP5 preindustrial set-up (Taylor et al., 2011a, b) with xed vegetation types and interactive plant physiology if running with an enabled carbon cycle. If pre-
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scribing vegetation and land surface, i.e. using option (ii) and (iii), groups should be aware that coastal land will be emerged compared to preindustrial because of the increased terrestrial ice volume and associated lower eustatic sea level (with the maximum during the early stages of the Core).Therefore, vegetation/land surface will need to be interpolated onto the emerged land from preindustrial grid cells, for example using the nearest neighbour methods.
For models with prognostic aerosols, the parameters for dust (forcing) can be computed dynamically. Alternatively, it is recommended that Core simulations x the associated parameters according to the CMIP5 preindustrial simulation (Taylor et al., 2011a, b), with no temporal variation. Examining the inuence of different transient aerosol scenarios (for those models that do not include prognostic dust, for example) could constitute a further suite of sensitivity simulations for comparison with the Core.
There is no last deglaciation protocol for setting up other forcings, transient or xed in time. For all simulations, groups are required to fully document their methods, including experiment design and especially when different or with additional components to the set-up described here.
3 Coordinating further simulations
As already discussed, we are faced with the challenge of designing an experiment that is suitable to be run with a wide range of models, from the more computationally efcient class of intermediate complexity models, to state-of-the-art Earth system models. One particular difculty is enabling the most complex and the highest resolution climate models to participate in this 12 000-year-long experiment when for some, even the integration to reach the LGM spin-up state demands a large number of computational resources. There is no easy solution and our approach will be to augment the Core simulations with shorter focussed simulations that target specic questions, mechanisms and time periods. Whilst the most computationally expensive models (e.g. the latest generation of Earth system models) may not be able to participate in the Core, they will be included in the shorter subset of focussed simulations. Similarly, alternative full-deglaciation simulations can be coordinated for the less computationally expensive models in the working group (e.g. low-resolution general circulation models, and Earth system models of intermediate complexity).
One line of investigation relating to meltwater inputs from ice sheets and icebergs is to carry out a suite of sensitivity simulations examining different injection sites. These simulations would help to address some of the uncertainty in freshwater ux scenarios. For example, geochemical evidence suggests that smaller and more localised discharges of freshwater than have traditionally been considered in climate models may have an important inuence on ocean circulation (e.g. Hall et al., 2006), implying that precise freshwa-
ter uxes are needed in the models to examine their effect.
Certainly, others have shown that the location of injection is a controlling factor on the impact of freshwater delivery to the ocean, not just laterally (e.g. Condron and Winsor, 2012;Smith and Gregory, 2009), but also in terms of depth (e.g.Roche et al., 2007). A set of coordinated simulations exploring a range of uncertainty in the freshwater forcing (location, depth, duration, magnitude, and physical characteristics such as temperature and density) would be well suited for the focussed experiments, thus building on the Core simulations, which may themselves indicate interesting avenues for investigation; partly the purpose of a exible meltwater approach.
However, freshwater is not the only issue and other focussed experiments could include the inuence of greenhouse gas records, differences in ice sheet reconstructions (e.g. the PMIP3 merged ice sheet from Abe-Ouchi et al., 2015; ICE-6G_C; GLAC-1D) or simulations with (coupled) ice-sheet models, the relative importance of different forcings (e.g. insolation vs. trace gases vs. ice sheet evolution), sensitivity to dust-forcing scenarios, the inuence of changes in tidal energy dissipation (Schmittner et al., 2015), event-specic hypothesis testing and shorter-term variability within the climate system.
Based on ongoing discussions, it is likely that the rst sets of focussed simulations will be
sensitivity and hypothesis-driven simulations that compare results from uniformly distributed meltwater uxes to results from river-routed meltwater uxes to examine the impact of the regional specicity of freshwater forcing upon climate system evolution;
sensitivity simulations that are free from ice meltwater uxes to provide information on what climate evolution was caused by processes other than freshwater uxes to the ocean;
a hypothesis-driven investigation of the possible mechanisms for preconditioning the glacial ocean for the relatively cool Heinrich Stadial 1 and ensuing catastrophic iceberg discharge (Barker et al., 2015);
sensitivity experiments examining the role of trace gas forcing resolution on climate evolution, for example, smoothing the record provided by Bereiter et al. (2015).
