Simulations of Permian Climate and Comparisons
with Climate-Sensitive Sediments
Mark T. Gibbs, P. McAllister Rees,1 John E. Kutzbach,2 Alfred M. Ziegler,1
Pat J. Behling, and David B. Rowley1
Center for Climatic Research, University of Wisconsin—Madison, Madison, Wisconsin 53706, U.S.A.
ABSTRACT
We use a climate model to simulate two intervals of Permian climate: the Sakmarian (ca. 280 Ma), at the end of the
major Permo-Carboniferous glaciation, and the Wordian (ca. 265 Ma). We explore the climate sensitivity to various
levels of atmospheric CO2 concentration and to changes in geography and topography between the two periods. The
model simulates large seasonality and high aridity in the continental interiors of both hemispheres for both periods.
The northern summer monsoon weakens and the southern monsoon strengthens between the Sakmarian and the
Wordian, owing to changes in geography and topography. The northern middle and high latitudes cool in winter,
between the Sakmarian and Wordian, associated with northward shift of the continents. This high-latitude cooling
strengthens the winter westerlies and shifts the maximum storm-track precipitation south. In the Southern Hemisphere, the winter westerlies weaken from the Sakmarian to the Wordian. Starting the simulations with no permanent
ice fields (i.e., by assuming that the late Sakmarian postdates deglaciation) and imposing increased levels of atmospheric CO2 four times the present level, we find no tendency for reinitiation of major glaciation. Some permanent
snow fields do develop in high southern latitudes, but these are primarily at high elevation. However, the combination
of low CO2 levels (such as present-day levels) and a cold summer orbital configuration produces expanded areas of
permanent snow. The results are based on statistics derived from the final 5 yr of 20-yr simulations. Paleoenvironmental indicators such as coal, evaporite, phosphate, and eolian sand deposits agree qualitatively with the simulated
climate. The extreme cold simulated in high latitudes is inconsistent with estimates of high-latitude conditions.
Either the interpretation of observations is incorrect, the model is incorrect, or both; a possible model deficiency
that leads to cold conditions in high latitudes is the relatively weak ocean-heat transport simulated by the heat
diffusion parameterization of the upper ocean model.
Introduction
warming (Ziegler et al. 1997). Relatively minor upland glacial deposits persisted into the Artinskian
in South Africa (Visser 1997). Apart from some evidence of mountain glaciers reaching sea level in
Siberia during the Capitanian Stage (Chumakov
1994), generally ice-free conditions then persisted
through the Mesozoic and into the early Cenozoic.
This article will focus on these earliest stages of
ice-free conditions.
We use a climate model and observations to
study global conditions during the postglacial Sakmarian and the Wordian (285–280 Ma and 267–264
Ma, respectively; Jin et al. 1997). As boundary conditions for the model, we use a new set of paleogeographic maps for the Permian that include the
most detailed reconstructions of paleotopography
produced for any pre-Quaternary interval (Ziegler
The Permian Period (296–251 Ma; Jin et al. 1997)
contains the most recent transition from a major
glaciation to a generally ice-free state. This deglaciation marked the end of the Permo-Carboniferous
glaciation, which began ∼330 Ma (Veevers and Powell 1987). Apparently, the deglaciation was relatively rapid, being mainly confined to the Early Permian Sakmarian Stage. A thriving Glossopteris
forest cover replaced the ice sheets throughout
much of southern Gondwana, and the classic and
ubiquitous Gondwanan sequence, from tillites to
coal-swamp deposits, indicates a major climate
Manuscript received November 2, 2000; accepted June 14,
2001.
1
Department of the Geophysical Sciences, University of
Chicago, Chicago, Illinois 60637, U.S.A.
2
Author for correspondence; e-mail: jek@facstaff.wisc.edu.
[The Journal of Geology, 2002, volume 110, p. 33–55] 䉷 2002 by The University of Chicago. All rights reserved. 0022-1376/2002/11001-0002$01.00
33
34
M . T. G I B B S E T A L .
et al. 1997) (fig. 1A, 1B). Between the Sakmarian
and the Wordian, there were considerable northward shifts of the continents, changes in topography, and perhaps increases in CO2. Our goals are
to (1) evaluate how differences in paleogeography
and CO2 between the two stages are manifested in
the data and model results; (2) describe the mechanisms responsible for the climate changes be-
tween these two stages, as simulated by the model;
(3) investigate whether high CO2 could have been
responsible for keeping the late Sakmarian and the
Wordian ice free; and (4) evaluate, for the Wordian
only, the climate sensitivity to imposed changes in
orbital parameters.
The simulations are tested against new global
compilations of data derived from the geological
Figure 1. Base maps for the Sakmarian (A) and Wordian (B) (from Ziegler et al. 1997) used in this study (Mollweide
projection with 45⬚ longitude lines), along with land elevation and location of climate-sensitive sediments (from
Ziegler et al. 1998). Land elevations for the Sakmarian (C) and Wordian (D) as prescribed in the climate model. The
model captures only the coarse-resolution features of the estimated topography shown in A and B (see text).
