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A suite of early Eocene (~ 55 Ma) climate model boundary conditions

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We describe a set of early Eocene (~ 55 Ma) climate model boundary conditions constructed in a self-consistent reference frame and incorporating recent data and methodologies. Given the growing need for uniform experimental design within the Eocene climate modelling community and the challenges faced in simulating the prominent features of Eocene climate, we make publicly available our data sets of Eocene topography, bathymetry, tidal dissipation, vegetation, aerosol distributions and river runoff. Major improvements in our boundary conditions over previous efforts include the implementation of the ANTscape palaeotopography of Antarctica, more accurate representations of the Drake Passage and Tasman Gateway, as well as an approximation of sub grid cell topographic variability. Our boundary conditions also include for the first time modelled estimates of Eocene aerosol distributions and tidal dissipation, both consistent with our palaeotopography and palaeobathymetry. The resolution of our data sets is unprecedented and will facilitate high resolution climate simulations. In light of the inherent uncertainties involved in reconstructing global boundary conditions for past time periods these data sets should be considered as one interpretation of the available data and users are encouraged to modify them according to their needs and interpretations. This paper marks the beginning of a process for reconstructing a set of accurate, open-access Eocene boundary conditions for use in climate models.
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Geosci. Model Dev., 7, 2077–2090, 2014
www.geosci-model-dev.net/7/2077/2014/
doi:10.5194/gmd-7-2077-2014
© Author(s) 2014. CC Attribution 3.0 License.
A suite of early Eocene (55Ma) climate model
boundary conditions
N. Herold1, J. Buzan2, M. Seton3, A. Goldner2, J. A. M. Green4, R. D. Müller3, P. Markwick5, and M. Huber1,6
1Earth Systems Research Center, Institute for Earth, Ocean and Space Sciences, University of New Hampshire,
Durham, NH, USA
2Department of Earth, Atmosphere, Planetary and Space Sciences, Purdue University, West Lafayette, IN, USA
3EarthByte Group, School of Geosciences, University of Sydney, Sydney NSW, Australia
4School of Ocean Sciences, Bangor University, Menai Bridge, UK
5Getech, Leeds, LS8 2LJ, UK
6Department of Earth Sciences, University of New Hampshire, Durham, NH, USA
Correspondence to: M. Huber (matthew.huber@unh.edu)
Received: 14 December 2013 – Published in Geosci. Model Dev. Discuss.: 17 January 2014
Revised: 27 April 2014 – Accepted: 3 July 2014 – Published: 16 September 2014
Abstract. We describe a set of early Eocene (55Ma)
climate model boundary conditions constructed in a self-
consistent reference frame and incorporating recent data and
methodologies. Given the growing need for uniform exper-
imental design within the Eocene climate modelling com-
munity and the challenges faced in simulating the prominent
features of Eocene climate, we make publicly available our
data sets of Eocene topography, bathymetry, tidal dissipa-
tion, vegetation, aerosol distributions and river runoff. Major
improvements in our boundary conditions over previous ef-
forts include the implementation of the ANTscape palaeoto-
pography of Antarctica, more accurate representations of the
Drake Passage and Tasman Gateway, as well as an approxi-
mation of sub grid cell topographic variability. Our boundary
conditions also include for the first time modelled estimates
of Eocene aerosol distributions and tidal dissipation, both
consistent with our palaeotopography and palaeobathymetry.
The 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 should
be considered as one interpretation of the available data and
users are encouraged to modify them according to their needs
and interpretations. This paper marks the beginning of a pro-
cess for reconstructing a set of accurate, open-access Eocene
boundary conditions for use in climate models.
1 Introduction
Growth of the palaeoclimate modelling community has led
to 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 by
the community in capturing pertinent aspects of this period
(Huber, 2012) make it desirable to distribute the boundary
condition data sets used in published research. This serves
two 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 disagreement
exists, the process need only be conducted once; (2) that
inter-model differences result only from variations in inter-
nal model assumptions and computational infrastructure. By
holding boundary conditions fixed this enables a greater level
of scientific understanding of the reasons for differences and
commonalities between different groups’ efforts. This was
the impetus for the Paleoclimate Modelling Intercomparison
Project (Braconnot et al., 2012), which assesses inter-model
variation in Quaternary climate simulations and for which a
consistent set of boundary conditions are openly available.
Initiatives such as this have successfully fostered collabo-
rations between research groups and provide a baseline for
those 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 – designated the Eocene Modelling Intercomparison
Project (EoMIP) – has already been conducted using climate
simulations described in studies published over the past sev-
eral years (Lunt et al., 2012). Consequently, each model in
this intercomparison differed at least partially with respect
to their prescribed boundary condition forcing. In the spirit
of encouraging data consistency within the Eocene climate
modelling community we herein document a set of openly
available and self-consistent climate model boundary condi-
tions for the early Eocene (55Ma). While their intended
application is in climate modelling, the broadening domain
of geoscientific models may see them applied in a variety
of numerical frameworks (e.g. Sect. 4). Specifically, this pa-
per describes a newly updated Eocene topography, a nec-
essary boundary condition for reconstructing past climates
and one with a long history of inquiry (Donn and Shaw,
1977; Barron et al., 1981). An accompanying data set of sub
grid cell topographic variability is also provided. We include
a reconstructed Eocene bathymetry, which captures an un-
precedented level of detail needed to meet the growing need
for reconstructing regional Eocene oceanography (e.g. Hollis
et 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 models’ suite
of inputs and which may have particular relevance to Eocene
climate (Lyle, 1997). Eocene vegetation simulated by an of-
fline dynamic vegetation model is also discussed and pro-
vided. Simulated Eocene aerosol distributions are provided –
again taking advantage of this recent addition to atmospheric
models’ prognostic capabilities – to account for the direct ef-
fects of Eocene dust, sea salt, sulfate, and organic and black
carbon. Finally, river runoff directions are provided based on
the gradient of Eocene topography. All of our data sets, with
the exception of aerosol distributions, are made available at
1×1to facilitate high resolution global and regional sim-
ulations.
Previous efforts have been made to assemble self-
consistent Eocene boundary conditions (Sewall et al., 2000;
Bice et al., 1998) and provide motivation for our work here.
While our boundary conditions incorporate more recent data
and methodologies than most of those used previously, there
are many aspects of Eocene tectonics and climate that remain
uncertain 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 (e.g.
elevation of the North American Cordillera). Our aim here
is not to propose a “correct” set of Eocene boundary con-
ditions but to provide boundary conditions that can enable
broader participation by the Eocene climate modelling com-
munity as well as greater transparency and reproducibility
among groups. Researchers are encouraged to change these
data sets based on their own data and interpretations.
2 Topography
2.1 Background and base data set
The palaeogeographic maps first used in climate modelling
(Barron, 1980; Donn and Shaw, 1977) were semi-global in
extent and were derived in large by Vinogradov (1967) and
Phillips and Forsyth (1972). However, the first global Eocene
palaeogeographic map applied to a climate model (Barron,
1985) was based on the work of Fred Ziegler and his col-
leagues at the University of Chicago, who had reconstructed
a suite of Mesozoic to Cenozoic palaeotopographies (Ziegler
et al., 1982). These palaeotopographies were built upon and
succeeded by Christopher Scotese in the Paleomap Project
(Scotese and Golonka, 1992), which was adopted by con-
temporary modelling efforts (Sloan and Rea, 1996; Sloan,
1994). Almost a decade later, Sewall et al. (2000) published
a new global Eocene topography incorporating the latest re-
gional tectonic data (Fig. 1a). For over a decade this data set
has remained, without update, a highly utilized topography
for Eocene climate modelling (Huber and Caballero, 2011;
Winguth et al., 2009; Huber et al., 2003; Shellito et al., 2009;
DeConto et al., 2012), and thus a data set incorporating more
recent scholarship is overdue.
For both our Eocene topography and bathymetry we uti-
lize base data sets that have been previously created. Here
we adapt the early Eocene palaeotopographic map from
Markwick (2007) (Fig. 1b). This map comes from a suite of
Cretaceous to modern palaeotopographies which – similar to
the Paleomap Project (Scotese and Golonka, 1992) – has its
origins in the Paleogeographic Atlas Project at the University
of Chicago (Ziegler et al., 1982). These maps have been aug-
mented with more recent faunal, floral and lithological data
and 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 1000m or less are estimated by compar-
ing past tectonic regimes to their present day analogues.
Subsequent to this, adjustments to the palaeo-shoreline are
made based on known Eocene biogeography (see Fig. 39
Markwick, 2007, for a map of known records). Thus, the
palaeotopographic map of Markwick (2007) consists of a
potential range of elevations for each grid cell, instead of
an explicit value. A significant benefit of this method over
others (e.g. Sewall et al., 2000) is obviation of the need
for explicit palaeo-elevation estimates – which are scarce
for most time periods and regions – while providing an ap-
proximate yet quantitative description of topography over a
wide area of the Earth. The obvious limitation, however, is
the lack of precision and topographic detail away from con-
tour lines, which becomes significant in continental interiors
where large anomalous plateaus appear (Fig. 1b).
Climate models require explicit and globally gridded
elevation data so a conversion from the vector-based
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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 the
topography 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 which
we applied a tension spline using the contour lines and sea
level 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 (e.g.
the North American and Andean Cordilleras) artificial tie
points were added by inserting mountain spines in these ar-
eas. The process of interpolation was performed using the
cssgrid function (Cubic Spline Sphere Gridder) from the
National Center for Atmospheric Research (NCAR) Com-
mand Language (UCAR/NCAR/CISL/VETS, 2013) and a
constant tension factor of 10, which provides a more linear
interpolation between tie points as opposed to a pure cubic
spline. This latter choice affects the roughness of the areas
we interpolate between contour intervals.
2.2 Topographic revisions
Adjustments were made to conform the topography of
Markwick (2007) to more recent or broadly accepted re-
gional palaeogeographic reconstructions. For Antarctica we
adopt the ANTscape “maximum” topographic reconstruction
(Wilson et al., 2012) which incorporates, among other im-
provements, a more elevated West Antarctic bedrock than
previous reconstructions have recognised (see Fig. 1). This
ANTscape reconstruction is specifically for the Eocene–
Oligocene boundary (34Ma). However, it is significantly
closer to the early Eocene than isostatically relaxed mod-
ern day bedrock (DeConto and Pollard, 2003; Pollard and
DeConto, 2005). Our choice of the maximum reconstruction
by Wilson et al. (2012) is also justified by the fact that the
crust in the early Eocene was younger than at 34Ma and
that the interpolation required to adapt our topography to a
given climate model inherently smooths high and complex
relief. The resolution and scholarship of this reconstruction is
also unprecedented, and given that no substantial continental
ice existed between the early Eocene and Eocene–Oligocene
transition (Cramer et al., 2011), uncertainty in the applica-
tion of this data set only arises from regional tectonics and
not emplacement of thick ice sheets. Future ANTscape re-
constructions will include the early Eocene and may form
a part of revisions to the global topography presented here
(http://www.antscape.org/).
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 such
area. Prior to India’s collision with Eurasia, between 55 and
45 Ma, geological evidence suggests Eurasia’s southern mar-
gin may have been up to 4km high (Molnar et al., 2010, and
references therein). However, recent thermochronologic and
cosmogenic nuclide data indicate relatively low relief per-
sisted prior to collision (Hetzel et al., 2011). We choose to
leave our data set as provided by Markwick (2007), with a
peak elevation of 1500m, which represents an intermediate
solution to these competing uplift histories. This is a region
where researchers with new data or interpretations may wish
to make changes.
The uplift history of North American Cordillera is also
subject to debate. Numerous palaeoaltimetry measurements
based on oxygen isotope geochemistry suggest that western
North America was relatively high, on the order of 3–4km,
since the early Cenozoic (e.g. Mix et al., 2011). However,
palaeobotanical evidence suggests elevations were closer to
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2080 N. Herold et al.: A suite of early Eocene climate model boundary conditions
2km (Wolfe et al., 1998) and it is known that atmospheric
dynamics upwind of mountain ranges can significantly bias
oxygen 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 estimates,
approximately 2500m (Fig. 1c).
Despite the uncertainties in our reconstructed topography,
there are several substantial improvements over the recon-
struction of Sewall et al. (2000). In addition to the changes
discussed above, our topography incorporates a more realis-
tic extent of the Mississippi Embayment, reducing its area
in accordance with marine carbonate, coal and peat distri-
butions (Sessa et al., 2012; Markwick, 2007) (Fig. 1). The
ANTscape Antarctic topography is also substantially more
accurate than that of Sewall et al. (2000), which had an er-
roneously small continental area. The width of the Drake
Passage is also reduced in our reconstruction to be more in
accordance with data which imply an extremely nascent –
i.e. oceanographically closed – gateway in the early Eocene
(Barker et al., 2007; Lawver et al., 2011; Livermore et al.,
2007). Palaeogeographical updates are also applied to Aus-
tralia (Langford et al., 2001) and Europe (Iakovleva et al.,
2001; Golonka, 2011; Torsvik et al., 2002). Our final Eocene
topography is shown in Fig. 1c.
2.3 Representation of sub grid cell topographic
variability
Numerous details at the sub grid cell scale have important
effects on resolvable processes in global atmospheric models
and thus require parameterisation. An important detail is the
variation of topography within each grid cell, which allows
models to parameterise atmospheric gravity waves based on
surface roughness. Global atmospheric circulation models
are sensitive to the parameterised wave drag and to their
waves. These waves are important for the atmosphere’s 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. For
example, the variation of topography in a 1×1model grid
cell is calculated from the standard deviation of all eleva-
tions within the 1×1domain using a 10×10data set (e.g.
ETOPO1; Amante and Eakin, 2009). However, for past time
periods knowledge of surface elevation at such a high resolu-
tion is impossible. To overcome this lack of information and
provide an estimate of the Eocene variability of sub grid cell
topography 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 and
Eakin, 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 1×1Eocene
topography. Firstly, the modern ETOPO1 topography is re-
gridded from its native 10×10resolution to 1×1(Fig. 2a),
then, within each 1×1grid cell the standard deviation of
elevations 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 the
smoothness of ice compared to continental crust. Secondly,
an array of 100m bins are created from 0 to 5500m – rep-
resenting the range of modern elevations – and the area-
weighted average of the standard deviations of the grid cells
that fall within each bin (calculated in the previous step) are
calculated, resulting in an array of 55 values (Fig. 2c). Lastly,
given the clear monotonic relation between height and stan-
dard deviation between sea level and approximately 3000m,
and between 3000 and 5500m, separate linear regressions
are calculated for these intervals (Fig. 2c) to assign estimates
of Eocene variability in sub grid cell topography to each
grid cell (Fig. 2d). Given that the maximum elevation in our
Eocene topography is less than 3000 m (Fig. 1c) only the first
linear regression is applicable here.
Figure 2c shows a peak in standard deviations of approx-
imately 800m at elevations between 2500 and 3500 m. This
corresponds to the “Andean-type” environments identified by
Ziegler et al. (1985) such as the boundaries of the Tibetan
Plateau and Andean Cordillera (Fig. 2b). This broad peak
remains regardless of the resolution we upscale ETOPO1
to, 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 uncertainty
in simulated surface temperatures which result from differ-
ences in the palaeo-elevation of a proxy record’s site and
the elevation resolved in a given climate model (e.g. Huber
and Caballero, 2011; Sewall et al., 2000; Sewall and Sloan,
2006).
3 Bathymetry
3.1 Background and base data set
The first bathymetric maps used for Eocene ocean mod-
elling constituted bowl-like basins in which the oceanic crust
was treated primarily as abyssal plain (Barron and Peterson,
1991). The choice of a relatively flat bathymetry, although
dictated to some extent by model resolution and available
geological data, was informed by the lack of large scale
oceanic responses to bathymetric details (Barron and Peter-
son, 1990). However, this result was misleading due to the
lack of treatment of crucial oceanic processes in models of
that generation (e.g. see Sect. 4). The most recent Eocene
bathymetric data sets included the locations of mid-ocean
ridges and shelf slope hypsometry (Bice et al., 1998; Huber
et al., 2003). However, given that the highest level of de-
tail in these data sets consist of only six depth classes and
3×1.5horizontal resolution, substantial gains are to be
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N. Herold et al.: A suite of early Eocene climate model boundary conditions 2081
Figure 2. Estimating the standard deviation of sub grid cell ele-
vations for the Eocene. (a) ETOPO1 topography downscaled from
its native 10×10resolution to 1×1.(b) Standard deviation of
10×10elevations inside each 1×1grid cell. (c) Standard devi-
ations from (b) area-weight averaged into 100m bins and plotted
against corresponding elevation. Standard error for each bin is plot-
ted. Dotted lines represent linear regressions between sea level and
3000, and 3000 and 5500 m. (d) Linear regressions from (c) applied
to 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 the
global 55Ma bathymetry of Müller et al. (2008b), which is
part of a suite of palaeobathymetric maps reconstructed from
140 Ma to the present. Like previous efforts the foundation of
this bathymetry is the application of an age–depth 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 constructing
our Eocene bathymetry the age–depth relationship derived by
Stein and Stein (1992) was applied to reconstructed 55Ma
seafloor ages:
if t < 20 Ma;d (t ) =2600 +365t1/2,
if t20 Ma;d(t ) =56512473exp(0.0278t),
where dis the basement depth in metres and tis time in
Myr. Several age–depth relationships have been previously
tested to determine the best match to modern bathymetry,
with Stein and Stein (1992) showing the least bias (Müller
et al., 2008b). To accommodate regions where Eocene crust
is not available at present (due to the subsequent subduction
of oceanic crust) symmetric mid-ocean ridge spreading was
assumed and seafloor spreading isochrons from the conju-
gate plate applied. In regions where no data were available
from the conjugate plate, interpolation was applied between
available isochrons and the adjacent plate margin (Müller et
al., 2008a, b).
On tectonic timescales (Myr) the development of large
igneous provinces (LIPs) can have significant impacts on
global sea level (Müller 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 outlines
and estimating palaeo-LIP height following Schubert and
Sandwell (1989). Additionally, given that certain regions of
the modern ocean are covered by up to several kilometres
of sediment (Whittaker et al., 2013) reconstructed sediment
thicknesses also represent an important component of our
reconstructed palaeobathymetry. Based on an empirical re-
lationship with age and latitude (polar latitudes generally
having larger river runoff and tropical latitudes subject to
high marine productivity), an age–latitude relationship was
applied (Müller et al., 2008b, Supplement) to reconstruct
Eocene sediment thickness (Fig. 3c).
3.2 Bathymetric revisions
While the methodology adopted from Müller 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 140Myr. Therefore dis-
crepancies exist in some regions where palaeoceanographic
data have been recovered. Particularly, the depths of cer-
tain LIPs may be verified against known depth habitats of
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2082 N. Herold et al.: A suite of early Eocene climate model boundary conditions
Figure 3. 55 Ma (a) seafloor age, (b) basement depth, (c) sediment thickness, (d) final bathymetry and (e) the error margin in our bathymetry
based on age uncertainty (values represent the range of uncertainty above and below the bathymetry shown in (d). Black outlines indicate
palaeo-shoreline.
foraminifera recovered from deep-sea cores. Such a verifica-
tion was carried out here using Deep Sea Drilling Project and
Ocean Drilling Project records. Based on these records the
depth of the Madagascar Ridge (Schlich, 1974), Mascarene
Ridge (Backman et al., 1988; Fisher et al., 1974; Vincent et
al., 1974), Shatsky Rise, Ontong Java Plateau (Barrera et al.,
1993), Kerguelen Plateau (Mackensen and Berggren, 1992),
Walvis Ridge (Zachos et al., 2005; Fuetterer, 1984) and the
Rio Grande Rise (Perch-Nielsen et al., 1977) were adjusted.
Reconstructing the tectonic history of ocean gateways is
critical in explaining past ocean circulation (Scher and Mar-
tin, 2006; Hill et al., 2013), faunal migration patterns (Dalziel
et al., 2013a) and potentially global climate change (Barker
and Thomas, 2004). The Drake Passage and Tasman gateway
are of particular significance given that their opening was a
requirement for development of the Antarctic Circumpolar
Current, the largest ocean current in the world (130Sv)
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 and
estimates of its opening range from the middle Eocene to
late Miocene (Dalziel et al., 2013b; Scher and Martin, 2006).
As our bathymetry represents the early Eocene we prescribe
an oceanographically closed Drake Passage, constraining its
depth to less than 100m. Multiple palaeoceanographic and
tectonic records indicate that the Tasman gateway did not
open to deep flow until the late Eocene (Stickley et al., 2004),
although when a shallow opening appeared is debatable. Our
reconstruction of tectonic plate positions as well as the loca-
tion of Tasmania suggests that a shallow epicontinental sea
may have existed and thus we prescribe a depth of 30m or
less in the Tasman gateway. Finally, no data are available for
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N. Herold et al.: A suite of early Eocene climate model boundary conditions 2083
the bathymetry of inland seas or continental shelves in our
base data sets and thus we assume a maximum depth of 50 m
for inland seas and use a Poisson equation solver to interpo-
late intermediate values for both areas. Figure 3d shows our
final Eocene bathymetry. The uncertainty in this bathymetry
is shown in Fig. 3e as a function of age uncertainty, with
largest values in the southeast and northwest Pacific Ocean
(Fig. 3a).
3.3 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 between
the two data sets we re-rotate our Eocene topography us-
ing the plate rotation model of Müller et al. (2008b). This
was achieved by changing the reference plate (Africa) loca-
tion from that determined by Ziegler to that determined by
Müller et al. (2008b), resulting in a relative shift of the other
continents. Refinements to the location of some continental
blocks were made to improve the match between the loca-
tions of continental crust in both data sets. These steps were
largely achieved using the open source software packages
GPlates (http://www.gplates.org/), for digitizing polygons,
and Generic Mapping Tools (http://gmt.soest.hawaii.edu/)
for manual corrections. Deep integration of plate rotation
software with open access palaeontology databases has the
potential to streamline future palaeogeographic reconstruc-
tions (e.g. Wright et al., 2013). The final merged Eocene
topography and bathymetry is shown in Fig. 4 alongside
ETOPO1.
4 Tidal dissipation
The importance of tidal dissipation in the ocean’s general
circulation stems from the fact that diapycnal (i.e. verti-
cal) mixing is greatly affected by the tide’s interaction with
bathymetry. Large increases in diapycnal mixing are ob-
served above regions of rough topography (e.g. Polzin et al.,
1997) and are primarily a result of breaking tidally induced
internal waves (Garrett and Kunze, 2007; Jayne et al., 2004).
Tidal models have been used to predict the amount of tidal
energy dissipated in the oceans and to better constrain ver-
tical mixing profiles incorporated in ocean general circula-
tion models (e.g. Simmons et al., 2004). Such experiments
have 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 (e.g. Green and Huber, 2013;
Egbert et al., 2004).
New atmosphere–ocean general circulation models are be-
ginning to incorporate tidal dissipation (e.g. the Community
Earth System Model; CESM; Gent et al., 2011). Green and
Figure 4. (a) ETOPO1 topography and bathymetry, (b) new Eocene
topography and bathymetry. Both at 1×1resolution.
Huber (2013) applied a tidal model using the bathymetry de-
scribed in Sect. 3 and showed that, while total Eocene tidal
dissipation was weaker than present, a larger amount of tidal
energy was dissipated in the deep ocean, especially in the
deep Pacific. The vertical diffusivities associated with these
results are significantly larger than present, supporting argu-
ments that enhanced vertical mixing in the Eocene oceans
helps to explain the low equator to pole temperature gradient
inferred from geological records (e.g. Lyle, 1997), but that
have hitherto been difficult to reproduce in models (Lunt et
al., 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 tidal
mixing schemes. While this work represents a coarse first
attempt at deriving Eocene tidal dissipation, to our knowl-
edge no similar effort has been made and thus this data set
provides a baseline for groups who do not have access to the
tools required for deriving this boundary condition. However,
given the infancy of this application to deep time palaeocli-
mate it is likely that such a data set will be improved upon
quickly.
www.geosci-model-dev.net/7/2077/2014/ Geosci. Model Dev., 7, 2077–2090, 2014
2084 N. Herold et al.: A suite of early Eocene climate model boundary conditions
Figure 5. (a) Modern and (b) Eocene simulated tidal dissipation
(Green and Huber, 2013).
5 Vegetation
Climate models have long shown substantial global and
regional climatic responses to vegetation change (Otto-
Bliesner and Upchurch, 1997; Dutton and Barron, 1997),
though newer models indicate a weaker sensitivity (Henrot
et 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 boundary
condition (e.g. Sloan and Rea, 1996; Dutton and Barron,
1997). Subsequently, Sewall et al. (2000) developed a new
Eocene vegetation distribution taking into account more re-
cent data and the effects of a low equator-to-pole temperature
gradient. Like their Eocene topography, the vegetation recon-
struction of Sewall et al. (2000) has remained highly utilized
by the Eocene climate modelling community (e.g. Huber et
al., 2003; Liu et al., 2009; Roberts et al., 2009; Huber and
Caballero, 2011; Shellito et al., 2003).
We choose to reconstruct early Eocene vegetation using
the offline dynamic vegetation model BIOME4 (Kaplan et
al., 2003). For input into BIOME4 we use temperature, pre-
cipitation and cloud cover from a CESM simulation forced
with the Eocene topography and bathymetry described in
Sects. 2 and 3, respectively, and an atmospheric CO2concen-
tration of 2240ppmv, a concentration which has been found
to approximately reproduce Eocene temperatures (Huber and
Caballero, 2011). This CESM simulation was integrated for
250 years and initialized with output from a previous CESM
simulation that was integrated for over 3000 years (this
latter simulation was forced with the boundary conditions
of Sewall et al. (2000) for topography and vegetation, and
Huber et al. (2003) for bathymetry, mixed-layer ocean simu-
lations of which are described by Goldner et al. (2013)). The
BIOME4 was forced with a CO2concentration of 1120 ppmv
since higher concentrations resulted in large scale reductions
in tropical forest. While this is not consistent with the CO2
forcing of the driving climatology we are here only inter-
ested in deriving a vegetation distribution that is feasibly
“Eocene” 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 biome
maps simplified from the 27 biomes simulated by BIOME4
to 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 are
consistent with geological indicators of climate (Crowley,
2012). One apparent bias is an abundance of relatively dry
vegetation in northern South America in BIOME4 (Morley,
2007). However, there remains a distinct lack of records for
validation from large regions of South Africa and Siberia. We
also note that “grass” did not exist at the biome level in the
Eocene (Strömberg, 2011), and thus the “Grassland and dry
shrubland” biome presented in Fig. 6 should be interpreted
as shrubland only. Our vegetation reconstruction reflects our
simulated Eocene climate and is therefore less zonal than
previous reconstructions (Sewall et al., 2000) and is consis-
tent with our Eocene topography.
The utilisation of a single climate simulation to drive
BIOME4 inherently results in a vegetation distribution that
encompasses the biases of our climate model. While utilisa-
tion of ensemble climate model data (Lunt et al., 2012) would
attenuate 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 Sewall
et 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 a
substantially lower resolution than done here. Thus, utilis-
ing such data sets would result in mountainous vegetation –
for example over the North American cordillera – not com-
pletely corresponding to the location of mountain ranges in
our topography. Such an issue may be improved over time as
more simulations are conducted with the topographic bound-
ary condition presented here.
Due to the significant differences between modern and
Eocene topography (Fig. 4), the anomaly method typically
Geosci. Model Dev., 7, 2077–2090, 2014 www.geosci-model-dev.net/7/2077/2014/
N. Herold et al.: A suite of early Eocene climate model boundary conditions 2085
Figure 6. (a) Pre-industrial and (b) Eocene vegetation simulated by BIOME4. The 27 biomes simulated by BIOME4 have been consolidated
into 10 mega biomes following Harrison and Prentice (2003).
used for specifying input into the BIOME4 (Kaplan et al.,
2003) 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 CESM
climate are small in comparison with the simulated change
in climate for the Eocene (Huber and Caballero, 2011) we do
not believe this to be a significant issue. Furthermore, while
asynchronous coupling between our climate and vegetation
models precludes the ability of the simulated vegetation to
affect climate – as compared to synchronous coupling efforts
(e.g. Shellito and Sloan, 2006a, b) – it benefits our results by
not erroneously amplifying biases in our climate model (e.g.
Wohlfahrt et al., 2008).
6 Aerosols
Aerosols in Eocene climate simulations have previously been
prescribed at pre-industrial levels or set to arbitrarily deter-
mined, globally uniform values. Aerosols constitute one of
the largest uncertainties in radiative forcing under future an-
thropogenic greenhouse warming (Stocker et al., 2013) and
may be important in resolving some long standing palaeo-
climate conundrums (Kump and Pollard, 2008). Insufficient
proxies from the pre-Quaternary prevent the reconstruction
of this boundary condition from geological records. How-
ever, the advent of aerosol prognostic capabilities in at-
mospheric models allows the palaeo-distribution of various
aerosol species to be simulated (Heavens et al., 2012). Here
we again employ the NCAR CESM in a configuration that
utilizes the newly implemented Bulk Aerosol Model, which
is a component of the Community Atmosphere Model 4
(Neale et al., 2010). In this configuration the model explicitly
simulates the monthly horizontal and vertical distribution of
dust, sea salt, sulfate, and organic and black carbon aerosols
consistent with our Eocene topography (Fig. 7). The Bulk
Aerosol Model makes simplistic assumptions regarding the
size distribution of aerosol species, compared to the more
complicated Modal Aerosol Models. A detailed description
of the steps involved in simulating the palaeo-distribution
of aerosols is provided by Heavens et al. (2012). Here we
branch the same CESM simulation described in Sect. 5 while
also enabling the Bulk Aerosol Model.
Various aerosol species require the prescription of emis-
sion sources in the Bulk Aerosol Model and this is done in
accordance with Heavens et al. (2012). One exception is that
we do not specify any volcanic sources of SO2or SO4, given
their small radiative effects and the uncertainty in the distri-
bution of Eocene volcanoes. Another largely unconstrained
yet climatically relevant emission source in the Bulk Aerosol
Model is that of dust. In the Bulk Aerosol Model dust is
emitted solely from the desert plant functional type which
in turn is determined from the prescribed vegetation data
set. It is generally understood that cooler climates promote
more dust-laden atmospheres – due to increases in desertifi-
cation, reduced soil moisture and stronger winds (Bar-Or et
al., 2008). However, the degree to which global Eocene dust
concentrations differed from typical glacial–interglacial vari-
ability is uncertain, though regional evidence exists for sub-
stantially weak dust fluxes in the early Cenozoic (Janecek
and Rea, 1983). Here we have assumed that global Eocene
dust loading was approximately three quarters that of the pre-
industrial era. The sources of dust in our data set (i.e. deserts)
were manually distributed based loosely on the distribution
of early Eocene evaporites (Crowley, 2012), which itself
follows the expected distribution of subtropical high pres-
sure regions. Our chosen concentrations provide an Eocene
dust loading intermediate to simulations which prescribe pre-
industrial values (e.g. Heinemann et al., 2009; Lunt et al.,
2010; Winguth et al., 2009) and those which eliminate the
radiative effects of aerosols altogether (Huber and Caballero,
2011). The significant improvement in the approach taken
here is that the distribution of aerosols is consistent with our
Eocene topography, providing a realistic regional representa-
tion of their radiative forcing.
www.geosci-model-dev.net/7/2077/2014/ Geosci. Model Dev., 7, 2077–2090, 2014
2086 N. Herold et al.: A suite of early Eocene climate model boundary conditions
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 aerosol
loading and distribution during past climates and that our
simulated concentrations are likely highly model dependant.
Furthermore, the aerosol data sets provided here are only ad-
equate for models that do not include the indirect effects of
aerosols. Models that include such effects may exhibit signif-
icant sensitivity to even slight changes in aerosol distribution
and loading and we are not confident that the use of the data
sets presented here, given the uncertainties involved, would
be 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 concentrations
while also accounting for their indirect effects. Such models
will see the emission sources of various aerosol species (e.g.
deserts, volcanoes, regions of high marine productivity) be-
come an additional palaeoclimate model boundary condition.
Figure 8. Eocene river runoff directions. Directions indicated by
colour.
7 River transport
River runoff in current generation climate models is impor-
tant primarily for the redistribution of fresh water to the
oceans and can have significant implications for deep wa-
ter formation (e.g. Bice et al., 1997). Here we use the gra-
dient of our Eocene topography to represent river runoff
direction (Fig. 8). This data set was created using scripts
made available by the National Center for Atmospheric Re-
search (Rosenbloom et al., 2011). Regions where vectors do
not reach the ocean (i.e. internal basins) were manually cor-
rected. Topographic gradient has been used to constrain river
directions in the overwhelming majority of palaeoclimate
simulations to date. However, it is a crude method which
we show here simply for completeness. Furthermore, the
data set provided (Fig. 7) is only illustrative as the regrid-
ding of our topography (Fig. 1) to a given climate model’s
resolution will require re-calculation of these river direc-
tions to account for changes in gradient. A more morpho-
logically constrained river direction data set (e.g. Markwick
and Valdes, 2004) should be integrated into future revisions
of our Eocene boundary conditions.
8 Discussion and future work
We describe an openly available and comprehensive set of
early Eocene climate model boundary conditions includ-
ing topography, bathymetry, tidal dissipation, vegetation,
aerosols and river transport. The resolution of most of these
data sets is unprecedented and alleviates the undesirable step
of upscaling lower resolution data sets to that of current gen-
eration climate models. This should lead to improvements in
model–data comparison in regions of strong relief and facili-
tate high resolution global and regional climate simulations.
An important distinction between our tidal, vegetation,
aerosol data sets and our topography and bathymetry data
sets is that the former are model derived and thus not directly
based on measured physical quantities. The use of modelling
Geosci. Model Dev., 7, 2077–2090, 2014 www.geosci-model-dev.net/7/2077/2014/
N. Herold et al.: A suite of early Eocene climate model boundary conditions 2087
frameworks for our tidal and aerosol boundary conditions is
necessitated by the absence of any quantitative Eocene data.
Our use of a model to derive Eocene vegetation was predi-
cated on the model’s ability to capture what is known about
Eocene vegetation from palaeobotanical records (model val-
idation). As this is the case (see Sect. 5) we can have
an at least (or perhaps at best) satisfactory level of confi-
dence that the model is not predicting unrealistic vegetation
in regions where data are scarce. This eliminates the need
for researchers to subjectively estimate vegetation for large
swathes of land, though of course is directly affected by the
climate biases of our driving climatology.
Despite the substantial improvements introduced in these
boundary conditions, uncertainties in the data remain. These
are most pertinent in the palaeo-elevation of the North Amer-
ican Cordillera and proto-Himalayas, the geometry of the
Drake Passage and Tasman Gateway, our modelled tidal dis-
sipation and aerosol distributions and lastly our rudimentary
representation of river runoff. These data- and model-based
uncertainties provide a natural focus for future research in
developing 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 for
reducing palaeotopographic uncertainty in revised versions
of these boundary conditions. On the other hand, advances
in modelling may substantially improve the reconstruction
of tidal dissipation and aerosol distributions, though quanti-
tative validation of either of these in the Eocene is next to
impossible.
Finally, as important as the input into any model repre-
senting a real-world system is, an at least equal importance
should be placed on the data against which such models
are validated. Fortunately, recent compilations of terrestrial
and marine data have already been conducted by Huber and
Caballero (2011) and Lunt et al. (2012), respectively. We
stress that the maintenance and public availability of such
data sets provides the necessary yardstick against which to
compare all models. Users are also able to rotate newly
collected data to their 55Ma position in the same refer-
ence frame used here via the open source software package
GPlates (http://www.gplates.org/), thus ensuring that consis-
tency in georeferencing is maintained. A community effort
to adopt consistent modelling methodologies and boundary
conditions can accelerate growth in our understanding of
Eocene 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 online
at doi:10.5194/gmd-7-2077-2014-supplement.
Acknowledgements. N. Herold, J. Buzan, A. Goldner and M. Hu-
ber are supported under 1049921-EAR: Collaborative Research:
Improved Cenozoic paleoelevation estimates for the Sierra Nevada,
California: Linking geodynamics with atmospheric dynamics.
M. Seton and R. D. Müller acknowledge support from Australian
Research Council (ARC) grants DP0987713 and FL0992245,
respectively. The tidal model simulations were funded by the
Natural Environmental Research Council (grant NE/F014821/1)
and the Climate Change Consortium for Wales (JAMG), and the
National Science Foundation (grant 0927946-ATM to M. Huber).
The NCAR Command Language (NCL) was used to create our
figures. NCL and Generic Mapping Tools were used for the
manipulation of data.
Edited by: D. Lunt
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... There were, however, significant differences with respect to tectonically active regions. For example, in the early Eocene, the Tibetan plateau was much lower than today, whereas the Rocky Mountains had almost reached their present-day height (Herold et al., 2014). At low latitudes, open Panama and Tethys Seaways provided tropical ocean connections. ...
... The main changes in boundary conditions from the pre-industrial (PI) period include the specification of Eocene bathymetry, paleogeography, and varied atmospheric CO 2 concentrations. Following Lunt et al. (2017), simulations employed bathymetry protocols in a hotspot reference frame (Herold et al., 2014), except for the NorESM simulation, which used a paleomagnetic reference bathymetry frame (van Hinsbergen et al., 2015). These two frames differ slightly, such as in the angle of rotation of the Antarctic continent and widths of the Drake Passage and Tasman Gateway ( Figure S1 in Supporting Information S1). ...
... This is likely due to a combination of freshwater forcing and the basin geometry being unfavorable. The early Eocene North Atlantic has a much reduced width compared with modern day and is restricted to mid-to-low latitudes (Herold et al., 2014). Moreover, north of approximately 40°N, the Atlantic receives a large freshwater flux input (Table 1), from both sides of the basins ( Figure S4a in Supporting Information S1). ...
Article
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Here, we compare the ocean overturning circulation of the early Eocene (47–56 Ma) in eight coupled climate model simulations from the Deep‐Time Model Intercomparison Project (DeepMIP) and investigate the causes of the observed inter‐model spread. The most common global meridional overturning circulation (MOC) feature of these simulations is the anticlockwise bottom cell, fed by sinking in the Southern Ocean. In the North Pacific, one model (GFDL) displays strong deepwater formation and one model (CESM) shows weak deepwater formation, while in the Atlantic two models show signs of weak intermediate water formation (MIROC and NorESM). The location of the Southern Ocean deepwater formation sites varies among models and relates to small differences in model geometry of the Southern Ocean gateways. Globally, convection occurs in the basins with smallest local freshwater gain from the atmosphere. The global MOC is insensitive to atmospheric CO2 concentrations from 1× (i.e., 280 ppm) to 3× (840 ppm) pre‐industrial levels. Only two models have simulations with higher CO2 (i.e., CESM and GFDL) and these show divergent responses, with a collapsed and active MOC, respectively, possibly due to differences in spin‐up conditions. Combining the multiple model results with available proxy data on abyssal ocean circulation highlights that strong Southern Hemisphere‐driven overturning is the most likely feature of the early Eocene. In the North Atlantic, unlike the present day, neither model results nor proxy data suggest deepwater formation in the open ocean during the early Eocene, while the evidence for deepwater formation in the North Pacific remains inconclusive.
... The new LSM produced a geographically smaller Africa relative to the PI, with much of the present-day landmass north of 20°N being ocean in the early Eocene due to the increased sea level (Figure 1a). Second, the paleogeography (including topography and bathymetry) was based on the digital reconstruction of the early Eocene from Herold et al. (2014), with the topography (and sub-grid scale topography) being applied as an absolute value rather than as an anomaly (Lunt et al., 2017). Over Africa, the most pronounced changes were over southern and eastern Africa, with generally larger areas of raised topography in the early Eocene, relative to the PI (Figure 1b). ...
... This can be seen more clearly in the Supporting Information, where the differences in topography are shown; there is clearly a large increase in elevation over western Africa where there is land in the early Eocene but ocean in the PI, but apart from this (where the landmasses coincide) the largest changes are over southern and eastern Africa ( Figure S1 in Supporting Information S1). Third, concerning the land surface, vegetation and river run-off routing was also based on the data set of Herold et al. (2014), using an appropriate lookup table to convert the vegetation megabiomes into whatever format was required by the model (Lunt et al., 2017). The early Eocene vegetation was created by running the dynamic vegetation model BIOME4 (Kaplan et al., 2003), with the resulting 27 biomes being consolidated into 10 megabiomes following the procedure of Harrison and Prentice (2003); please see Table 3 in Harrison and Prentice (2003) for a distinction between these megabiomes. ...
... BIOME4 itself was forced by Eocene topography, bathymetry and CO 2 coming out of an early Eocene simulation from the CESM climate Harrison and Prentice (2003) (where 1 = tropical, 2 = warm-temperate, 3 = temperate, 4 = boreal, 5 = savanna, 6 = grassland and 7 = desert). The PI topography/bathymetry is taken from ETOPO5, re-gridded to 1° × 1° resolution, whereas the other fields are from Herold et al. (2014). 10.1029/2022PA004419 5 of 29 model. ...
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The early Eocene (∼56-48 million years ago) is characterised by high CO2 estimates (1200-2500 ppmv) and elevated global temperatures (∼10 to 16°C higher than modern). However, the response of the hydrological cycle during the early Eocene is poorly constrained, especially in regions with sparse data coverage (e.g. Africa). Here we present a study of African hydroclimate during the early Eocene, as simulated by an ensemble of state-of-the-art climate models in the Deep-time Model Intercomparison Project (DeepMIP). A comparison between the DeepMIP pre-industrial simulations and modern observations suggests that model biases are model- and geographically dependent, however these biases are reduced in the model ensemble mean. A comparison between the Eocene simulations and the pre-industrial suggests that there is no obvious wetting or drying trend as the CO2 increases. The results suggest that changes to the land sea mask (relative to modern) in the models may be responsible for the simulated increases in precipitation to the north of Eocene Africa. There is an increase in precipitation over equatorial and West Africa and associated drying over northern Africa as CO2 rises. There are also important dynamical changes, with evidence that anticyclonic low-level circulation is replaced by increased south-westerly flow at high CO2 levels. Lastly, a model-data comparison using newly-compiled quantitative climate estimates from palaeobotanical proxy data suggests a marginally better fit with the reconstructions at lower levels of CO2.
... The new LSM produced a geographically smaller Africa relative to the PI, with much of the present-day landmass north of 20°N being ocean in the early Eocene due to the increased sea level (Figure 1a). Second, the paleogeography (including topography and bathymetry) was based on the digital reconstruction of the early Eocene from Herold et al. (2014), with the topography (and sub-grid scale topography) being applied as an absolute value rather than as an anomaly (Lunt et al., 2017). Over Africa, the most pronounced changes were over southern and eastern Africa, with generally larger areas of raised topography in the early Eocene, relative to the PI (Figure 1b). ...
... This can be seen more clearly in the Supporting Information, where the differences in topography are shown; there is clearly a large increase in elevation over western Africa where there is land in the early Eocene but ocean in the PI, but apart from this (where the landmasses coincide) the largest changes are over southern and eastern Africa ( Figure S1 in Supporting Information S1). Third, concerning the land surface, vegetation and river run-off routing was also based on the data set of Herold et al. (2014), using an appropriate lookup table to convert the vegetation megabiomes into whatever format was required by the model (Lunt et al., 2017). The early Eocene vegetation was created by running the dynamic vegetation model BIOME4 (Kaplan et al., 2003), with the resulting 27 biomes being consolidated into 10 megabiomes following the procedure of Harrison and Prentice (2003); please see Table 3 in Harrison and Prentice (2003) for a distinction between these megabiomes. ...
... BIOME4 itself was forced by Eocene topography, bathymetry and CO 2 coming out of an early Eocene simulation from the CESM climate Harrison and Prentice (2003) (where 1 = tropical, 2 = warm-temperate, 3 = temperate, 4 = boreal, 5 = savanna, 6 = grassland and 7 = desert). The PI topography/bathymetry is taken from ETOPO5, re-gridded to 1° × 1° resolution, whereas the other fields are from Herold et al. (2014). 10.1029/2022PA004419 5 of 29 model. ...
Preprint
The early Eocene (~56-48 million years ago) is characterised by high CO2 estimates (1200-2500 44 ppmv) and elevated global temperatures (~10 to 16°C higher than modern). However, the response 45 of the hydrological cycle during the early Eocene is poorly constrained, especially in regions with 46 sparse data coverage (e.g. Africa). Here we present a study of African hydroclimate during the early 47 Eocene, as simulated by an ensemble of state-of-the-art climate models in the Deep-time Model 48 Intercomparison Project (DeepMIP). A comparison between the DeepMIP pre-industrial simulations 49 and modern observations suggests that model biases are model- and geographically dependent, 50 however these biases are reduced in the model ensemble mean. A comparison between the Eocene 51 simulations and the pre-industrial suggests that there is no obvious wetting or drying trend as the CO2 52 increases. The results suggest that changes to the land sea mask (relative to modern) in the models 53 may be responsible for the simulated increases in precipitation to the north of Eocene Africa, whereas 54 it is likely that changes in vegetation in the models are responsible for the simulated region of drying 55 over equatorial Eocene Africa. There is an increase in precipitation over equatorial and West Africa 56 and associated drying over northern Africa as CO2 rises. There are also important dynamical changes, 57 with evidence that anticyclonic low-level circulation is replaced by increased south-westerly flow at 58 high CO2 levels. Lastly, a model-data comparison using newly-compiled quantitative climate 59 estimates from palaeobotanical proxy data suggests a marginally better fit with the reconstructions at 60 lower levels of CO2.
... We use simulations from the Deep-time Model Intercomparison Project (DeepMIP) (Lunt et al., , 2021. DeepMIP simulations exist from eight models, covering a range of atmospheric CO 2 concentrations from 1 to 9× the preindustrial value, with the paleogeography and vegetation from Herold et al. (2014), and preindustrial levels of non-CO 2 greenhouse gases and Earth orbital parameters. Here we employ the early Eocene climate simulations from the Community Earth System Model version 1.2 (CESM1.2) run with a resolution of 1.9° × 2.5° (longitude × latitude) and the GFDL Climate Model version 2.1 (GFDL_CM2.1) ...
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During the early to middle Eocene, a mid-to-high latitudinal position and enhanced hydrological cycle in Australia would have contributed to a wetter and “greener” Australian continent where today arid to semi-arid climates dominate. Here, we revisit 12 southern Australian plant megafossil sites from the early to middle Eocene to generate temperature, precipitation and seasonality paleoclimate estimates, net primary productivity (NPP) and vegetation type, based on paleobotanical proxies and compare to early Eocene global climate models. Temperature reconstructions are uniformly subtropical (mean annual, summer, and winter mean temperatures 19–21 °C, 25–27 °C and 14–16 °C, respectively), indicating that southern Australia was ∼5 °C warmer than today, despite a >20° poleward shift from its modern geographic location. Precipitation was less homogeneous than temperature, with mean annual precipitation of ∼60 cm over inland sites and >100 cm over coastal sites. Precipitation may have been seasonal with the driest month receiving 2–7× less than mean monthly precipitation. Proxy-model comparison is favorable with an 1680 ppm CO2 concentration. However, individual proxy reconstructions can disagree with models as well as with each other. In particular, seasonality reconstructions have systemic offsets. NPP estimates were higher than modern, implying a more homogenously “green” southern Australia in the early to middle Eocene, when this part of Australia was at 48–64 °S, and larger carbon fluxes to and from the Australian biosphere. The most similar modern vegetation type is modern-day eastern Australian subtropical forest, although distance from coast and latitude may have led to vegetation heterogeneity.
... Modern world biogeographic divisions follow Holt et al. (2013). Palaeobiogeographic divisions for the Eocene based on Meyen (1987) and Akhmet'ev (2004), modified and updated with data and interpretations from Akhmet'ev & Zaporozhets (2014), Herold et al. (2014), de Bruyn et al. (2014 and Baatsen et al. (2020). ...
Article
Gedanochila museisucini gen. et sp. nov. is described, based on inclusions in the Eocene Baltic amber. A morphological phylogenetic analysis supports the placement of Gedanochila gen. nov. into the tribe Achilini. Definition, content and subdivisions of the tribe as well as position of extinct taxa placed within are briefly discussed.
... The iCESM1.2 simulations were performed following protocols of the Deeptime Model Intercomparison Project (Lunt et al., 2017(Lunt et al., , 2021 with the Eocene paleogeography and vegetation (56.0-47.8 Ma; Herold et al., 2014) and atmospheric CO 2 levels of ×1, ×3, ×6, and ×9 the preindustrial value (284.7 ppmv). The different atmospheric CO 2 levels span the range of proxy-derived CO 2 estimates for the early Eocene (Anagnostou et al., 2020). ...
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... However, it corresponds with the Early Eocene Climate Optimum (EECO) , an episode of global warming characterized by the warmest sustained temperatures of the Cenozoic (e.g., Zachos et al., 2001Zachos et al., , 2008. Herold et al. (2014) presented a general biome model for the Eocene, based on several simulated vegetation distribution and topographic reconstructions, and recovered the presence of "paratropical" forests in North America (ca. 30 • N) and across Eurasia at the same latitude. ...
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