We have described the plans for focussed simulations to highlight the depth of the working groups aims and to properly contextualise the Core simulations, but the purpose of this manuscript is to outline the model set-up for the Core experiment. The design for subsequent focussed simulations will be described at a later date on the PMIP4 last deglaciation wiki (PMIP Last Deglaciation Working Group, 2016) and we welcome contributions to the discussion of what further simulations to coordinate there.
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4 Working group phases
The experiment will be split into three phases that are designed to run seamlessly into each other (Fig. 1a). Phase one begins at the LGM (21 ka) and will nish at the abrupt Blling Warming event, which is where phase 2 picks up, encompassing the Blling Warming. Phase 3 begins at the start of the Younger Dryas cooling and is currently planned to continue through to the end of the Core experiment at 9 ka.
Perhaps most importantly, this affords near-future milestones for managing the ultimate completion of the long full deglacial simulation across all participant groups. It will provide a timetabled framework for beginning and continuing the longer simulations; for scheduling shorter, event-or challenge-specic transient simulations by more computationally expensive models (see discussion in Sect. 3); and for the analysis and publication of results as the milestones are reached. Another motivation is to ensure that the experiment design for later periods of the last deglaciation is updated according to knowledge gained from simulations of the preceding time period; for example, changes in ocean and climate states, which have previously been shown to have a strong inuence on climate trajectories (e.g. Kageyama et al., 2010; Timm and Timmermann, 2007). This is particularly important for setting up shorter, event-specic focussed simulations, but it is not planned to be explicitly used to inuence the Core. Splitting the period into phases also provides the opportunity to update model boundary conditions and climate forcing data with cutting edge palaeocli-mate reconstructions, as they emerge during the lifespan of the multi-model experiment. However, care will be taken to ensure that these are physically consistent between phases, and these updates will not compromise the Core simulations described in this manuscript. This is so as not to disadvantage more computationally efcient models that may have already completed simulating the full 219 ka (or beyond) period. Instead, the information will be incorporated into focussed versions of the last deglaciation simulations; possibly spun-off sub-periods that do not have to start again at the LGM.
Each phase will encompass at least one distinguishable climate event; Heinrich Stadial 1 and Heinrich Event 1 in phase 1 following on from the LGM; MWP1a, the Blling Warming and the Antarctic Cold Reversal in phase 2; and the Younger Dryas cooling in phase 3 (Fig. 1b). As outlined in Sect. 3, simulations of these shorter events can be coordinated in the focussed simulations. This is to engage the higher complexity/resolution models, which are unable to run longer simulations, but can use the wider framework of the working group to provide valuable knowledge on rapid climate changes known to have taken place in the last 21 ka.
5 Summary
The last deglaciation presents a host of exciting opportunities to study the Earth system and in particular, to try to understand a range of abrupt climate changes that occurred over just a few years to centuries within the context of more gradual trends. Numerical climate models provide useful tools to investigate the mechanisms that underpin the events of this well-studied time period, especially now that technological and scientic advances make it possible to run multi-millennium simulations with some of the most complex models. Several recent modelling studies have begun this task, but many questions and untested hypotheses remain. Therefore, under the auspices of the Paleoclimate Modelling Intercom-parison Project (PMIP), we have set up an initiative to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 000 years.
The rst step has been to design a Core experiment suitable for a range of PMIP models: from relatively fast and coarse resolution Earth system models of intermediate complexity, to new generations of the more complex and higher-resolution general circulation and Earth system models. The set-up for this Core experiment is based on an approach that tries to combine a traditional Model Intercomparison Project method of strictly prescribing boundary conditions across all models, and the philosophy of utilising the breadth of participants to address outstanding uncertainty in the climate forcings, model structure and palaeoclimate reconstructions. Accordingly, we have made recommendations for the initialisation conditions for the simulation and have stated our minimum requirements for the transient experiment design, as summarised in Tables 1 and 2, respectively.