Journal of Geology
S I M U L AT I O N S O F P E R M I A N C L I M AT E
record. These data include lithologic indicators of
Permian climate such as coals, evaporites, eolian
sands, carbonate buildups, tillites, glacial dropstones, and phosphorites. We also make extensive
use of fossil floral data, which provided the highest
resolution of paleoclimate information, to evaluate
the model results (see companion article in this
issue by Rees et al. 2002). Our studies allow comparisons of trends in the simulations with trends
discernible in the geologic record, as is the case
between the Sakmarian and Wordian. The data
sources we use here are correlated to the stage level,
based on the internationally proposed scheme of
Jin et al. (1997), which replaces the old twofold subdivision of the Permian with three divisions. With
this time scale, the classic Russian subdivision of
the Lower Permian is retained, with the Sakmarian
(285–280 Ma) representing the second of four
stages. The Wordian (267–264 Ma) is the second of
three Middle Permian stages and is based on an
American unit thought to be equivalent with the
Russian Kazanian Stage.
The structure of this article is as follows. We first
review previous climate modeling studies of the
Permian. We then provide a brief description of the
climate model and justifications for our choices of
boundary conditions. After describing the main features of the climate simulations, we evaluate the
model’s performance when tested with climatesensitive sediment patterns. In our companion article (Rees et al. 2002), we derive Permian climate
biomes from paleobotanical and lithological data,
make data/model biome comparisons, and discuss
the major data/model agreements and disagreements that we have identified.
Previous Modeling Studies
Various studies have ascribed the major Permian
deglaciation, at least in part, to an increase in the
level of atmospheric CO2 (e.g., Crowley and Baum
1992; Fawcett 1994; Barron and Fawcett 1995), and
indeed Berner’s (1994) geochemical cycling model
indicates that atmospheric CO2 rose from near
present-day levels at about 300 Ma to perhaps four
times present-day levels or higher by 250 Ma. The
CO2 rise began about 270 Ma, according to Berner’s
model (which has a time step of 10 m.yr.), and on
his timescale, this would be about the beginning
of the deglaciation.
The Wordian (pKazanian) Stage has become a
“target interval” for paleoclimate modeling studies
as it represents a time that was effectively ice free,
with a Pangean supercontinent paleogeography.
These studies include Crowley et al. (1989), Kutz-
35
bach and Ziegler (1993), Fawcett (1994), Fawcett et
al. (1994), and Barron and Fawcett (1995). Climate
features that are typical of many previous Pangean
simulations include high aridity in the continental
interior, particularly in the subtropics (Kutzbach
and Gallimore 1989; Kutzbach and Ziegler 1993;
Barron and Fawcett 1995; Fawcett and Barron
1998); strong monsoons along the Tethyan coasts
(Kutzbach and Gallimore 1989; Kutzbach and Ziegler 1993); precipitation focused around tropical
mountains (Kutzbach and Ziegler 1993; OttoBliesner 1993; Crowley et al. 1996); and extreme
continentality (lack of oceanic moderation) leading
to large seasonal variations, i.e., hot summers and
very cold winters (Crowley et al. 1986; Kutzbach
and Gallimore 1989; Crowley and Baum 1994).
Model Description and Boundary Conditions
The climate model used here is GENESIS (Global
Environmental and Ecological Simulation of Interactive Systems) version 2, which is described in
Thompson and Pollard (1997a). This model is a refinement of GENESIS version 1 (Thompson and
Pollard 1995). Version 1 has been used extensively
for paleoclimate studies, and version 2 is now beginning to be applied to paleoclimate problems
(e.g., Thompson and Pollard 1997b; DeConto et al.,
1999).
GENESIS consists of an atmospheric general circulation model (AGCM) coupled to a land-surface
model (known as LSX), a sea-ice model, and a simple mixed-layer ocean model. GENESIS predicts
spatial patterns of climate at the earth’s surface and
for 18 levels within the atmosphere. The equations
governing the physical processes within the atmosphere (conservation of mass, momentum, moisture; radiative and convective processes) are solved
every half hour and include both the diurnal and
seasonal cycles. The AGCM calculations employ a
set of spherical harmonics that are truncated at
wave number 31 (“T31 truncation”), equivalent to
a lat ∼3.75⬚ # long 3.75⬚ grid. The land-surface calculations are performed over a 2⬚ # 2⬚ grid. The
ocean is represented by a 50-m mixed-layer (“slab”)
model, which allows for seasonal heat storage and
acts as a moisture source. The same mixed-layer
depth was also used for lakes. Poleward ocean-heat
transport is modeled as a diffusion process that is
proportional to the local gradient of slab-ocean temperature. The diffusion coefficient is time invariant
but depends on the latitude and zonal land/sea fraction. Sea ice is predicted using a simplified thermodynamic energy budget calculation at each grid
cell; there is no sea-ice advection. The heat flux
36
M . T. G I B B S E T A L .
convergence under 100% sea-ice cover was set at
10 W/m2 for both hemispheres (rather than 2 W/
m2 for the present-day control representation of the
enclosed Arctic Ocean) to represent the relatively
open oceans of the Permian.
While the model calculates climate from basic
physical principles and laws, certain external
boundary conditions have to be specified (e.g., table
1). These specifications allow us to isolate the effects of (or sensitivity to) changes in important
climate-forcing factors, i.e., solar luminosity, paleogeography, atmospheric CO2, and orbital parameters. Below, we provide details on our choice
of these boundary conditions.
Solar Luminosity.
The sun’s luminosity is
thought to have been steadily increasing since formation, a consequence of conversion of hydrogen
to helium. We used the relationship of A. I. Boothroyd (pers. comm. to Caldeira and Kasting 1992) to
determine reductions of 2.4% and 2.1% relative to
the present-day control value (1365 W/m2 in GENESIS version 2) for the Sakmarian and Wordian,
respectively.
