A suite of early Eocene ( 55Ma) climate model boundary conditions · 2020-06-23 · ice existed...

Geosci Model Dev 7 2077ndash2090 2014wwwgeosci-model-devnet720772014doi105194gmd-7-2077-2014copy Author(s) 2014 CC Attribution 30 License

A suite of early Eocene (sim 55 Ma) climate modelboundary conditions

N Herold1 J Buzan2 M Seton3 A Goldner2 J A M Green4 R D Muumlller 3 P Markwick 5 and M Huber16

1Earth Systems Research Center Institute for Earth Ocean and Space Sciences University of New HampshireDurham NH USA2Department of Earth Atmosphere Planetary and Space Sciences Purdue University West Lafayette IN USA3EarthByte Group School of Geosciences University of Sydney Sydney NSW Australia4School of Ocean Sciences Bangor University Menai Bridge UK5Getech Leeds LS8 2LJ UK6Department of Earth Sciences University of New Hampshire Durham NH USA

Correspondence toM Huber (matthewhuberunhedu)

Received 14 December 2013 ndash Published in Geosci Model Dev Discuss 17 January 2014Revised 27 April 2014 ndash Accepted 3 July 2014 ndash Published 16 September 2014

Abstract We describe a set of early Eocene (sim 55 Ma)climate model boundary conditions constructed in a self-consistent reference frame and incorporating recent data andmethodologies Given the growing need for uniform exper-imental design within the Eocene climate modelling com-munity and the challenges faced in simulating the prominentfeatures of Eocene climate we make publicly available ourdata sets of Eocene topography bathymetry tidal dissipa-tion vegetation aerosol distributions and river runoff Majorimprovements in our boundary conditions over previous ef-forts include the implementation of the ANTscape palaeoto-pography of Antarctica more accurate representations of theDrake Passage and Tasman Gateway as well as an approxi-mation of sub grid cell topographic variability Our boundaryconditions also include for the first time modelled estimatesof Eocene aerosol distributions and tidal dissipation bothconsistent with our palaeotopography and palaeobathymetryThe resolution of our data sets is unprecedented and will fa-cilitate high resolution climate simulations In light of the in-herent uncertainties involved in reconstructing global bound-ary conditions for past time periods these data sets shouldbe considered as one interpretation of the available data andusers are encouraged to modify them according to their needsand interpretations This paper marks the beginning of a pro-cess for reconstructing a set of accurate open-access Eoceneboundary conditions for use in climate models

1 Introduction

Growth of the palaeoclimate modelling community has ledto multiple independent efforts in modelling Eocene climate(Lunt et al 2012) The growth in research groups mod-elling Eocene climate as well as the challenges faced bythe community in capturing pertinent aspects of this period(Huber 2012) make it desirable to distribute the boundarycondition data sets used in published research This servestwo purposes (1) that effort is not needlessly duplicated be-tween research groups The construction of boundary con-dition data sets for global climate models takes consider-able effort and expertise Thus unless scientific disagreementexists the process need only be conducted once (2) thatinter-model differences result only from variations in inter-nal model assumptions and computational infrastructure Byholding boundary conditions fixed this enables a greater levelof scientific understanding of the reasons for differences andcommonalities between different groupsrsquo efforts This wasthe impetus for the Paleoclimate Modelling IntercomparisonProject (Braconnot et al 2012) which assesses inter-modelvariation in Quaternary climate simulations and for which aconsistent set of boundary conditions are openly availableInitiatives such as this have successfully fostered collabo-rations between research groups and provide a baseline forthose wishing to conduct Quaternary climate simulations

Published by Copernicus Publications on behalf of the European Geosciences Union

2078 N Herold et al A suite of early Eocene climate model boundary conditions

An ensemble of opportunity assembled in an ad hoc fash-ion ndash designated the Eocene Modelling IntercomparisonProject (EoMIP) ndash has already been conducted using climatesimulations described in studies published over the past sev-eral years (Lunt et al 2012) Consequently each model inthis intercomparison differed at least partially with respectto their prescribed boundary condition forcing In the spiritof encouraging data consistency within the Eocene climatemodelling community we herein document a set of openlyavailable and self-consistent climate model boundary condi-tions for the early Eocene (sim 55 Ma) While their intendedapplication is in climate modelling the broadening domainof geoscientific models may see them applied in a varietyof numerical frameworks (eg Sect 4) Specifically this pa-per describes a newly updated Eocene topography a nec-essary boundary condition for reconstructing past climatesand one with a long history of inquiry (Donn and Shaw1977 Barron et al 1981) An accompanying data set of subgrid cell topographic variability is also provided We includea reconstructed Eocene bathymetry which captures an un-precedented level of detail needed to meet the growing needfor reconstructing regional Eocene oceanography (eg Holliset al 2012) The first estimate of Eocene tidal dissipation(Green and Huber 2013) is also made available comple-menting this recent addition to global climate modelsrsquo suiteof inputs and which may have particular relevance to Eoceneclimate (Lyle 1997) Eocene vegetation simulated by an of-fline dynamic vegetation model is also discussed and pro-vided Simulated Eocene aerosol distributions are provided ndashagain taking advantage of this recent addition to atmosphericmodelsrsquo prognostic capabilities ndash to account for the direct ef-fects of Eocene dust sea salt sulfate and organic and blackcarbon Finally river runoff directions are provided based onthe gradient of Eocene topography All of our data sets withthe exception of aerosol distributions are made available at1

times 1 to facilitate high resolution global and regional sim-ulations

Previous efforts have been made to assemble self-consistent Eocene boundary conditions (Sewall et al 2000Bice et al 1998) and provide motivation for our work hereWhile our boundary conditions incorporate more recent dataand methodologies than most of those used previously thereare many aspects of Eocene tectonics and climate that remainuncertain or controversial Thus in many regions our bound-ary conditions merely reflect one interpretation of the avail-able data and may conflict with alternate interpretations (egelevation of the North American Cordillera) Our aim hereis not to propose a ldquocorrectrdquo set of Eocene boundary con-ditions but to provide boundary conditions that can enablebroader participation by the Eocene climate modelling com-munity as well as greater transparency and reproducibilityamong groups Researchers are encouraged to change thesedata sets based on their own data and interpretations

2 Topography

21 Background and base data set

The palaeogeographic maps first used in climate modelling(Barron 1980 Donn and Shaw 1977) were semi-global inextent and were derived in large by Vinogradov (1967) andPhillips and Forsyth (1972) However the first global Eocenepalaeogeographic map applied to a climate model (Barron1985) was based on the work of Fred Ziegler and his col-leagues at the University of Chicago who had reconstructeda suite of Mesozoic to Cenozoic palaeotopographies (Ziegleret al 1982) These palaeotopographies were built upon andsucceeded by Christopher Scotese in the Paleomap Project(Scotese and Golonka 1992) which was adopted by con-temporary modelling efforts (Sloan and Rea 1996 Sloan1994) Almost a decade later Sewall et al (2000) publisheda new global Eocene topography incorporating the latest re-gional tectonic data (Fig 1a) For over a decade this data sethas remained without update a highly utilized topographyfor Eocene climate modelling (Huber and Caballero 2011Winguth et al 2009 Huber et al 2003 Shellito et al 2009DeConto et al 2012) and thus a data set incorporating morerecent scholarship is overdue

For both our Eocene topography and bathymetry we uti-lize base data sets that have been previously created Herewe adapt the early Eocene palaeotopographic map fromMarkwick (2007) (Fig 1b) This map comes from a suite ofCretaceous to modern palaeotopographies which ndash similar tothe Paleomap Project (Scotese and Golonka 1992) ndash has itsorigins in the Paleogeographic Atlas Project at the Universityof Chicago (Ziegler et al 1982) These maps have been aug-mented with more recent faunal floral and lithological dataand use a more recent rotation model (Rowley 1995 unpub-lished) The primary method used to derive this Eocene to-pography is based on that described by Ziegler et al (1985)and further documented by Markwick (2007) in which con-tour intervals of 1000 m or less are estimated by compar-ing past tectonic regimes to their present day analoguesSubsequent to this adjustments to the palaeo-shoreline aremade based on known Eocene biogeography (see Fig 39Markwick 2007 for a map of known records) Thus thepalaeotopographic map of Markwick (2007) consists of apotential range of elevations for each grid cell instead ofan explicit value A significant benefit of this method overothers (eg Sewall et al 2000) is obviation of the needfor explicit palaeo-elevation estimates ndash which are scarcefor most time periods and regions ndash while providing an ap-proximate yet quantitative description of topography over awide area of the Earth The obvious limitation however isthe lack of precision and topographic detail away from con-tour lines which becomes significant in continental interiorswhere large anomalous plateaus appear (Fig 1b)

Climate models require explicit and globally griddedelevation data so a conversion from the vector-based

Geosci Model Dev 7 2077ndash2090 2014 wwwgeosci-model-devnet720772014

N Herold et al A suite of early Eocene climate model boundary conditions 2079

Figure 1 Eocene topography from(a) Sewall et al (2000)(b) Markwick (2007) and(c) our revised early Eocene topography

Geographic Information Systems approach underlying thetopography of Markwick (2007) to a discrete digital eleva-tion model was necessary More importantly detail in re-gions bounded by contour intervals was needed for whichwe applied a tension spline using the contour lines and sealevel as tie points This creates continuous discrete eleva-tions at all locations In order to provide plausible peak el-evations and gradients along known mountain ranges (egthe North American and Andean Cordilleras) artificial tiepoints were added by inserting mountain spines in these ar-eas The process of interpolation was performed using thecssgrid function (Cubic Spline Sphere Gridder) from the

National Center for Atmospheric Research (NCAR) Com-mand Language (UCARNCARCISLVETS 2013) and aconstant tension factor of 10 which provides a more linearinterpolation between tie points as opposed to a pure cubicspline This latter choice affects the roughness of the areaswe interpolate between contour intervals

22 Topographic revisions

Adjustments were made to conform the topography ofMarkwick (2007) to more recent or broadly accepted re-gional palaeogeographic reconstructions For Antarctica weadopt the ANTscape ldquomaximumrdquo topographic reconstruction(Wilson et al 2012) which incorporates among other im-provements a more elevated West Antarctic bedrock thanprevious reconstructions have recognised (see Fig 1) ThisANTscape reconstruction is specifically for the EocenendashOligocene boundary (sim 34 Ma) However it is significantlycloser to the early Eocene than isostatically relaxed mod-ern day bedrock (DeConto and Pollard 2003 Pollard andDeConto 2005) Our choice of the maximum reconstructionby Wilson et al (2012) is also justified by the fact that thecrust in the early Eocene was younger than at 34 Ma andthat the interpolation required to adapt our topography to agiven climate model inherently smooths high and complexrelief The resolution and scholarship of this reconstruction isalso unprecedented and given that no substantial continentalice existed between the early Eocene and EocenendashOligocenetransition (Cramer et al 2011) uncertainty in the applica-tion of this data set only arises from regional tectonics andnot emplacement of thick ice sheets Future ANTscape re-constructions will include the early Eocene and may forma part of revisions to the global topography presented here(httpwwwantscapeorg)

While our data set provides global coverage of land eleva-tion there are several regions which suffer from large topo-graphic uncertainty and which we highlight here The proto-Himalayas along the southern margin of Eurasia is one sucharea Prior to Indiarsquos collision with Eurasia between 55 and45 Ma geological evidence suggests Eurasiarsquos southern mar-gin may have been up to 4 km high (Molnar et al 2010 andreferences therein) However recent thermochronologic andcosmogenic nuclide data indicate relatively low relief per-sisted prior to collision (Hetzel et al 2011) We choose toleave our data set as provided by Markwick (2007) with apeak elevation of 1500 m which represents an intermediatesolution to these competing uplift histories This is a regionwhere researchers with new data or interpretations may wishto make changes

The uplift history of North American Cordillera is alsosubject to debate Numerous palaeoaltimetry measurementsbased on oxygen isotope geochemistry suggest that westernNorth America was relatively high on the order of 3ndash4 kmsince the early Cenozoic (eg Mix et al 2011) Howeverpalaeobotanical evidence suggests elevations were closer to

wwwgeosci-model-devnet720772014 Geosci Model Dev 7 2077ndash2090 2014


2 km (Wolfe et al 1998) and it is known that atmosphericdynamics upwind of mountain ranges can significantly biasoxygen isotope records toward higher estimates of elevation(Galewsky 2009) Thus we choose to constrain the maxi-mum elevation of this region to the lower end of estimatesapproximately 2500 m (Fig 1c)

Despite the uncertainties in our reconstructed topographythere are several substantial improvements over the recon-struction of Sewall et al (2000) In addition to the changesdiscussed above our topography incorporates a more realis-tic extent of the Mississippi Embayment reducing its areain accordance with marine carbonate coal and peat distri-butions (Sessa et al 2012 Markwick 2007) (Fig 1) TheANTscape Antarctic topography is also substantially moreaccurate than that of Sewall et al (2000) which had an er-roneously small continental area The width of the DrakePassage is also reduced in our reconstruction to be more inaccordance with data which imply an extremely nascent ndashie oceanographically closed ndash gateway in the early Eocene(Barker et al 2007 Lawver et al 2011 Livermore et al2007) Palaeogeographical updates are also applied to Aus-tralia (Langford et al 2001) and Europe (Iakovleva et al2001 Golonka 2011 Torsvik et al 2002) Our final Eocenetopography is shown in Fig 1c

23 Representation of sub grid cell topographicvariability

Numerous details at the sub grid cell scale have importanteffects on resolvable processes in global atmospheric modelsand thus require parameterisation An important detail is thevariation of topography within each grid cell which allowsmodels to parameterise atmospheric gravity waves based onsurface roughness Global atmospheric circulation modelsare sensitive to the parameterised wave drag and to theirwaves These waves are important for the atmospherersquos mo-mentum balance jet stream strength and the vertical trans-port of tracers such as H2O In modern simulations the vari-ability of sub grid cell topography is represented by the stan-dard deviation of elevations within each model grid cell Forexample the variation of topography in a 1

times 1 model gridcell is calculated from the standard deviation of all eleva-tions within the 1 times 1 domain using a 1prime times 1prime data set (egETOPO1 Amante and Eakin 2009) However for past timeperiods knowledge of surface elevation at such a high resolu-tion is impossible To overcome this lack of information andprovide an estimate of the Eocene variability of sub grid celltopography we use an empirical relationship between mod-ern elevation and the standard deviation of sub grid cell to-pography derived from the ETOPO1 data set (Amante andEakin 2009) A script that performs this task on a given to-pographic data set is provided in the Supplement

In Fig 2 we illustrate this process on our 1times 1 Eocene

topography Firstly the modern ETOPO1 topography is re-gridded from its native 1prime times 1prime resolution to 1 times 1 (Fig 2a)

then within each 1 times 1 grid cell the standard deviation ofelevations in the original ETOPO1 data set are calculated(Fig 2b) The Greenland and Antarctic ice sheets are re-placed with the appropriate bedrock topography given thesmoothness of ice compared to continental crust Secondlyan array of 100 m bins are created from 0 to 5500 m ndash rep-resenting the range of modern elevations ndash and the area-weighted average of the standard deviations of the grid cellsthat fall within each bin (calculated in the previous step) arecalculated resulting in an array of 55 values (Fig 2c) Lastlygiven the clear monotonic relation between height and stan-dard deviation between sea level and approximately 3000 mand between 3000 and 5500 m separate linear regressionsare calculated for these intervals (Fig 2c) to assign estimatesof Eocene variability in sub grid cell topography to eachgrid cell (Fig 2d) Given that the maximum elevation in ourEocene topography is less than 3000 m (Fig 1c) only the firstlinear regression is applicable here

Figure 2c shows a peak in standard deviations of approx-imately 800 m at elevations between 2500 and 3500 m Thiscorresponds to the ldquoAndean-typerdquo environments identified byZiegler et al (1985) such as the boundaries of the TibetanPlateau and Andean Cordillera (Fig 2b) This broad peakremains regardless of the resolution we upscale ETOPO1to though its magnitude and width decreases with increas-ing resolution Combined with an adequately derived atmo-spheric lapse rate this data set of sub grid cell scale to-pographic variability may be used to constrain uncertaintyin simulated surface temperatures which result from differ-ences in the palaeo-elevation of a proxy recordrsquos site andthe elevation resolved in a given climate model (eg Huberand Caballero 2011 Sewall et al 2000 Sewall and Sloan2006)

3 Bathymetry


The first bathymetric maps used for Eocene ocean mod-elling constituted bowl-like basins in which the oceanic crustwas treated primarily as abyssal plain (Barron and Peterson1991) The choice of a relatively flat bathymetry althoughdictated to some extent by model resolution and availablegeological data was informed by the lack of large scaleoceanic responses to bathymetric details (Barron and Peter-son 1990) However this result was misleading due to thelack of treatment of crucial oceanic processes in models ofthat generation (eg see Sect 4) The most recent Eocenebathymetric data sets included the locations of mid-oceanridges and shelf slope hypsometry (Bice et al 1998 Huberet al 2003) However given that the highest level of de-tail in these data sets consist of only six depth classes andsim 3

times 15 horizontal resolution substantial gains are to be



Figure 2 Estimating the standard deviation of sub grid cell ele-vations for the Eocene(a) ETOPO1 topography downscaled fromits native 1prime times 1prime resolution to 1 times 1 (b) Standard deviation of1prime

times 1prime elevations inside each 1times 1 grid cell (c) Standard devi-

ations from(b) area-weight averaged into 100 m bins and plottedagainst corresponding elevation Standard error for each bin is plot-ted Dotted lines represent linear regressions between sea level and3000 and 3000 and 5500 m(d) Linear regressions from(c) appliedto Eocene topography (Fig 1c) See text for details

made by employing new methodologies and higher resolu-tion base data sets to reconstruct Eocene bathymetry

The base data set for our bathymetry is formed from theglobal 55 Ma bathymetry of Muumlller et al (2008b) which ispart of a suite of palaeobathymetric maps reconstructed from140 Ma to the present Like previous efforts the foundation ofthis bathymetry is the application of an agendashdepth relation-ship to reconstructed seafloor spreading isochrons As litho-spheric crust ages and cools on its path away from the mid-ocean ridge thinning occurs (Fig 3a and b) In constructingour Eocene bathymetry the agendashdepth relationship derived byStein and Stein (1992) was applied to reconstructed 55 Maseafloor ages

if t lt 20 Ma d(t) = 2600+ 365t12

if t ge 20 Ma d(t) = 5651minus 2473exp(minus00278t)

whered is the basement depth in metres andt is time inMyr Several agendashdepth relationships have been previouslytested to determine the best match to modern bathymetrywith Stein and Stein (1992) showing the least bias (Muumllleret al 2008b) To accommodate regions where Eocene crustis not available at present (due to the subsequent subductionof oceanic crust) symmetric mid-ocean ridge spreading wasassumed and seafloor spreading isochrons from the conju-gate plate applied In regions where no data were availablefrom the conjugate plate interpolation was applied betweenavailable isochrons and the adjacent plate margin (Muumlller etal 2008a b)

On tectonic timescales (Myr) the development of largeigneous provinces (LIPs) can have significant impacts onglobal sea level (Muumlller et al 2008b) and ocean circulation(Lawver et al 2011) thus LIPs form an important com-ponent of our Eocene bathymetry These bathymetric fea-tures are reconstructed by applying modern LIP outlinesand estimating palaeo-LIP height following Schubert andSandwell (1989) Additionally given that certain regions ofthe modern ocean are covered by up to several kilometresof sediment (Whittaker et al 2013) reconstructed sedimentthicknesses also represent an important component of ourreconstructed palaeobathymetry Based on an empirical re-lationship with age and latitude (polar latitudes generallyhaving larger river runoff and tropical latitudes subject tohigh marine productivity) an agendashlatitude relationship wasapplied (Muumlller et al 2008b Supplement) to reconstructEocene sediment thickness (Fig 3c)

32 Bathymetric revisions

While the methodology adopted from Muumlller et al (2008b)represents a substantial improvement over previous bathy-metric maps it is by design a generic process used to re-construct bathymetry over the past 140 Myr Therefore dis-crepancies exist in some regions where palaeoceanographicdata have been recovered Particularly the depths of cer-tain LIPs may be verified against known depth habitats of



Figure 3 55 Ma(a) seafloor age(b) basement depth(c) sediment thickness(d) final bathymetry and(e) the error margin in our bathymetrybased on age uncertainty (values represent the range of uncertainty above and below the bathymetry shown in(d) Black outlines indicatepalaeo-shoreline

foraminifera recovered from deep-sea cores Such a verifica-tion was carried out here using Deep Sea Drilling Project andOcean Drilling Project records Based on these records thedepth of the Madagascar Ridge (Schlich 1974) MascareneRidge (Backman et al 1988 Fisher et al 1974 Vincent etal 1974) Shatsky Rise Ontong Java Plateau (Barrera et al1993) Kerguelen Plateau (Mackensen and Berggren 1992)Walvis Ridge (Zachos et al 2005 Fuetterer 1984) and theRio Grande Rise (Perch-Nielsen et al 1977) were adjusted

Reconstructing the tectonic history of ocean gateways iscritical in explaining past ocean circulation (Scher and Mar-tin 2006 Hill et al 2013) faunal migration patterns (Dalzielet al 2013a) and potentially global climate change (Barkerand Thomas 2004) The Drake Passage and Tasman gatewayare of particular significance given that their opening was arequirement for development of the Antarctic Circumpolar

Current the largest ocean current in the world (sim 130 Sv)and the only circum global one (Barker and Thomas 2004)Unfortunately the Drake Passage suffers from poor age con-straints due to the tectonically complex Scotia arc region andestimates of its opening range from the middle Eocene tolate Miocene (Dalziel et al 2013b Scher and Martin 2006)As our bathymetry represents the early Eocene we prescribean oceanographically closed Drake Passage constraining itsdepth to less than 100 m Multiple palaeoceanographic andtectonic records indicate that the Tasman gateway did notopen to deep flow until the late Eocene (Stickley et al 2004)although when a shallow opening appeared is debatable Ourreconstruction of tectonic plate positions as well as the loca-tion of Tasmania suggests that a shallow epicontinental seamay have existed and thus we prescribe a depth of 30 m orless in the Tasman gateway Finally no data are available for



the bathymetry of inland seas or continental shelves in ourbase data sets and thus we assume a maximum depth of 50 mfor inland seas and use a Poisson equation solver to interpo-late intermediate values for both areas Figure 3d shows ourfinal Eocene bathymetry The uncertainty in this bathymetryis shown in Fig 3e as a function of age uncertainty withlargest values in the southeast and northwest Pacific Ocean(Fig 3a)

33 Consistent plate rotations

The plate rotation model used to construct our palaeo-bathymetry differs from that used for our palaeo-topography(Sect 2) To maintain a consistent reference frame betweenthe two data sets we re-rotate our Eocene topography us-ing the plate rotation model of Muumlller et al (2008b) Thiswas achieved by changing the reference plate (Africa) loca-tion from that determined by Ziegler to that determined byMuumlller et al (2008b) resulting in a relative shift of the othercontinents Refinements to the location of some continentalblocks were made to improve the match between the loca-tions of continental crust in both data sets These steps werelargely achieved using the open source software packagesGPlates (httpwwwgplatesorg) for digitizing polygonsand Generic Mapping Tools (httpgmtsoesthawaiiedu)for manual corrections Deep integration of plate rotationsoftware with open access palaeontology databases has thepotential to streamline future palaeogeographic reconstruc-tions (eg Wright et al 2013) The final merged Eocenetopography and bathymetry is shown in Fig 4 alongsideETOPO1

4 Tidal dissipation

The importance of tidal dissipation in the oceanrsquos generalcirculation stems from the fact that diapycnal (ie verti-cal) mixing is greatly affected by the tidersquos interaction withbathymetry Large increases in diapycnal mixing are ob-served above regions of rough topography (eg Polzin et al1997) and are primarily a result of breaking tidally inducedinternal waves (Garrett and Kunze 2007 Jayne et al 2004)Tidal models have been used to predict the amount of tidalenergy dissipated in the oceans and to better constrain ver-tical mixing profiles incorporated in ocean general circula-tion models (eg Simmons et al 2004) Such experimentshave demonstrated that tidal energy considerations signif-icantly reduce the discrepancy between simulated and ob-served modern ocean heat transport (Simmons et al 2004)and provides motivation for explicitly including tidal dissipa-tion in past climate simulations (eg Green and Huber 2013Egbert et al 2004)

New atmospherendashocean general circulation models are be-ginning to incorporate tidal dissipation (eg the CommunityEarth System Model CESM Gent et al 2011) Green and

Figure 4 (a)ETOPO1 topography and bathymetry(b) new Eocenetopography and bathymetry Both at 1

times 1 resolution

Huber (2013) applied a tidal model using the bathymetry de-scribed in Sect 3 and showed that while total Eocene tidaldissipation was weaker than present a larger amount of tidalenergy was dissipated in the deep ocean especially in thedeep Pacific The vertical diffusivities associated with theseresults are significantly larger than present supporting argu-ments that enhanced vertical mixing in the Eocene oceanshelps to explain the low equator to pole temperature gradientinferred from geological records (eg Lyle 1997) but thathave hitherto been difficult to reproduce in models (Lunt etal 2012)

We distribute the data set from Green and Huber (2013)here as a map of energy dissipated per unit area (Fig 5)Models such as the National Center for Atmospheric Re-search CESM can utilize this data set to drive their tidalmixing schemes While this work represents a coarse firstattempt at deriving Eocene tidal dissipation to our knowl-edge no similar effort has been made and thus this data setprovides a baseline for groups who do not have access to thetools required for deriving this boundary condition Howevergiven the infancy of this application to deep time palaeocli-mate it is likely that such a data set will be improved uponquickly



Figure 5 (a) Modern and(b) Eocene simulated tidal dissipation(Green and Huber 2013)

5 Vegetation

Climate models have long shown substantial global andregional climatic responses to vegetation change (Otto-Bliesner and Upchurch 1997 Dutton and Barron 1997)though newer models indicate a weaker sensitivity (Henrotet al 2010 Micheels et al 2007) A series of Tertiary veg-etation maps based on palaeofloral records (Wolfe 1985)formed the foundation of many early palaeoclimate simu-lations that explicitly included a palaeovegetation boundarycondition (eg Sloan and Rea 1996 Dutton and Barron1997) Subsequently Sewall et al (2000) developed a newEocene vegetation distribution taking into account more re-cent data and the effects of a low equator-to-pole temperaturegradient Like their Eocene topography the vegetation recon-struction of Sewall et al (2000) has remained highly utilizedby the Eocene climate modelling community (eg Huber etal 2003 Liu et al 2009 Roberts et al 2009 Huber andCaballero 2011 Shellito et al 2003)

We choose to reconstruct early Eocene vegetation usingthe offline dynamic vegetation model BIOME4 (Kaplan etal 2003) For input into BIOME4 we use temperature pre-cipitation and cloud cover from a CESM simulation forcedwith the Eocene topography and bathymetry described in

Sects 2 and 3 respectively and an atmospheric CO2 concen-tration of 2240 ppmv a concentration which has been foundto approximately reproduce Eocene temperatures (Huber andCaballero 2011) This CESM simulation was integrated for250 years and initialized with output from a previous CESMsimulation that was integrated for over 3000 years (thislatter simulation was forced with the boundary conditionsof Sewall et al (2000) for topography and vegetation andHuber et al (2003) for bathymetry mixed-layer ocean simu-lations of which are described by Goldner et al (2013)) TheBIOME4 was forced with a CO2 concentration of 1120 ppmvsince higher concentrations resulted in large scale reductionsin tropical forest While this is not consistent with the CO2forcing of the driving climatology we are here only inter-ested in deriving a vegetation distribution that is feasiblyldquoEocenerdquo in character Figure 6a and b shows the simu-lated pre-industrial and Eocene distributions of biomes re-spectively For ease of comparison we show these biomemaps simplified from the 27 biomes simulated by BIOME4to 10 mega biomes after Harrison and Prentice (2003)Our BIOME4 simulated vegetation compares well with veg-etation inferred from Palaeocene and Eocene palynoflora(Utescher and Mosbrugger 2007 Morley 2007) and areconsistent with geological indicators of climate (Crowley2012) One apparent bias is an abundance of relatively dryvegetation in northern South America in BIOME4 (Morley2007) However there remains a distinct lack of records forvalidation from large regions of South Africa and Siberia Wealso note that ldquograssrdquo did not exist at the biome level in theEocene (Stroumlmberg 2011) and thus the ldquoGrassland and dryshrublandrdquo biome presented in Fig 6 should be interpretedas shrubland only Our vegetation reconstruction reflects oursimulated Eocene climate and is therefore less zonal thanprevious reconstructions (Sewall et al 2000) and is consis-tent with our Eocene topography

The utilisation of a single climate simulation to driveBIOME4 inherently results in a vegetation distribution thatencompasses the biases of our climate model While utilisa-tion of ensemble climate model data (Lunt et al 2012) wouldattenuate individual model biases such data sets would dete-riorate the representation of our new topography in the sim-ulated vegetation For example many of the models evalu-ated in EoMIP were forced with the topography of Sewallet al (2000) in which certain continents were several de-grees of latitude or longitude offset from our new topogra-phy Furthermore most of these simulations were run at asubstantially lower resolution than done here Thus utilis-ing such data sets would result in mountainous vegetation ndashfor example over the North American cordillera ndash not com-pletely corresponding to the location of mountain ranges inour topography Such an issue may be improved over time asmore simulations are conducted with the topographic bound-ary condition presented here

Due to the significant differences between modern andEocene topography (Fig 4) the anomaly method typically



Figure 6 (a)Pre-industrial and(b) Eocene vegetation simulated by BIOME4 The 27 biomes simulated by BIOME4 have been consolidatedinto 10 mega biomes following Harrison and Prentice (2003)

used for specifying input into the BIOME4 (Kaplan et al2003) was not possible and thus first order biases in our con-trol CESM simulation are not taken into consideration How-ever given that the CESM simulates modern land and sea-surface temperatures broadly consistent with observations(Gent et al 2011) and that the biases in the modern CESMclimate are small in comparison with the simulated changein climate for the Eocene (Huber and Caballero 2011) we donot believe this to be a significant issue Furthermore whileasynchronous coupling between our climate and vegetationmodels precludes the ability of the simulated vegetation toaffect climate ndash as compared to synchronous coupling efforts(eg Shellito and Sloan 2006a b) ndash it benefits our results bynot erroneously amplifying biases in our climate model (egWohlfahrt et al 2008)

6 Aerosols

Aerosols in Eocene climate simulations have previously beenprescribed at pre-industrial levels or set to arbitrarily deter-mined globally uniform values Aerosols constitute one ofthe largest uncertainties in radiative forcing under future an-thropogenic greenhouse warming (Stocker et al 2013) andmay be important in resolving some long standing palaeo-climate conundrums (Kump and Pollard 2008) Insufficientproxies from the pre-Quaternary prevent the reconstructionof this boundary condition from geological records How-ever the advent of aerosol prognostic capabilities in at-mospheric models allows the palaeo-distribution of variousaerosol species to be simulated (Heavens et al 2012) Herewe again employ the NCAR CESM in a configuration thatutilizes the newly implemented Bulk Aerosol Model whichis a component of the Community Atmosphere Model 4(Neale et al 2010) In this configuration the model explicitlysimulates the monthly horizontal and vertical distribution ofdust sea salt sulfate and organic and black carbon aerosolsconsistent with our Eocene topography (Fig 7) The BulkAerosol Model makes simplistic assumptions regarding the

size distribution of aerosol species compared to the morecomplicated Modal Aerosol Models A detailed descriptionof the steps involved in simulating the palaeo-distributionof aerosols is provided by Heavens et al (2012) Here webranch the same CESM simulation described in Sect 5 whilealso enabling the Bulk Aerosol Model

Various aerosol species require the prescription of emis-sion sources in the Bulk Aerosol Model and this is done inaccordance with Heavens et al (2012) One exception is thatwe do not specify any volcanic sources of SO2 or SO4 giventheir small radiative effects and the uncertainty in the distri-bution of Eocene volcanoes Another largely unconstrainedyet climatically relevant emission source in the Bulk AerosolModel is that of dust In the Bulk Aerosol Model dust isemitted solely from the desert plant functional type whichin turn is determined from the prescribed vegetation dataset It is generally understood that cooler climates promotemore dust-laden atmospheres ndash due to increases in desertifi-cation reduced soil moisture and stronger winds (Bar-Or etal 2008) However the degree to which global Eocene dustconcentrations differed from typical glacialndashinterglacial vari-ability is uncertain though regional evidence exists for sub-stantially weak dust fluxes in the early Cenozoic (Janecekand Rea 1983) Here we have assumed that global Eocenedust loading was approximately three quarters that of the pre-industrial era The sources of dust in our data set (ie deserts)were manually distributed based loosely on the distributionof early Eocene evaporites (Crowley 2012) which itselffollows the expected distribution of subtropical high pres-sure regions Our chosen concentrations provide an Eocenedust loading intermediate to simulations which prescribe pre-industrial values (eg Heinemann et al 2009 Lunt et al2010 Winguth et al 2009) and those which eliminate theradiative effects of aerosols altogether (Huber and Caballero2011) The significant improvement in the approach takenhere is that the distribution of aerosols is consistent with ourEocene topography providing a realistic regional representa-tion of their radiative forcing



Figure 7 (a) Pre-industrial and(b) Eocene aerosol optical depth(unitless) simulated by the Community Atmosphere Model 4

It is important to stress the large uncertainty in aerosolloading and distribution during past climates and that oursimulated concentrations are likely highly model dependantFurthermore the aerosol data sets provided here are only ad-equate for models that do not include the indirect effects ofaerosols Models that include such effects may exhibit signif-icant sensitivity to even slight changes in aerosol distributionand loading and we are not confident that the use of the datasets presented here given the uncertainties involved wouldbe scientifically sound

Finally we note that the ability to prognose aerosol distri-butions in long climate simulations (available in the latest at-mospheric models though at significant computational cost)will obviate the need for prescribed aerosol concentrationswhile also accounting for their indirect effects Such modelswill see the emission sources of various aerosol species (egdeserts volcanoes regions of high marine productivity) be-come an additional palaeoclimate model boundary condition

Figure 8 Eocene river runoff directions Directions indicated bycolour

7 River transport

River runoff in current generation climate models is impor-tant primarily for the redistribution of fresh water to theoceans and can have significant implications for deep wa-ter formation (eg Bice et al 1997) Here we use the gra-dient of our Eocene topography to represent river runoffdirection (Fig 8) This data set was created using scriptsmade available by the National Center for Atmospheric Re-search (Rosenbloom et al 2011) Regions where vectors donot reach the ocean (ie internal basins) were manually cor-rected Topographic gradient has been used to constrain riverdirections in the overwhelming majority of palaeoclimatesimulations to date However it is a crude method whichwe show here simply for completeness Furthermore thedata set provided (Fig 7) is only illustrative as the regrid-ding of our topography (Fig 1) to a given climate modelrsquosresolution will require re-calculation of these river direc-tions to account for changes in gradient A more morpho-logically constrained river direction data set (eg Markwickand Valdes 2004) should be integrated into future revisionsof our Eocene boundary conditions

8 Discussion and future work

We describe an openly available and comprehensive set ofearly Eocene climate model boundary conditions includ-ing topography bathymetry tidal dissipation vegetationaerosols and river transport The resolution of most of thesedata sets is unprecedented and alleviates the undesirable stepof upscaling lower resolution data sets to that of current gen-eration climate models This should lead to improvements inmodelndashdata comparison in regions of strong relief and facili-tate high resolution global and regional climate simulations

An important distinction between our tidal vegetationaerosol data sets and our topography and bathymetry datasets is that the former are model derived and thus not directlybased on measured physical quantities The use of modelling



frameworks for our tidal and aerosol boundary conditions isnecessitated by the absence of any quantitative Eocene dataOur use of a model to derive Eocene vegetation was predi-cated on the modelrsquos ability to capture what is known aboutEocene vegetation from palaeobotanical records (model val-idation) As this is the case (see Sect 5) we can havean at least (or perhaps at best) satisfactory level of confi-dence that the model is not predicting unrealistic vegetationin regions where data are scarce This eliminates the needfor researchers to subjectively estimate vegetation for largeswathes of land though of course is directly affected by theclimate biases of our driving climatology

Despite the substantial improvements introduced in theseboundary conditions uncertainties in the data remain Theseare most pertinent in the palaeo-elevation of the North Amer-ican Cordillera and proto-Himalayas the geometry of theDrake Passage and Tasman Gateway our modelled tidal dis-sipation and aerosol distributions and lastly our rudimentaryrepresentation of river runoff These data- and model-baseduncertainties provide a natural focus for future research indeveloping new methods of inquiry (or eliminating old ones)and in focusing efforts on data collection Reconciling tec-tonic models and palaeo-elevation proxies will be crucial forreducing palaeotopographic uncertainty in revised versionsof these boundary conditions On the other hand advancesin modelling may substantially improve the reconstructionof tidal dissipation and aerosol distributions though quanti-tative validation of either of these in the Eocene is next toimpossible

Finally as important as the input into any model repre-senting a real-world system is an at least equal importanceshould be placed on the data against which such modelsare validated Fortunately recent compilations of terrestrialand marine data have already been conducted by Huber andCaballero (2011) and Lunt et al (2012) respectively Westress that the maintenance and public availability of suchdata sets provides the necessary yardstick against which tocompare all models Users are also able to rotate newlycollected data to their 55 Ma position in the same refer-ence frame used here via the open source software packageGPlates (httpwwwgplatesorg) thus ensuring that consis-tency in georeferencing is maintained A community effortto adopt consistent modelling methodologies and boundaryconditions can accelerate growth in our understanding ofEocene climates and specifically help highlight the most per-tinent shortcomings of the current generation of climate mod-els in simulating extreme greenhouse warmth

The Supplement related to this article is available onlineat doi105194gmd-7-2077-2014-supplement

AcknowledgementsN Herold J Buzan A Goldner and M Hu-ber are supported under1049921-EAR Collaborative ResearchImproved Cenozoic paleoelevation estimates for the Sierra NevadaCalifornia Linking geodynamics with atmospheric dynamicsM Seton and R D Muumlller acknowledge support from AustralianResearch Council (ARC) grants DP0987713 and FL0992245respectively The tidal model simulations were funded by theNatural Environmental Research Council (grant NEF0148211)and the Climate Change Consortium for Wales (JAMG) and theNational Science Foundation (grant 0927946-ATM to M Huber)The NCAR Command Language (NCL) was used to create ourfigures NCL and Generic Mapping Tools were used for themanipulation of data

Edited by D Lunt

References

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Barron E J Paleogeography and Climate 180 Million Years to thePresent University of MIAMI 1980

Barron E J Explanations of the Tertiary global cooling trendPalaeogeogr Palaeocl 50 45ndash61 1985

Barron E J and Peterson W H Mid-Cretaceous ocean circula-tion Results from model sensitivity studies Paleoceanography5 319ndash337 doi101029PA005i003p00319 1990

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Barron E J Thompson S L and Schneider S H An Ice-FreeCretaceous Results from Climate Model Simulations Science212 501-508 doi101126science2124494501 1981

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Cramer B S Miller K G Barrett P J and Wright J D LateCretaceousndashNeogene trends in deep ocean temperature and con-tinental ice volume Reconciling records of benthic foraminiferalgeochemistry (δ18O and MgCa) with sea level history J Geo-phys Res-Oceans 116 C12023 doi1010292011jc0072552011

Crowley C W An atlas of Cenozoic climates Masters of sciencein geology The University of Texas 2012

Dalziel I W D Lawver L A Norton I O and Gahagan LM The Scotia Arc Genesis Evolution Global SignificanceAnnu Rev Earth Pl Sc 41 767ndash793 doi101146annurev-earth-050212-124155 2013a

Dalziel I W D Lawver L A Pearce J A Barker P F HastieA R Barfod D N Schenke H-W and Davis M B A po-tential barrier to deep Antarctic circumpolar flow until the lateMiocene Geology 41 947ndash950 doi101130g343521 2013b

DeConto R M and Pollard D Rapid Cenozoic glaciation ofAntarctica induced by declining atmospheric CO2 Nature 421245ndash249 2003

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Donn W L and Shaw D M Model of climate evo-lution based on continental drift and polar wanderingGeol Soc Am Bull 88 390ndash396 doi1011300016-7606(1977)88lt390mocebogt20co2 1977

Dutton J F and Barron E J Miocene to present vegetationchanges a possible piece of the Cenozoic cooling puzzle Ge-ology 25 39ndash41 1997

Egbert G D Ray R D and Bills B G Numerical model-ing of the global semidiurnal tide in the present day and in thelast glacial maximum J Geophys Res-Oceans 109 C03003doi1010292003jc001973 2004

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Galewsky J Orographic precipitation isotopic ratios in stratifiedatmospheric flows Implications for paleoelevation studies Ge-ology 37 791ndash794 doi101130g30008a1 2009

Garrett C and Kunze E Internal Tide Generation inthe Deep Ocean Annu Rev Fluid Mech 39 57ndash87doi101146annurevfluid39050905110227 2007

Gent P R Danabasoglu G Donner L J Holland M M HunkeE C Jayne S R Lawrence D M Neale R B Rasch P JVertenstein M Worley P H Yang Z-L and Zhang M TheCommunity Climate System Model Version 4 J Climate 244973ndash4991 doi1011752011jcli40831 2011

Goldner A Huber M and Caballero R Does Antarctic glacia-tion cool the world Clim Past 9 173ndash189 doi105194cp-9-173-2013 2013

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Green J A M and Huber M Tidal dissipation in the early Eoceneand implications for ocean mixing Geophys Res Lett 402707ndash2713 doi101002grl50510 2013

Harrison S P and Prentice C I Climate and CO2 controlson global vegetation distribution at the last glacial maximumAnalysis based on palaeovegetation data biome modelling andpalaeoclimate simulations Global Change Biol 9 983ndash10042003

Heavens N G Shields C A and Mahowald N M A paleogeo-graphic approach to aerosol prescription in simulations of deeptime climate Journal of Advances in Modeling Earth Systems4 M11002 doi1010292012ms000166 2012

Heinemann M Jungclaus J H and Marotzke J Warm Pale-oceneEocene climate as simulated in ECHAM5MPI-OM ClimPast 5 785ndash802 doi105194cp-5-785-2009 2009

Henrot A-J Franccedilois L Favre E Butzin M Ouberdous Mand Munhoven G Effects of CO2 continental distribution to-pography and vegetation changes on the climate at the MiddleMiocene a model study Clim Past 6 675ndash694 doi105194cp-6-675-2010 2010

Hetzel R Dunkl I Haider V Strobl M von Eynatten H DingL and Frei D Peneplain formation in southern Tibet predatesthe India-Asia collision and plateau uplift Geology 39 983ndash986 doi101130g320691 2011

Hill D J Haywood A M Valdes P J Francis J E Lunt DJ Wade B S and Bowman V C Paleogeographic controlson the onset of the Antarctic circumpolar current Geophys ResLett 40 5199ndash5204 doi101002grl50941 2013

Hollis C J Taylor K W R Handley L Pancost R D HuberM Creech J B Hines B R Crouch E M Morgans H EG Crampton J S Gibbs S Pearson P N and Zachos JC Early Paleogene temperature history of the Southwest PacificOcean Reconciling proxies and models Earth Planet Sc Lett349ndash350 53ndash66 doi101016jepsl201206024 2012

Huber M Progress in greenhouse climate modelling in Recon-structing Earthrsquos Deep-Time Climate edited by Linda Ivany BH Paleontological Society 2012

Huber M and Caballero R The early Eocene equable climateproblem revisited Clim Past 7 603ndash633 doi105194cp-7-603-2011 2011

Huber M Sloan L C and Shellito C Early Paleogene oceansand climate fully coupled modeling approach using the NCARCCSM in Causes and consequences of globally warm climatesin the early Paleogene edited by Wing S L Gingerich P DSchmitz B and Thomas E Geological Society of America(GSA) Boulder CO 2003

Iakovleva A I Brinkhuis H and Cavagnetto C LatePalaeocenendashEarly Eocene dinoflagellate cysts from the Tur-gay Strait Kazakhstan correlations across ancient seawaysPalaeogeogr Palaeocl 172 243ndash268 doi101016S0031-0182(01)00300-5 2001

Janecek T R and Rea D K Eolian deposition in the north-east Pacific Ocean Cenozoic history of atmospheric circu-



lation Geol Soc Am B 94 730ndash738 doi1011300016-7606(1983)94lt730editnpgt20co2 1983

Jayne S R Laurent L C S and Gille S T Connections Be-tween Ocean Bottom Topography and Earthrsquos Climate Oceanog-raphy 17 65ndash74 2004

Kaplan J O Bigelow N H Prentice I C Harrison S PBartlein P J Christensen T R Cramer W Matveyeva NV McGuire A D Murray D F Razzhivin V Y SmithB Walker D A Anderson P M Andreev A A BrubakerL B Edwards M E and Lozhkin A V Climate changeand Arctic ecosystems 2 Modeling paleodata-model compar-isons and future projections J Geophys Res 108 8171doi1010292002jd002559 2003

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Lawver L A Gahagan L M and Dalziel I W D A DifferentLook at Gateways Drake Passage and AustraliaAntarctica inTectonic Climatic and Cryospheric Evolution of the AntarcticPeninsula American Geophysical Union 5ndash33 2011

Liu Z Pagani M Zinniker D DeConto R Huber MBrinkhuis H Shah S R Leckie R M and Pearson AGlobal Cooling During the Eocene-Oligocene Climate Tran-sition Science 323 1187ndash1190 doi101126science11663682009

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Lunt D J Valdes P J Jones T D Ridgwell A HaywoodA M Schmidt D N Marsh R and Maslin M CO2-drivenocean circulation changes as an amplifier of Paleocene-Eocenethermal maximum hydrate destabilization Geology 38 875ndash878 doi101130g311841 2010

Lunt D J Dunkley Jones T Heinemann M Huber MLeGrande A Winguth A Loptson C Marotzke J RobertsC D Tindall J Valdes P and Winguth C A model-data comparison for a multi-model ensemble of early Eoceneatmosphere-ocean simulations EoMIP Clim Past 8 1717ndash1736 doi105194cp-8-1717-2012 2012

Lyle M Could early Cenozoic thermohaline circulation havewarmed the poles Paleoceanography 12 161ndash167 1997

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An ensemble of opportunity assembled in an ad hoc fash-ion ndash designated the Eocene Modelling IntercomparisonProject (EoMIP) ndash has already been conducted using climatesimulations described in studies published over the past sev-eral years (Lunt et al 2012) Consequently each model inthis intercomparison differed at least partially with respectto their prescribed boundary condition forcing In the spiritof encouraging data consistency within the Eocene climatemodelling community we herein document a set of openlyavailable and self-consistent climate model boundary condi-tions for the early Eocene (sim 55 Ma) While their intendedapplication is in climate modelling the broadening domainof geoscientific models may see them applied in a varietyof numerical frameworks (eg Sect 4) Specifically this pa-per describes a newly updated Eocene topography a nec-essary boundary condition for reconstructing past climatesand one with a long history of inquiry (Donn and Shaw1977 Barron et al 1981) An accompanying data set of subgrid cell topographic variability is also provided We includea reconstructed Eocene bathymetry which captures an un-precedented level of detail needed to meet the growing needfor reconstructing regional Eocene oceanography (eg Holliset al 2012) The first estimate of Eocene tidal dissipation(Green and Huber 2013) is also made available comple-menting this recent addition to global climate modelsrsquo suiteof inputs and which may have particular relevance to Eoceneclimate (Lyle 1997) Eocene vegetation simulated by an of-fline dynamic vegetation model is also discussed and pro-vided Simulated Eocene aerosol distributions are provided ndashagain taking advantage of this recent addition to atmosphericmodelsrsquo prognostic capabilities ndash to account for the direct ef-fects of Eocene dust sea salt sulfate and organic and blackcarbon Finally river runoff directions are provided based onthe gradient of Eocene topography All of our data sets withthe exception of aerosol distributions are made available at1

times 1 to facilitate high resolution global and regional sim-ulations

Previous efforts have been made to assemble self-consistent Eocene boundary conditions (Sewall et al 2000Bice et al 1998) and provide motivation for our work hereWhile our boundary conditions incorporate more recent dataand methodologies than most of those used previously thereare many aspects of Eocene tectonics and climate that remainuncertain or controversial Thus in many regions our bound-ary conditions merely reflect one interpretation of the avail-able data and may conflict with alternate interpretations (egelevation of the North American Cordillera) Our aim hereis not to propose a ldquocorrectrdquo set of Eocene boundary con-ditions but to provide boundary conditions that can enablebroader participation by the Eocene climate modelling com-munity as well as greater transparency and reproducibilityamong groups Researchers are encouraged to change thesedata sets based on their own data and interpretations

2 Topography


The palaeogeographic maps first used in climate modelling(Barron 1980 Donn and Shaw 1977) were semi-global inextent and were derived in large by Vinogradov (1967) andPhillips and Forsyth (1972) However the first global Eocenepalaeogeographic map applied to a climate model (Barron1985) was based on the work of Fred Ziegler and his col-leagues at the University of Chicago who had reconstructeda suite of Mesozoic to Cenozoic palaeotopographies (Ziegleret al 1982) These palaeotopographies were built upon andsucceeded by Christopher Scotese in the Paleomap Project(Scotese and Golonka 1992) which was adopted by con-temporary modelling efforts (Sloan and Rea 1996 Sloan1994) Almost a decade later Sewall et al (2000) publisheda new global Eocene topography incorporating the latest re-gional tectonic data (Fig 1a) For over a decade this data sethas remained without update a highly utilized topographyfor Eocene climate modelling (Huber and Caballero 2011Winguth et al 2009 Huber et al 2003 Shellito et al 2009DeConto et al 2012) and thus a data set incorporating morerecent scholarship is overdue

For both our Eocene topography and bathymetry we uti-lize base data sets that have been previously created Herewe adapt the early Eocene palaeotopographic map fromMarkwick (2007) (Fig 1b) This map comes from a suite ofCretaceous to modern palaeotopographies which ndash similar tothe Paleomap Project (Scotese and Golonka 1992) ndash has itsorigins in the Paleogeographic Atlas Project at the Universityof Chicago (Ziegler et al 1982) These maps have been aug-mented with more recent faunal floral and lithological dataand use a more recent rotation model (Rowley 1995 unpub-lished) The primary method used to derive this Eocene to-pography is based on that described by Ziegler et al (1985)and further documented by Markwick (2007) in which con-tour intervals of 1000 m or less are estimated by compar-ing past tectonic regimes to their present day analoguesSubsequent to this adjustments to the palaeo-shoreline aremade based on known Eocene biogeography (see Fig 39Markwick 2007 for a map of known records) Thus thepalaeotopographic map of Markwick (2007) consists of apotential range of elevations for each grid cell instead ofan explicit value A significant benefit of this method overothers (eg Sewall et al 2000) is obviation of the needfor explicit palaeo-elevation estimates ndash which are scarcefor most time periods and regions ndash while providing an ap-proximate yet quantitative description of topography over awide area of the Earth The obvious limitation however isthe lack of precision and topographic detail away from con-tour lines which becomes significant in continental interiorswhere large anomalous plateaus appear (Fig 1b)

Climate models require explicit and globally griddedelevation data so a conversion from the vector-based





















3 Bathymetry











if t lt 20 Ma d(t) = 2600+ 365t12

















4 Tidal dissipation




times 1 resolution






5 Vegetation










6 Aerosols










7 River transport












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3 Bathymetry











if t lt 20 Ma d(t) = 2600+ 365t12

















4 Tidal dissipation




times 1 resolution






5 Vegetation










6 Aerosols










7 River transport












Edited by D Lunt

References




























































































































3 Bathymetry











if t lt 20 Ma d(t) = 2600+ 365t12

















4 Tidal dissipation




times 1 resolution






5 Vegetation










6 Aerosols










7 River transport












Edited by D Lunt

References
























































































































if t lt 20 Ma d(t) = 2600+ 365t12

















4 Tidal dissipation




times 1 resolution






5 Vegetation










6 Aerosols










7 River transport












Edited by D Lunt

References




























































































































4 Tidal dissipation




times 1 resolution






5 Vegetation










6 Aerosols










7 River transport












Edited by D Lunt

References






















































































































4 Tidal dissipation




times 1 resolution






5 Vegetation










6 Aerosols










7 River transport












Edited by D Lunt

References




















































































































5 Vegetation










6 Aerosols










7 River transport












Edited by D Lunt

References





















































































































6 Aerosols










7 River transport












Edited by D Lunt

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7 River transport












Edited by D Lunt

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A suite of early Eocene ( 55Ma) climate model boundary conditions · 2020-06-23 · ice existed...

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