However, there are some uncertainties that the Core is not designed to deal with directly or exhaustively; two examples discussed in this manuscript being the effect of trace gas record resolution and the inuence of ice melt on the oceans and climate, respectively. We know that the Core simulations will not tackle all of our questions, and are likely to give rise to others. Therefore, additional focussed simulations will also be coordinated on an ad hoc basis by the working group. Many of these will build on and be centred around the Core; often taking shorter snapshots in time, thus including the most computationally expensive models in the experiment, or presenting 12 000 year alternatives to the Core for faster models to contribute. Not all simulations will be suitable for all models, but the aim is that taken as a whole, the experiment can utilise the wide range of PMIP model strengths and hence minimise individual weaknesses.
Essentially, the Core experiment has been designed to be inclusive, taking into account the best compromise between uncertainties in the geological data and model limitations.The hypothesis-driven focussed experiments will go further than the Core to target the questions that remain. It is hoped
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that this exciting initiative will improve our individual efforts, providing new opportunities to drive the science forwards towards understanding this fascinating time period, specic mechanisms of rapid climate warming, cooling and sea-level change and Earths climate system more broadly.
6 Data availability
All boundary condition data required for running the last deglaciation Core experiment version 1 (summarised by Tables 1 and 2) can be downloaded from the PMIP4 last deglaciation wiki (PMIP Last Deglaciation Working Group, 2016; https://pmip4.lsce.ipsl.fr/doku.php/exp_design:degla
Web End =https://pmip4.lsce.ipsl.fr/doku.php/exp_design:degla ).
Author contributions. Ruza F. Ivanovic and Lauren J. Gregoire lead the PMIP Last Deglaciation Working Group, for which Andrea Burke, Masa Kageyama, Didier M. Roche and Paul J. Valdes act as the advisory group. Ruza F. Ivanovic, Lauren J. Gregoire, Masa Kageyama, Didier M. Roche, Paul J. Valdes and Andrea Burke collaboratively designed the working groups aims, structure, Core experiment and additional experiments in consultation with the wider community. Rosemarie Drummond,W. Richard Peltier and Lev Tarasov provided the ice sheet reconstructions, plus associated boundary conditions. Ruza F. Ivanovic and Lauren J. Gregoire collated these and all other boundary condition data for the simulations. Ruza F. Ivanovic and Lauren J. Gregoire wrote the manuscript and produced the gures with contributions from all authors.
Acknowledgements. Ruza F. Ivanovic is funded by a NERC Independent Research Fellowship (no. NE/K008536/1). Data processing for boundary condition preparation was carried out using the computational facilities of the Palaeo@Leeds modelling group, University of Leeds, UK. All authors would like to thank everyone who has taken the time to discuss the Working Groups aims and experiments with us. We are especially grateful to Jean-Yves Peterschmitt (Laboratoire des Sciences du Climat et de lEnvironnement, France) for managing and archiving the boundary conditions, as well as setting up and maintaining the PMIP wiki pages; to Emilie Capron (British Antarctic Survey, UK) for help with the ice-core data and to Bette Otto-Bliesner (National Center for Atmospheric Research, USA) for useful comments on an earlier version of this manuscript. Specic thanks also go to Anders Carlson, Eric Wolff, Andreas Schmittner, Shawn Marshall and an anonymous reviewer for valuable comments on the manuscript, as well as to Jeremy Fyke for editing.
Edited by: J. FykeReviewed by: S. J. Marshall and one anonymous referee
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www.geosci-model-dev.net/9/2563/2016/ Geosci. Model Dev., 9, 25632587, 2016
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Copyright Copernicus GmbH 2016
Abstract
The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the climate change events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 000 years. Here, we present the design of a coordinated Core experiment over the period 21-9 thousand years before present (ka) with time-varying orbital forcing, greenhouse gases, ice sheets and other geographical changes. A choice of two ice sheet reconstructions is given, and we make recommendations for prescribing ice meltwater (or not) in the Core experiment. Additional focussed simulations will also be coordinated on an ad hoc basis by the working group, for example to investigate more thoroughly the effect of ice meltwater on climate system evolution, and to examine the uncertainty in other forcings. Some of these focussed simulations will target shorter durations around specific events in order to understand them in more detail and allow for the more computationally expensive models to take part.
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Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer