Pliocene Model Intercomparison (PlioMIP) Phase 2: scientific objectives and experimental design

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, and their potential relevance in the context of future climate change. PlioMIP operates under the umbrella of the Palaeoclimate Modelling Intercomparison Project (PMIP), which examines multiple intervals in Earth history, the consistency of model predictions in simulating these intervals and their ability to reproduce climate signals preserved in geological climate archives. 
 
This paper provides a thorough model intercomparison project description, and documents the experimental design in a detailed way. Specifically, this paper describes the experimental design and boundary conditions that will be utilised for the experiments in Phase 2 of PlioMIP.


PlioMIP Phase 1 Design and objectives
The PlioMIP project was initiated in 2008 and is closely aligned with the US Geologi- 15 cal Survey Program known as PRISM (Pliocene Research Interpretation and Synoptic Mapping), which has spent more than 25 years focusing on the reconstruction and understanding of the mid Pliocene Warm Period (mPWP: ∼ 3.3 to 3 million years ago), as well as the production of boundary condition data sets suitable for use with numerical climate models. Figures  Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Experiment 2 used coupled ocean-atmosphere GCMs where sea-surface temperatures and sea-ice were predicted dynamically by the models; vegetation, land/sea distribution, and topography remained fixed to PRISM3D estimates. The scientific objectives in Phase 1 were to: -Examine large-scale features of mPWP climate that are consistent across models.

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-Determine the dominant components of mPWP warming derived from the imposed boundary conditions.
-Examine first order changes in ocean circulation between the mPWP and presentday.
-Examine the behaviour of the Monsoons (e.g. their intensity).

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-Compare model results with proxy data to determine the performance of models simulating a warm climate state.
-Use the mPWP as a tool to evaluate the long term sensitivity of the climate system to near modern concentrations of atmospheric CO 2 . 15 In the context of co-ordinated international model intercomparison projects, PlioMIP achieved a number of firsts. For example, it was the first palaeoclimate modelling intercomparison project to require vegetation distributions to be modified in climate models, facilitating the incorporation of vegetation forcing on climate. It was also the first intercomparison project that required individual groups to fully document the im- 20 plementation of palaeo-boundary conditions within their models, along with the basic climatological responses. This was designed to facilitate the intercomparison itself by enabling artefacts of individual methodologies of boundary condition implementation to be separated from robust model responses to imposed palaeo boundary conditions. Through PlioMIP a spin off project known as PLISMIP (Pliocene Ice Sheet Model Intercomparison Project; Dolan et al., 2011) was initiated and has focused on (1) assessing ice sheet model dependency of Greenland Ice Sheet reconstructions using shallow ice approximation ice sheet models (Dolan et al., 2011;Koenig et al., 2014), (2) examining the effect of different GCM climatological forcing on predicted ice sheet configurations 5 (Dolan et al., 2014) and (3) using shallow shelf ice sheet models for Antarctica to test both ice sheet model and climate model dependency on predicted ice sheet reconstructions (de Boer et al., 2015). Outputs from PlioMIP Phase 1 include:

PlioMIP Phase 1 accomplishments
-Identified consistency in surface temperature change across models in the tropics. 10 Lack of consistency identified in model responses at high latitudes. In contrast model predictions are inconsistent in terms of total precipitation rate in the tropics (Haywood et al., 2013a).
-Global annual mean surface temperatures increased by 1.84 to 3.6 • C and show a greater range for Experiment 2 using coupled ocean-atmosphere models than 15 Experiment 1 using fixed sea-surface temperatures (Haywood et al., 2013a).
-There was no clear signal signal in model predictions to support enhanced Atlantic Meridional Overturning Circulation and Ocean Heat Transport to the high latitudes (Zhang et al., 2013).
-Clear sky albedo and greenhouse gas emissivity dominate polar amplification of 20 surface temperature warming during the mPWP. This demonstrated the importance of specified ice sheet and high latitude vegetation boundary conditions and simulated sea ice and snow albedo feedbacks. Furthermore, the dominance of greenhouse gas emissivity in driving surface temperature changes in the tropics was identified   (Zhang et al., 2013).
-Data-model comparison using both sea surface and surface temperature proxies indicate that climate models potentially underestimate the magnitude of polar 5 amplification. However, current limitations in age control and correlation make interpreting model-data discrepancies challenging (Dowsett et al., 2012;Dowsett et al., 2013a;, Salzmann et al., 2013).
-Model results indicate that longer term climate sensitivity (Earth System Sensitivity) is greater than Charney Sensitivity (best estimate ESS / CS ratio of 1.5: Haywood et al., 2013a).

PlioMIP -emerging challenges/opportunities
One of the key findings in PlioMIP Phase 1 was the potential underestimation of modelpredicted surface temperature warming in the high latitudes. Understanding modeldata discord is non-trivial and can rarely be attributed to a single factor. The complexity 15 of understanding model-data discord is highlighted by the PMIP Triangle ( Fig. 1), which illustrates three possible contributions to model-data discrepancy, and has at its vertices model physics (structural and parameter uncertainty), model boundary conditions and proxy data uncertainty. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for 20 sampling structural uncertainty within climate models as a suite of different models will take part in PlioMIP. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as weaknesses in the methodologies used for data-model comparison, which stemmed from the time averaged nature of proxy data used in previous data/model comparisons (Dowsett et al., 2013a;Salzmann 25 et al., 2013). Therefore, our strategy for Phase 2 is to utilise state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeogra-4008 Introduction phy reconstruction detailing ocean bathymetry and land/ice surface topography. The ice surface topography is built upon the lessons learned during the PLISMIP project (Dolan et al., 2014). Land surface cover will be enhanced by recent additions of Pliocene soils and lakes (Pound et al., 2014). Atmospheric reconstructions of palaeo-CO 2 are emerging on orbital timescales (e.g. Bartoli et al., 2011;Badger et al., 2013) and these will also be incorporated into PlioMIP Phase 2. It was recognised during Phase 1, that a key influence on model-data discord stems from uncertainties associated with the derivation of the proxy-data sets used to assess the climate models. Although certainty surrounding any proxy data set is limited by analytical, spatial and temporal uncertainty, Phase 1 highlighted temporal uncertainty 10 as an important constraint on more robust methodologies for data/model comparison (DMC: Dowsett et al., 2013a;Haywood et al., 2013b;Salzmann et al., 2013). The concept of climate stability during the mPWP is overly simplistic both in geological environmental reconstruction and climate modelling approaches.
Due to the increasing recognition of climate variability in the mPWP, time averaged 15 approaches to palaeoenvironmental reconstruction have reached their ultimate potential to evaluate climate models. Therefore, enhancing the temporal resolution of data collection in order to more adequately understand climate variation in the Pliocene is required, and developing a more strategic approach to the choice of relevant Pliocene event(s) to reconstruct and model is needed. One of PlioMIP's guiding principles is 20 to utilise palaeoenvironments to better inform us of likely scenarios for future global change. To this end, the event chosen for PlioMIP Phase 2 focuses on the identification of a "time slice" centred on an interglacial peak (MIS KM5c; 3.205 Ma) that has nearmodern orbital forcing, and yet retains many of the characteristics of mPWP warmth on which we have focussed in the past (Dowsett et al., 2013b;Haywood et al., 2013b PRISM and the wider Pliocene data community are rising to the challenge to obtain higher resolution proxy-data that will inform the models about the chosen time slice (e.g. Dowsett et al., 2013b; see also Haywood et al., 2013b). The key differences between the PRISM data that underpinned PlioMIP Phase 1 and the new direction for data collection include: 5 -Expanding to a community-wide effort, new data generation will focus on key locations and specific regions that have been identified by PlioMIP Phase 1 as important for understanding Pliocene climate variability and model performance.
-In order to increase our understanding of temporal changes in mPWP climate, time series data will be produced as standard, which will in essence increase previous temporal resolution by two orders of magnitude and lead to enhanced methods of data/model comparison.
-We will encourage the use of multi-proxy methods of data generation. This will enable us to derive more robust and holistic palaeoenvironmental reconstructions. 15 The utilization of the Pliocene as a means to understand future global change ("Pliocene for Future") remains a priority in Phase 2. It is our intention to forge even stronger links between PlioMIP, PMIP, CMIP and the next IPCC assessment. However, we recognise that many researchers are primarily interested in the Pliocene because it represents a considerable challenge to our understanding of the operation of the 20 Earth System ("Pliocene for Pliocene"). Furthermore, a number of scientific requirements and priorities do not fit exclusively within a Pliocene for Future mandate. For example, state of the art palaeographic reconstructions are indicating more substantial regional variations in palaeogeography than were known in the past. Due to the differing requirements identified, in PlioMIP Phase 2 we have designed a portfolio of model experiments that effectively address both the "Pliocene for Future" and "Pliocene for Pliocene" agendas. This is illustrated in the following CMIP-style diagram (e.g. Taylor et al., 2012) where priorities for both agendas are highlighted, with both agendas sharing a common core experiment that represents the PlioMIP Phase 2 experiment within CMIP6.

Pliocene for future and Pliocene for Pliocene
2 Strategy and methodology 5

Naming convention and summary of the experimental design for PlioMIP Phase 2
The experiments in PlioMIP Phase 2 have been grouped into half's "Pliocene4Pliocene" and "Pliocene4Future" and should ideally be completed by all participating groups. However, the core experiments must be completed by all groups. Each half of the 10 project is divided into two "tiers" (Fig. 2). After the core experiments, Tier 1 experiments are identified as a higher priority for completion than Tier 2. We describe several model simulations, which essentially consist of various combinations of boundary conditions associated with prescribed CO 2 , orography, soils, lakes, and ice sheets. To simplify the experimental descriptions, we use the following nomen-15 clature: Ex c , where c is the concentration of CO 2 in ppmv, and x are any boundary conditions which are Pliocene as opposed to pre-industrial, where x can be any or none of o, i , where o is orography and i is ice sheets. For example, a pre-industrial simulation with 280 ppmv CO 2 we denote E 280 . A Pliocene simulation with 400 ppmv is Eoi 400 , and a simulation with Pliocene ice sheets, but preindustrial orography, and 20 at 560 ppmv, is Ei 560 . Note that in all our simulations, orography and lakes and soils are modified in unison, and so "o" denotes changes to orography, bathymetry, land-sea mask, lakes and soils combined.
Within the Pliocene4Future agenda, given the uncertainty in total greenhouse gas forcing for the KM5c time slice, we have proposed a simulation using 450 ppmv CO 2  System processes that may have an effect on radiative forcing, besides greenhouse gas concentrations. For example, Unger and Yue (2014) have demonstrated that chemistry-climate feedbacks, in terms of their radiative forcing, may play as important, or even more important, role as CO 2 during the Pliocene. With a 450 ppmv experiment we also aim to address how uncertainty in radiative forcing can account for high lati-5 tude data/model mismatches that were revealed in PlioMIP Phase 1 (Haywood et al., 2013a;Dowsett et al., 2012Dowsett et al., , 2013aSalzmann et al., 2013). We have also specified a pre-industrial experiment with Pliocene CO 2 as a Tier 1 experiment (E 400 ). This is to facilitate an investigation into Climate (Charney) and Earth System Sensitivity. Within Tier 2 we have proposed two experiments that are designed to assess the 10 dependence of climate sensitivity on the background climate and boundary condition states. Here we wish to to compare the response of the system to CO 2 forcing, between the Pliocene and the modern, by specifying a 560 ppmv CO 2 concentration in both a Pliocene (Eoi 560 ) as well as pre-industrial experiment (E 560  land/sea mask (LSM), topography, bathymetry and ice distribution) are provided. The standard boundary condition data package does not require a modelling group to have the ability to alter the LSM or bathymetry. The enhanced boundary condition requires the ability to change the model's LSM and ocean bathymetry. The standard data package, using an approximately modern LSM, is provided in order to maximise 5 the potential number of participating modelling groups in PlioMIP Phase 2, since it is difficult in some climate models to successfully alter the LSM. Groups that are not able to change their LSMs at all are required to use their own modern LSM. A PRISM4/PlioMIP Phase 2 modern land/sea mask is provided to help guide the implementation of Pliocene topography into different climate models. Groups are asked to 10 make every effort to implement as many of the boundary conditions in the enhanced data packages as possible; however, we recognise that this will not be possible for all groups. The concentration of CO 2 in the atmosphere is to be set to 400 ppmv. In the absence of proxy data, all other trace gases and aerosols are specified to be identical to the individual group's pre-industrial control experiment. When trying to reconstruct Pliocene CO 2 uncertainty is inevitable. Pliocene CO 2 reconstruction is an important ongoing area of research with new records and syntheses (2) carbon isotope analyses (e.g. Raymo et al., 1996), (3) alkenone-based estimates (Pagani et al., 2010;Seki et al., 2010;Badger et al., 2014) and (4) boron isotope analyses (e.g. Seki et al., 2010). For the warm intervals of the Pliocene values of CO 2 from each of these proxies vary, but within error they may overlap (Bartoli et al., 2011). The stomatal density records support a CO 2 concentration of 350 to 380 ppmv. The average 5 of the Raymo et al. (1996) carbon isotope analyses is similar to the stomatal-based estimates, but peaks above that value (beyond 425 ppmv) occur. The Pagani et al. (2010) study reconstructed CO 2 from a number of different marine records, and in three of the six marine records a CO 2 value of 400 is reasonable and within the range of 365 to 415 ppmv. In the Seki et al. (2010) study the alkenone-based CO 2 record is consis-10 tent with a value around 400 ppmv. Badger et al. (2014), have demonstrated that while absolute alkenone-based CO 2 reconstructions are influenced by a number of factors including productivity, cell size, SST, other local palaeoceanographic conditions as well as secondary effects of alkenone δ 13 C, assessments of the degree of variability in CO 2 (rather than absolute concentration) are likely to be more robust, and indicate less than 15 55 ppmv of variation between 3.3 and 2.8 million years ago. Atmospheric CO 2 is an obvious choice for sensitivity tests as part of PlioMIP Phase 2 and is addressed within the experimental design. Information on the concentration of other greenhouse gasses such as Methane and Nitrogen Dioxide is absent and must be prescribed at a preindustrial level. The CO 2 concentrations specified within PlioMIP Phase 2 are therefore 20 designed to account for the total greenhouse gas forcing derived from all sources. The solar constant is to be specified as the same as in each participating group's pre-industrial control run. In the past PRISM boundary conditions  represented an average of the warm intervals during time slab (∼ 3.3 to 3 million yr), rather than conditions occurring during a discrete time slice. This made it impossible to 25 prescribe an orbital configuration which would be representative of the entire 300 000 year interval. However, due to the new focus within PRISM4 and PlioMIP Phase 2 to increase the temporal resolution of proxy records, and to concentrate on a smaller interval of time approaching a time slice reconstruction for MIS KM5c, it is now possible 4014 CPD 11,2015  to provide climate models with more certain values for astronomical and orbital forcing. The KM5c time slice was selected partly on the basis of a strong similarity in orbital forcing to present-day. Therefore, in the interests of simplicity of the experimental design, astronomical/orbital forcing in Pliocene experiments (eccentricity, obliquity, and precession) is to remain unchanged from each models pre-industrial control simula-5 tion.

Palaeogeography (land/sea mask, topography, bathymetry, ocean gateways, land ice)
The PRISM4 palaeogeography provides a consistent reconstruction of topography, bathymetry, ice sheets and the land-sea mask that can be implemented in PlioMIP 10 Phase 2 models. The PRISM4 Pliocene palaeogeography data set is provided in NetCDF format at a 1 • × 1 • resolution. The PRISM4 palaeogeography includes components, such as the contribution of dynamic topography caused by changes in the mantle flow (e.g. Rowley et al., 2013) and the glacial isostatic response of loading specific Pliocene ice sheets (e.g. Raymo et al., 2010), that were not previously considered 15 in the PRISM3D reconstruction of Sohl et al. (2009). In the Standard boundary condition data set all ocean gateways remain the same as the modern except for the Bering Strait that should be closed, and the Canadian Arctic Archipelago which should also be closed (isolating Baffin Bay and the Labrador Sea from the Arctic Ocean). In the enhanced boundary condition data set the Bering Strait and Canadian Arctic Archipelago 20 are also closed, but there are other required changes in the Torres Strait, Java Sea, South China Sea, Kara Strait as well as a West Antarctic Seaway. The approach taken to derive PRISM4 ice sheets in the palaeogeography reconstruction is different to PRISM3D . The results of PLISMIP have shown that ice sheet model dependency over Greenland is low. However, the initial 25 climatological forcing has a large impact on the predicted Greenland ice sheet configuration (Dolan et al., 2014;Koenig et al., 2014). Using a compilation of the results presented in Koenig et al. (2014) Greenland in PRISM4 where we have the highest-confidence in the possibility of ice sheet location during the warmest parts of the Late Pliocene (see Fig. 6b in Koenig et al., 2014). The PRISM4 Greenland Ice Sheet configuration is smaller than in PRISM3D and ice is limited to high elevations in the Eastern Greenland Mountains (Fig. 4). Over Antarctica, work in PLISMIP is still ongoing (de Boer et al., 2015); therefore we 5 have decided to use an ice sheet that best agrees with the available proxy-data. Based on evidence from the ANDRILL core data and ice sheet modelling (Naish et al., 2009;Pollard and DeConto, 2009) that suggests that, in specific warm periods of the Late Pliocene, there was no ice present in West Antarctica, this region remains ice free in the PRISM4 palaeogeography reconstruction (Fig. 4). Over East Antarctica, Cook et 10 al. (2013) show that the Wilkes subglacial basin may have been highly dynamic during the warmest parts of the Late Pliocene and they infer significant potential for ice sheet retreat in this region. Additionally, Young et al. (2011) highlight the Aurora subglacial basin as an area which may have been subject to marine ice sheet instabilities in the past (potentially in the Pliocene). Therefore, over East Antarctica PlioMIP Phase 2 15 uses the PRISM3D ice sheet reconstruction (Hill et al., 2007;Hill, 2009;Dowsett et al., 2010), as this remains consistent with more recently available data. In this reconstruction (Fig. 4) large portions of the East Antarctic ice sheet show little change or a small increase in surface altitude with respect to modern, and significant ice sheet retreat is limited to the low-lying Wilkes and Aurora subglacial basins. 20 For the Pliocene experiments, two versions of the palaeogeography will be provided to climate modelling groups: -Standard: For the models where altering the LSM and bathymetry is problematic, we provide a palaeogeography with a modern land-sea configuration and bathymetry. In this instance the Late Pliocene topographic elevations were ex-25 tended to the modern coastline, and the bathymetry remained at modern values. Groups that are unable to change their land-sea mask or bathymetry at all are asked to use their local modern boundary conditions; however guidance on the implementation of Pliocene topography in this case should be taken from the standard palaeogeography data set.
-Enhanced: This presents the full palaeogeographic reconstruction including all changes to topography, bathymetry, ice sheets and the LSM.
To ensure that the climate anomalies (Pliocene minus present day) from all PlioMIP 5 Phase 2 climate models are directly comparable, i.e. that they reflect differences in the models themselves rather than the differences of modern boundary conditions, it has been decided to implement Pliocene topography (and bathymetry) as an anomaly to whatever standard modern topographic data set is used by each modelling group in their own model.

Vegetation, lakes, soils and rivers
A global data set of vegetation for the core KM5c time slice is not available. A number of climate models now have the ability to predict the type and distribution of vegetation using dynamic vegetation models. In PlioMIP Phase 2 vegetation models should be initialised with pre-industrial vegetation cover and spun up until an equilibrium condition 5 is reached. If Pliocene vegetation cannot be predicted dynamically, modelling groups can prescribe vegetation using the Salzmann et al. (2008) PRISM3 vegetation reconstruction used within PlioMIP Phase 1 (Haywood et al., , 2011, and provided as a mega biome reconstruction in the PlioMIP Phase 2 boundary condition files. An equivalent potential natural vegetation data set is also provided to guide how groups 10 implement prescribed Pliocene vegetation. Further details on correctly approaching the implementation of prescribed Pliocene vegetation for PlioMIP Phase 2 can be found in Haywood et al. (2010, Sect. 3.5). Due to lack of information covering the distribution of lakes and soils during PlioMIP Phase 1, lakes were absent from the land cover boundary conditions. Since PlioMIP 15 Phase 1, the global distribution of Late Pliocene soils and lakes have been reconstructed through a synthesis of geological data (Pound et al., 2014). Initial experiments using the Hadley Centre Coupled Climate Model Version 3 (HadCM3) indicate regionally confined changes of local climate and vegetation in response to the new lakes and soils boundary condition (Pound et al., 2014). When combined (lakes plus soils), the 20 feedbacks on climate from Late Pliocene lakes and soils improve the proxy data-model fit in western North America as well as the southern part of northern Africa (Pound et al., 2014).
In PlioMIP Phase 2 all modelling groups should implement the Pound et al. (2014) data sets for global lake (Fig. 5) and soils distribution (Fig. 6). If lake distribution is a set is not necessary. The lake data set provides information on both lake size as well as the fractional coverage of lakes within model grid boxes. The colour (for albedo) and texture translations for the nine soil orders used in the modelling of Late Pliocene soils and lakes are provided to guide the implementation of soil type and distribution in models. This translation is based upon the definition of 5 soils with the HadCM3 (Table 2).
Groups should implement Pliocene lakes using the anomaly method (the anomaly between the provided Pliocene and modern lake data sets added to each groups local modern lake distribution data set), and ensure that minimum lake fractions do not fall below 0 and the maximum do not exceed 1 (100 %). Groups may implement the 10 Pliocene soils using whatever method they deem most appropriate for their model. This may be by applying the provided Pliocene soil properties directly in their Pliocene simulation (i.e. as an absolute), or by calculating an anomaly from the provided modern soils data, and adding this to the local modern control soil properties. Alternatively, groups may choose to develop a regression of the provided modern soil properties 15 with their local modern control soil properties, and then apply the resulting regression formulae to the provided Pliocene soil properties.
With regard to river routing the required solution is to follow modern river routes except where this would be inappropriate due to the appearance of new land grid cells in the Pliocene land/sea mask, in which case rivers should be routed to the nearest Within the Pliocene for Future agenda a pre-industrial experiment with Pliocene CO 2 has been selected as a Tier 1 experiment (E 400 ). This is to facilitate an investigation 5 into Climate (Charney) and Earth System Sensitivity. Also given the uncertainty in total greenhouse gas forcing for the KM5c time slice, we have proposed a simulation using 450 ppmv CO 2 (Eoi 450 ). Within Tier 2 we have proposed two experiments that are designed to assess how similar climate feedbacks to higher CO 2 are between the Pliocene and the future by specifying a 560 ppmv CO 2 concentration in both a Pliocene 10 (Eoi 560 ) as well as pre-industrial experiment (E 560 ).

Pliocene for Pliocene Tier 1
For the Pliocene for Pliocene agenda we have within Tier 1 focused on the atmospheric CO 2 uncertainty by specifying a high and low CO 2 experiment at 450 and 350 ppmv (Eoi 450 and Eoi 350 , respectively), which provides a 100 ppmv uncertainty 15 bracket around our KM5c core experiment (using 400 ppmv CO 2 ).

Pliocene for Pliocene Tier 2 forcing factorization experiments
The primary aim of the Pliocene for Pliocene Tier 2 forcing factorisation experiments is to assess the relative importance of various boundary condition changes which contribute to Pliocene warmth. Following a similar methodology adopted in Lunt et 20 al. (2012) we intend to partition the total Pliocene warming (or temperature change; ∆T ) into three components, each due to the change in one of the following boundary conditions: CO 2 , topography and ice sheets. Our factorisation, which is that proposed are in addition to simulations already in Tier 1 or the Core. This method, although more computationally demanding than the linear approach (e.g. Broccoli and Manabe, 1987;von Deimling et al., 2006), has the advantage that it takes into account non-linear 10 interactions, is symmetric, and is unique (Table 3).
If groups do not have the computational resource to carry out the full factorisation, they may carry out a linear factorisation, as follows: This is a total of 4 simulations, but only 1 of them (Eo 400 ) in addition to simulations already in Tier 1 or the Core.

Proxy data for the evaluation of model outputs
Short, high-resolution time series extending from MIS M2 through KM3 will be neces-20 sary to meet the evaluation requirements of PlioMIP Phase 2. Marine sequences will depend upon chronology from the Lisiecki and Raymo (2004)  should have multiple palaeoenvironmental proxies. Previous work from the palaeoclimate data community suggests a number of sites potentially suitable for evaluation of PlioMIP Phase 2 model outputs (e.g. Dowsett et al., 2012;2013a, Fedorov, 2013Salzmann et al., 2013;Brigham-Grette et al., 2013). Well dated, high resolution records from continental interiors are scarce, and terrestrial reconstructions will be mostly 5 based on marine and marginal marine sequences. The primary areas of discord between simulated and estimated Pliocene palaeoclimate conditions identified in PlioMIP Phase 1 include the mid-to-high latitude North Atlantic, tropics and upwelling regions. The PRISM4 marine and terrestrial contribution to the PlioMIP Phase 2 community evaluation data set has been initially concentrated in the North Atlantic region (Fig. 7). 10

Variables, output format, data processing and storage
The PlioMIP Phase 2 core experiment has been adopted as a CMIP6 simulation. Therefore, model data for this experiment must use the Climate Model Output Rewriter (CMOR) format and stored on an ESGF node (The Earth System Grid Federation). The CMOR library has been specially developed to help meet the requirements of 15 the Model Intercomparison. Further details of CMIP6 experiments and require outputs and required CMOR file formats will be made available on the CMIP6 website (http://www.wcrp-climate.org/index.php/wgcm-cmip/wgcm-cmip6). For PlioMIP Phase 2 experiments listed within Tiers 1 and 2 more flexibility in terms of data storage and file formats is available. PlioMIP Phase 2 has modified 20 the established variables list outlined by the 3rd Phase of the PMIP project. The list of required variables can be found listed on the PlioMIP Phase 2 website (http: //geology.er.usgs.gov/egpsc/prism/_pliomip2.html). All model outputs will be submitted initially to a data repository at the University of Leeds (including the PlioMIP Phase 2 core experiment which may have data replicated in CMOR format on an ESGF node). 25 In general (CMIP6 guidelines aside) PlioMIP project requires participants to prepare 4022 CPD 11,2015  their data files so that they meet the following constraints (regardless of the way their models produce and store their results).
-The data files have to be in the (now widely used) netCDF binary file format and conform to the CF (Climate and Forecast) metadata convention (outlined on the website http://cf-pcmdi.llnl.gov/).

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-There must be only one output variable per file.
-For the data that are a function of longitude and latitude, only regular grids (grids representable as a Cartesian product of longitude and latitude axes) are allowed.
-The file names have to follow the PMIP2 file name convention and be unique (see the PMIP2 website). Modern files for reference purposes only. Full modern palaeogeography reconstruction including present-day topography, bathymetry, ice sheets and land-sea mask derived from ETOPO1. Global distribution of soil and vegetation characteristics using the same descriptors as the Pliocene reconstruction provided to aid the implementation of Pliocene soil and vegetation characteristics. Soil file also contains the lake distribution and ice-mask information. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Table 3. Details of all experiments proposed in PlioMIP Phase 2 including information on landsea mask (LSM), topography (TOPO), soils, lakes, vegetation, CO 2 and the experiment type (e.g. P4F = Pliocene for Future; P4P = Pliocene for Pliocene). For simplicity of approach we assume that all forcing factorisation experiments will only use the standard rather than enhanced datasets. Prescribed static vegetation is also an option, although dynamically predicted vegetation is preferred. The core experiments are highlighted in bold. Further details about the experimental design can also be found in Supplement 1.