Land/Sea Distributions.
The paleogeographic
base maps, specifically the land/sea distribution
and land-surface elevations (fig. 1), were taken from
Ziegler et al. (1997). Continental positioning is a
crucial boundary condition for climate model studies, and uncertainty in paleogeographic reconstructions increases farther back in the Phanerozoic.
However, Permian paleogeography is reasonably
well known because the configuration is basically
Pangean, except for Tethyan microcontinents that
now constitute south Asia. The Permian paleomagnetic data are reasonably consistent with continental positions at the start of the Triassic (a more
detailed discussion is given in Ziegler et al. 1996).
The total error in the paleomagnetic data for the
position of Pangea is on the order of a few degrees
of latitude.
In contrast, the position in Tethys of the Southeast Asian microplates is more uncertain. One
Table 1.
problem with the Ziegler et al. (1997) maps is that
the Mongolian Arcs are shown in a latitudinal position that is probably too low, as indicated by the
floral data (Rees et al. 1999). Few paleomagnetic
data are available for this region, and the position
of Mongolia is therefore constrained mainly by the
timing of its collision with North China at the end
of the Permian. Current revisions of the timescale
are beginning to suggest that the Wordian stage terminated well before the end of the Permian, and
the new assignment of the Wordian to the Middle
Permian reflects this change (Jin et al. 1997). Rees
et al. (1999, 2002) discuss how this problem affects
data/model comparisons for this region. However,
because Mongolia was a relatively narrow landmass, the uncertainty in its position would have
little effect on the general model results. Ziegler et
al. (1997) depicted the coastlines in average positions, which accounts for why some marine/terrestrial deposits appear onshore/offshore (fig. 1).
The model’s land/sea distribution was derived
from the Sakmarian and Wordian coastline and lake
borders by determining which 2⬚ # 2⬚ cells were
greater than or equal to 50% land. Figure 2 shows
important differences in the land/sea distributions
between the Sakmarian and the Wordian; Pangea
moved northward by 10⬚–15⬚ of latitude during this
interval and became more symmetrically distributed about the equator by the Wordian. Other
changes include the drying up of the Amazon seaway and the movement of Angara (present-day Siberia) into high northern latitudes by the Wordian.
Topography. The Ziegler et al. (1997) maps (fig.
1A, 1B) are the first paleogeographic maps for the
Permian that give more than a cursory view of
paleotopography. Because mountain chains have
a profound effect on climate, this information is
important input to a climate modeling study (cf.
Moore et al. 1992; Kutzbach et al. 1993; OttoBliesner 1993) and is included in our simulations
(fig. 1C, 1D). To do this, the literature on geochro-
Boundary Conditions Used in Simulations
Boundary condition
Solar luminosity
Orbital configuration
Land/sea distribution and
topography
Vegetation type
Soil properties
Atmospheric CO2
How defined/varied
Sakmarian: 2.4% reduction, relative to modern; Wordian: 2.1% reduction, relative
to modern
Circular orbit with 23.5⬚ obliquity; for warm and cold summer orbit configuration,
see text
Ziegler et al. 1997; see figure 1
Uniform savanna (mixed trees and grassland)
Uniform (loamy) soil texture
Sakmarian: one, four, and eight times present level of CO2; Wordian: four and
eight times present level of CO2
Journal of Geology
S I M U L AT I O N S O F P E R M I A N C L I M AT E
37
Figure 2. Sakmarian and Wordian land/sea distributions: land area per lat 2⬚ belt (A) and spatial distribution, with
Sakmarian (right hatch) and Wordian (left hatch) land areas superimposed (B). Pangea moves northward by 10⬚–15⬚
of latitude during this interval and is more symmetrically distributed about the equator in the Wordian compared to
the Sakmarian.
nology, tectonics, sedimentary provenance, paleovolcanism, gravity, and paleogeology was assembled, and tectonic, epeirogenic, and volcanic zones
active during and prior to the Permian were identified. The locations of the mountain ranges are
estimated more accurately than their elevations
(e.g., 200 m for all lowlands; 1000 m for uplands;
and 2000 m for the collisional mountain belts,
which is probably a conservative estimate), particularly in the case of mountain ranges that had
formed previously and were being eroded by the
Permian.
To derive the topography field required by the
climate model at the 3.75⬚ # 3.75⬚ grid scale (fig.
1), a spline curve was first fitted to the Ziegler et
al. (1997) topographic contours using the generic
mapping tools (GMT) program (Wessel and Smith
1991). The spline function assigns a maximum
height above the highest contour, dependent on the
“tightness” of the function. In this case, we used
a tightness of 0.7, typical for topography. Because
there is no contour on the Ziegler et al. (1997) maps
between 200 and 1000 m, the GMT program tended
to create broad plateaus, especially flanking the Appalachians. The climate model algorithms then
smoothed the topography further in a manner consistent with the spatial resolution of the atmospheric dynamical calculations. The equatorial
mountains of both the Sakmarian and the Wordian
have maximum elevations of 1800 m; relatively
large regions with elevations of 800–1000 m are
placed in the east of Euramerica in the Sakmarian,
in Angara in the Wordian, in central Gondwana at
70⬚ S in the Sakmarian and at 60⬚ S in the Wordian,
and in extreme southern Gondwana at 85⬚ S in the
Wordian (fig. 1).
Thus, while the climate model thus incorporates
the major topographic features covering many grid
cells, it has insufficient resolution to depict narrow
mountain ranges and associated regional climate
effects accurately. For instance, the Urals, a mountain chain striking NW-SE in the Permian and spanning mid- to subtropical latitudes, would be expected to produce important rain-shadow effects
and prevent mixing of near-surface air masses.
However, this barrier is poorly resolved in the climate model (fig. 1).
Land Surface. Uniform vegetation, consisting of
mixed tree and grassland or savanna, as defined
by Dorman and Sellers (1989), was imposed at
every land-grid point. This prescribed uniformity
is clearly unrealistic; for instance, large areas of
central Pangea were probably desert. On the other
hand, prescribing the estimates of Pangean biomes
(Rees et al. 2002) would have limited the utility of
data/model comparisons as a means of assessing
the accuracy of the simulation because vegetation
can have a significant effect on climate (e.g., Bonan
et al. 1992; Foley et al. 1994; Dutton and Barron
1997; Otto-Bliesner and Upchurch 1997; DeConto
et al., 1999). An intermediate (loamy) soil texture
38
Table 2.
M . T. G I B B S E T A L .
Global Annual Averages of Temperature, Precipitation, and Precipitation Minus Evaporation (P ⫺ E)
Temperature (⬚C)
Precipitation (mm/d)
P⫺E (mm/d)
Experiment
Land
Ocean
Global
Land
Ocean
Global
Land
Ocean
Global
SAK-8#CO2
SAK-4#CO2
SAK-1#CO2
WORD-8#CO2
WORD-4#CO2
Modern control
16.7
12.9
6.6
16.5
12.9
8.3
23.1
20.7
16.0
23.1
20.8
18.2
21.6
18.9
13.8
21.4
18.8
15.1
1.7
1.6
1.5
1.5
1.4
2.0
4.0
3.8
3.4
4.0
3.8
3.1
3.5
3.3
3.0
3.4
3.2
3.6
.62
.58
.51
.47
.44
.56
⫺.26
⫺.25
⫺.23
⫺.24
⫺.23
⫺.26
∼0
∼0
∼0
∼0
∼0
∼0
(43% sand, 39% silt, and 18% clay) was also prescribed at every land-grid point.
Our choice of a uniform “average” land surface
in both the Sakmarian and the Wordian, although
introducing a bias, allows us to isolate changes due
to paleogeography and atmospheric CO2 alone (cf.
Fawcett and Barron 1998; Rees et al. 1999). Our
choice of intermediate vegetation and soil values
is the same as that of Fawcett and Barron (1998),
which allows a measure of compatibility with their
experiments using GENESIS version 1.02A. We are
planning climate model experiments for the Permian that will incorporate prescribed vegetation
based on the available data or interactive vegetation
schemes that will simulate the vegetation based on
the climate.
No ice sheets were prescribed for any of the simulations because our goal was to investigate the
factors responsible for continuation of ice-free conditions or for glacial reinitiation, which we will
infer from absence or presence of net annual snow
accumulation.
Atmospheric CO2 Level.
Our choice of atmospheric CO2 levels was guided by Berner’s (1994)
GEOCARB II geochemical cycle model predictions
and by proxy indicators of atmospheric CO2 levels
where these are available (see Berner 1997 for further details). GEOCARB II suggests an increase
from approximately one to four times present-day
CO2 levels through the Permian. Berner (1994) conducted various sensitivity analyses for factors such
as the effect of vascular plants on weathering and
rates of global degassing, to yield a crude range of
error estimates (1.5 to six times present-day level
for the latest Permian). We therefore chose one,
four, and eight times present-day levels as “end
member” estimates for the Sakmarian (the GENESIS version 2 present-day control value for CO2 is
345 ppm). Our use of a range of atmospheric CO2
levels allows us to examine the sensitivity of the
model climate to changes in atmospheric CO2.
Orbital Parameters.
For our primary experiments, we prescribe the earth’s orbit about the sun
as circular (eccentricity p 0 ) and assign the earth’s
obliquity (axial tilt) to be 23.5⬚, the modern value.
The use of a circular orbit is not realistic, but it
ensures equal receipt of insolation for both hemispheres. Experiments with hot and cold summer
orbital parameters were conducted for the Wordian
to investigate the potential for ice-sheet reinitiation. Following Crowley and Baum (1995), we use
extreme values for the Pleistocene from Berger
(1978): the warm summer orbit (WSO), an eccentricity of 0.06 and an obliquity of 24.5⬚, with perihelion occurring at the Southern Hemisphere summer solstice, and the cold summer orbit (CSO), an
eccentricity of 0.06 and obliquity of 22.0⬚, with
perihelion occurring at the Southern Hemisphere
winter solstice. Given more computational resources, it would have been useful to conduct similar experiments for the Sakmarian, but here we
used the Wordian results as a rough approximation
of overall sensitivity.
Simulation Results
The Sakmarian and Wordian experiments are
referred to as SAK-1#CO2, SAK-4#CO2, SAK8#CO2, WORD-4#CO2, and WORD-8#CO2,
representing three levels of atmospheric carbon dioxide concentration: one, four, and eight times the
present-day concentration. The Wordian experiments with extreme orbital parameters are referred
to as WORD-4#CO2, CSO; WORD-4#CO2, WSO;
WORD-8#CO2, CSO; and WORD-8#CO2, WSO,
where the 4 and 8 refer to the carbon dioxide concentration and WSO and CSO refer to warm and
cold summer orbital conditions for the Southern
Hemisphere summer. The results summarized are
for the final 5 yr of 20-yr simulations. As more
computer resources become available, it will be important to undertake longer simulations so that climatic averages can be based on longer temporal
records.
Global Averages.
Global average surface temperature, precipitation, and precipitation minus
evaporation (P ⫺ E) are summarized for all experiments in table 2. The global average temperature
for the Sakmarian simulation with 1#CO2 (13.8⬚C)
Journal of Geology
S I M U L AT I O N S O F P E R M I A N C L I M AT E
39
Figure 3. Zonal-average surface temperature (⬚C) for December-January-February (DJF) and June-July-August (JJA)
and for land and ocean for various CO2 levels: Sakmarian, Wordian, and Sakmarian and Wordian, both with 4#CO2.
is somewhat lower than for the modern control
(15.1⬚C), presumably due to the lower value of solar
luminosity in the Sakmarian and to differences in
geography. As expected, the temperature increases
with the carbon dioxide concentration. The difference in global temperature between the SAK1#CO2 and SAK-4#CO2 simulations (5.1⬚C) is
greater than that between the SAK-4#CO2 and
SAK-8#CO2 simulations (2.7⬚C) because the net
change in radiative forcing (i.e., the greenhouse effect) is larger from one to four times than from four
to eight times CO2. This is because the temperature
response to increases in atmospheric CO2 concentration follows a general logarithmic relationship
as the “strong” 15-mm band saturates (Berner and
Barron 1984; Kiehl and Dickinson 1987). Precipitation increases with increasing CO2 levels asso-
ciated with the overall increase in the intensity of
the hydrologic cycle (both evaporation and precipitation) at higher temperatures. For the same CO2
level, global average temperature and precipitation
vary little with the change in paleogeography between the Sakmarian and the Wordian.
Zonal Averages.
Zonal plots of temperature
(December-January-February [DJF] and June-JulyAugust [JJA]) over land and ocean (fig. 3) indicate
that increased CO2 has its most pronounced thermal effect in polar regions; the increase in temperature from one to four times CO2 in the Sakmarian
is particularly apparent. However, even with
4#CO2, the high-latitude Southern Ocean remains
very cold, and year-round sea ice extends from the
South Pole to about 70⬚ S in the Sakmarian and to
about 75⬚ S in the Wordian. The Northern Hemi-
40
M . T. G I B B S E T A L .
sphere polar oceans remain free of sea ice with
4#CO2. Winter temperature over land decreases in
the Northern Hemisphere high latitudes from the
Sakmarian to the Wordian as the area of land in
high latitudes increases (fig. 3, right; 4#CO2).
Zonal plots of precipitation over land (fig. 4) show
differences due to changes in CO2 levels and to
change in paleogeography between the Sakmarian
and the Wordian. For both paleogeographies, precipitation tends to decrease near the equator and
to increase in high latitudes with increasing CO2.
This tendency is perhaps linked to increased poleward transport of moisture as CO2 levels and temperature increase, as noted in modern-day studies
of the response of climate to CO2 change (Manabe
and Stouffer 1980). Changes in precipitation due to
changes of geography and topography are also evident. In the Sakmarian, the Southern Hemisphere
summer monsoon (DJF) is somewhat weaker than
its Northern Hemisphere counterpart (JJA). In the
Wordian, the southern summer monsoon has
strengthened and the northern summer monsoon
has weakened, such that the southern monsoon is
now the stronger. One basic cause of these monsoonal changes is the amount of land in low latitudes. In the Sakmarian (fig. 2), there is more land
in the northern subtropics, whereas in the Wordian
there is more land in the southern subtropics.
There are also differences in topography between
the two intervals. In the northern subtropics, the
Hercynian orogeny in Europe was waning by the
Middle Permian (Ziegler et al. 1997), and the area
above 1000 m is accordingly diminished between
the Sakmarian and Wordian (fig. 1). This decrease
in elevation contributes to the weakening of the
Northern Hemisphere summer monsoon.
The changes of land distribution in middle and
high latitudes also cause changes in precipitation
patterns. In the Northern Hemisphere, the northsouth temperature gradient (DJF) strengthens in the
Wordian because of the poleward shift and cooling
of high-latitude land (fig. 3, right). This increase in
temperature gradient strengthens the Northern
Hemisphere westerlies in the Wordian and shifts
the maximum storm-track precipitation slightly
south in DJF (fig. 4, right). The latitude of the precipitation maximum shifts from about 55⬚ N in the
Sakmarian to about 45⬚ N in the Wordian, with a
significant reduction of precipitation to the north
of the maximum. In the Southern Hemisphere,
winter temperatures near the pole are slightly
colder in the Sakmarian relative to the Wordian (fig.
3, right), the westerlies occupy a broader latitudinal
band, and midlatitude storm-track precipitation
also occupies a broader band, extending both farther
north and farther south in the Sakmarian relative
to the Wordian (fig. 4, right); the maxima, however,
are at the same latitude in both simulations.
Spatial Patterns. Maps of average seasonal surface temperature for the Sakmarian and Wordian,
both with 4#CO2, are shown in figure 5. The large
continent promotes extreme continentality; temperatures are greater than 35⬚–40⬚C in the summer
in the subtropics and reach ⫺35⬚ to ⫺40⬚C in the
winter in southern Gondwana and 0⬚ to ⫺15⬚C in
winter in Angara. With the increase in land area in
Figure 4. Zonal-average precipitation (mm/d) over land for DJF and JJA and for various CO2 levels: Sakmarian,
Wordian, and Sakmarian and Wordian, both with 4#CO2.
Journal of Geology
Figure 5.
S I M U L AT I O N S O F P E R M I A N C L I M AT E
41
Average seasonal (DJF and JJA) surface temperatures (⬚C) for the Sakmarian and Wordian, both with 4#CO2
the southern Tropics in the Wordian, relative to the
Sakmarian, summer temperatures increase. With
the northward shift of land in the northern high
latitudes in the Wordian, summer and winter temperatures decrease. With CO2 levels at four times
present, summer temperatures are above freezing
in high southern latitudes, with maxima of up to
5⬚C (figs. 3, 5). However, these temperatures are
substantially below those inferred from the data;
see Rees et al. (2002).
Maps of seasonal precipitation and surface winds
for the Sakmarian and the Wordian, both with
4#CO2, are shown in figure 6. There is little change
in spatial patterns for 8#CO2 (not shown). A welldeveloped intertropical convergence zone (ITCZ) is
present over the oceans for both geographies with
the associated precipitation band located near to,
or slightly north of, the equator. The large land/
sea temperature contrasts (fig. 5) promote “megamonsoons” (Kutzbach and Gallimore 1989) on
eastward-facing low-latitude coasts (fig. 7). The
Southern Hemisphere summer monsoon (DJF) lowpressure area—for example, the area with sealevel pressure less than 1010 mb—is larger in the
Wordian than in the Sakmarian. This difference is
a result of the larger land area in the subtropics in
42
M . T. G I B B S E T A L .
Figure 6. Average seasonal (DJF and JJA) precipitation (mm/d), sea-level pressure (mb), and surface wind vectors
(see reference vector) for the Sakmarian and Wordian, both with 4#CO2.
the Wordian and the resulting greater summertime
heating (fig. 5). As a consequence, higher summer
monsoon precipitation (DJF) occurs on the eastern
subtropical coast in the Wordian compared to the
Sakmarian. In contrast, the monsoon winds moving
onshore in the northern summer (JJA) are slightly
weaker in the Wordian relative to the Sakmarian.
This difference, related to the reduced land area and
the lowered topography in the Wordian, results in
a decrease of summer monsoon precipitation along
the eastern subtropical coast in the Wordian relative to the Sakmarian (fig. 6). The near-equatorial
east-west mountain range also influences the climate simulation. In the Wordian, this range is centered on the equator in the west, having shifted
northward from its position in the Sakmarian, and
elevations are increased. As a consequence, nearequatorial precipitation is enhanced in the Wordian
Journal of Geology
S I M U L AT I O N S O F P E R M I A N C L I M AT E
43
Figure 7. Average late-summertime snow depth (cm, water equivalent) over land for five simulations with a range
of geographies, CO2 levels, and orbital configurations: Sakmarian, 1#CO2; Sakmarian, 4#CO2; Wordian, 4#CO2 and
cold summer orbit (CSO); Wordian, 4#CO2; Wordian, 4#CO2 and warm summer orbit (WSO). The late-summertime
snow depths are for August (Northern Hemisphere) and February (Southern Hemisphere) and indicate the area where
snow cover is maintained throughout the year rather than being confined to winter.
due to moisture advection from the west; see also
similar examples of near-equatorial precipitation
reported for other time intervals by Otto-Bliesner
(1993, 1998) and Hay and Wold (1998). However,
the maximum elevation of this range in our simulations is less than 2000 m; elevations are more
typically 800–1000 m. Equatorial precipitation enhancement is probably less than it would be if the
prescribed elevations were higher.
The low precipitation in most of the continental
interior, at both low and midlatitudes, is evident
for both geographies (fig. 6). This is a consequence
of the large distances required to advect moisture
from oceanic sources (Kutzbach and Gallimore
1989; Kutzbach and Ziegler 1993; Fawcett and Barron 1998). The northward shift of North China between the Sakmarian and the Wordian leads to a
sizable reduction in precipitation as the region
44
M . T. G I B B S E T A L .
moves from the domain of intertropical and subtropical convergence rainfall and toward the region
under the dominance of the oceanic subtropical
anticyclone.
The midlatitude precipitation associated with
the winter westerlies and the storm track also
changes, as described earlier in terms of the zonal
averages. In the Northern Hemisphere, the wintertime westerlies are stronger in the Wordian, and
winter storm-track precipitation extends farther
south relative to the Sakmarian. In general, the topography of Angara is higher in the Wordian than
in the Sakmarian in the belt 30⬚–45⬚ N, and this
feature also contributes to winter precipitation enhancement. In the Southern Hemisphere, the westerlies and storm-track precipitation occupy a
broader belt (extending farther north and south) in
the Sakmarian relative to the Wordian.
Snow Budgets. Because our Sakmarian simulation prescribes no southern ice sheet (i.e., the late
Sakmarian is assumed to postdate deglaciation), we
can address the question of whether ice-free conditions can be maintained or whether glaciers will
re-form. Our model is not linked to a dynamic icesheet model (Pollard and Thompson 1997), and,
therefore, we cannot simulate ice-sheet development and ice movement directly. However, if our
simulation, which is initiated without snow cover,
develops permanent snow cover (i.e., if winter
snowfall does not melt completely in summer),
then we infer the potential for ice-sheet reinitiation. Therefore, we examine snow depth statistics
for late summer in each hemisphere (February in
the Southern Hemisphere, August in the Northern
Hemisphere) to determine if snow cover is persisting through summer. With the CO2 level at four
times present, we find some net snow accumulation occurring at high elevations in the mountains
that form the southern rim of Gondwana (note that
snow is still present in February; fig. 7). With CO2
at modern levels, this region of permanent and
deepening snow cover is considerably larger, extending to almost 45⬚ latitude in some areas, i.e.,
close to the region of earlier Permian glacial tills
(Ziegler et al. 1998). From these results, we conclude that our Sakmarian experiment with 1#CO2
could well have supported regrowth of Southern
Hemisphere ice sheets but that elevated carbon dioxide levels (exemplified by 4#CO2 in our simulation) might have limited regrowth of ice to high
elevations in high southern latitudes. Moreover,
experiments with coupled climate–ice sheet models for the Carboniferous suggest that CO2 levels
greater than present (3#CO2) were required for deglaciation (Hyde et al. 1999). Using these two lines
of evidence for higher-than-present CO2 levels (i.e.,
the results from our experiments and those of Hyde
et al. 1999), it seems possible that the CO2 rise
modeled by Berner (1994) at 270 Ma may have begun somewhat earlier.
The correct specification of the height of the
southernmost Gondwanan mountains is also important for estimating ice regrowth potential. The
east-west range near 70⬚ S in the Sakmarian and
near 60⬚ S in the Wordian has elevations specified
to be in the range 800–1000 m, as does the range
along the southern rim of the continent in the Wordian. If the height of these ranges is overestimated
in the model, then snow accumulation is also overestimated. In the Northern Hemisphere, snow
fields disappear in late summer (August) with CO2
levels at four times present. With CO2 levels at one
time present, a small area of accumulation exists
at high elevations in Angara north of 50⬚ latitude.
In the Wordian, with 4#CO2, the depth of late
summer snow cover is reduced in southern summer, relative to the Sakmarian, owing to the northward displacement of the southern continent off
the South Pole. Only a small area of net snow accumulation remains, mainly above 500 m altitude,
in the highest southern latitudes (fig. 7). Imposing
a warm summer orbit, this area of net accumulation almost disappears (fig. 7). Conversely, with
cold summer orbit conditions, the area and depth
of late summer snow cover increases. We conclude
that with CO2 levels of four times present, Wordian
ice would have generally been confined to high elevations in high southern latitudes.
Interglacials must have occurred within the
Permo-Carboniferous glaciation, as evidenced by
the record of cyclothems in low latitudes (Veevers
and Powell 1987). Our conclusions are that with a
cold summer orbit, high-latitude glaciation may
have been possible for both the Sakmarian and Wordian paleogeographies, even with high levels of atmospheric CO2. However, to study this issue more
quantitatively, simulations using an interactive
ice-sheet model, or off-line ice-sheet model, would
be required.
Ocean-Heat Transport. Our simulations for the
Sakmarian and Wordian with the GENESIS model
produce considerably colder conditions in high latitudes than our previous simulations for the Kazanian (i.e., Wordian) (Kutzbach and Ziegler 1993),
which used the CCM1 model. Summer temperatures in the high southern latitudes are under 5⬚C
(though above freezing), and the core winter temperatures of Gondwana are below ⫺35⬚C. In contrast, the Kutzbach and Ziegler (1993) experiment
simulated temperatures of 25⬚–30⬚C in summer and
Journal of Geology
S I M U L AT I O N S O F P E R M I A N C L I M AT E
only ⫺20⬚C in winter for this area. Although Kutzbach and Ziegler (1993) assumed a higher value of
atmospheric CO2 (five times present), they also assumed a greater reduction in solar luminosity (1%);
therefore, differences in net radiative forcing cannot be the source of the differences in temperature
between these experiments.
We attribute this model-model difference in polar
temperature, in part, to the different values of poleward ocean-heat transport in the two models. Kutzbach and Ziegler (1993) prescribed values of oceanheat transport in the CCM1 model, based on estimates from a dynamic ocean model experiment
with idealized Pangean paleogeography (Kutzbach et al. 1990). In contrast, the GENESIS model
(Thompson and Pollard 1997a) predicts ocean-heat
transport values, based on a heat-diffusion parameterization that is linked to the model’s latitudinal
sea-surface-temperature gradient. As shown in figure 8, the prescribed transport in our previous experiment was almost double the model-simulated
transport in the GENESIS model, and, in turn, the
total heat exported to middle and high latitudes is
about halved in the GENESIS model relative to the
previous experiments with CCM1. Whereas sea ice
does not persist in the high-latitude oceans in the
Kutzbach and Ziegler (1993) experiment, it occurs
year-round in the southern polar ocean in the GENESIS model simulations, extending equatorward to
about 70⬚ S in the Sakmarian simulation and to
about 75⬚ S in the Wordian simulation (not shown).
This strong bias toward cold in the high-latitude
Southern Ocean also influences conditions on the
high-latitude southern land and helps explain, in
part, the net snow accumulation in high latitudes
described earlier. In contrast, snow survived on
land for a shorter part of the seasonal cycle, surface
albedo was lower, and land temperatures were
warmer in our previous simulations with CCM1.
This model-model difference underscores the need
to explore the role of ocean circulation patterns and
how they interact with the atmosphere by using
fully coupled ocean-atmosphere models.
Testing Model Results with ClimateSensitive Sediments
The distributional data available for testing model
predictions include climate-sensitive sediments
(fig. 1) as well as localities from which floral lists
have been obtained (see Rees et al. 2002). The sediment data set (Ziegler et al. 1998) is a comprehensive, global literature compilation of 1200 occurrences of coals, evaporites, eolian sands, carbonate
buildups, organic-rich shales, tillites, dropstones,
45
Figure 8. Zonal-averaged ocean-heat transport in petawatts (PW; 1015 W) in three Permian climate simulations:
the prescribed transport used in Kutzbach and Ziegler
(1993) and the transport calculated by the diffusive parameterization in the mixed-layer ocean model for the
Sakmarian and Wordian, with 4#CO2. The maximum
transport estimated from modern observations is about
2–3 PW.
and phosphorites. It covers all nine stages of the
Permian, and, in general, there is excellent global
data coverage, a consequence of the widespread distribution of Permian sedimentary rocks. The exceptions are certain areas of northwestern North
America and parts of central Pangea that lack a
Permian sedimentary record. Globally, there are
183 Sakmarian and 157 Wordian control points
(coals, evaporites, eolian sands, and phosphorites).
We compare here the environmental information
indicated by these sediments with the environmental conditions simulated by the climate model.
This approach has also been taken by Chandler et
al. (1992), Otto-Bliesner (1993), Fawcett (1994),
Fawcett et al. (1994), Pollard and Schulz (1994), Wilson et al. (1994), and Price et al. (1997) when evaluating model results for various time intervals.
Model Precipitation/Evaporation and Coal/Evaporite
Patterns. For both the Sakmarian and the Wor-
dian, the distribution of annual average P ⫺ E indicates wet conditions in high latitudes, arid continental interiors and west coasts, wet tropical
east-facing (monsoon-dominated) coasts, and wet
western equatorial coasts (fig. 9c, 9d). For both the
Sakmarian and the Wordian, there is a good spatial
match between these simulated annual average
P ⫺ E distributions and the observed distribution of
46
M . T. G I B B S E T A L .
Figure 9. Sakmarian (A) and Wordian (B) locations of phosphorites, eolian sands, evaporites, and coals. Estimates
of paleowind directions are indicated where available (see table 3). Sakmarian (C) and Wordian (D) simulations of
annual precipitation minus evaporation (P ⫺ E [mm/d]) and wintertime (black) and summertime (white) winds (see
reference vector for magnitude) for the experiments with 4#CO2.
coals, evaporites, and eolian sands (fig. 9a, 9b).
Coals align with positive P ⫺ E (in temperate latitudes in southern Gondwana and Angara and along
the tropical east-facing coasts), and evaporites and
eolian sands align with negative P ⫺ E (along the
west coasts and along subtropical interior basins
and seaways, such as the Amazon Basin and Russian Platform Sea). North China is simulated to be
wet, matching the record of continual coal deposition. However, the magnitude of positive P ⫺ E
diminishes somewhat between the Sakmarian and
the Wordian, which matches a decrease in the ex-
Journal of Geology
S I M U L AT I O N S O F P E R M I A N C L I M AT E
tent of coal deposition over this interval (Liu 1990).
With different levels of atmospheric CO2, we find
little change in the spatial variation of P ⫺ E, a conclusion also reached by Fawcett et al. (1997).
Possible explanations can be advanced for the few
discrepancies that do occur for these data/model
comparisons. Coals fall in an area of negative P ⫺
E along the equatorial west in the Sakmarian
(southwestern United States). These coals are thin
in character, representing a significant reduction
from the extensive coal deposition of the Carboniferous in this area. This area is close to the region
of high P ⫺ E associated with the intertropical convergence zone and the eastward-advected moisture
from the western ocean. Sakmarian evaporites from
southern Russia fall in an area of weakly positive
P ⫺ E but are very close to drier conditions to the
north. A Wordian evaporite in France plots in an
area of weakly positive P ⫺ E; a palinspastically restored reconstruction would place this deposit to
the south, in an area that does experience negative
P ⫺ E conditions.
Many basins experienced climate change as Pangea moved 10⬚–15⬚ northward during the Permian
(Ziegler et al. 1997). These important temporal
trends are captured by the model. For instance, the
western United States becomes more arid as it
moves north between the Sakmarian and the Wordian, matching the cessation of coal deposition and
the more extensive evaporite formation. The Urals
moved northward between the Sakmarian and the
Wordian, and this range increased in elevation
(cf. fig. 1) as the collision of the Russian Platform
and the Kazakhstania microcontinent continued
through the Permian (Ziegler et al. 1997). The modeled result for the Wordian was extensive orographic rainfall from the westerlies and high annual
P ⫺ E, and this fits well with the appearance of extensive coals in the Pechora Basin throughout the
Middle and Late Permian (Ziegler et al. 1998).
Successful comparisons have been made between
model-derived moisture distributions and with different coal and evaporite data sets for a wide range
of paleogeographies. These include the Carboniferous (Otto-Bliesner 1993; Crowley and Baum 1994;
Crowley et al. 1996), the Late Permian (Fawcett
1994; Fawcett et al. 1994), the Triassic (Pollard and
Schulz 1994; Wilson et al. 1994), the Early Jurassic
(Chandler et al. 1992), and the Late Jurassic and
mid-Cretaceous (Price et al. 1997). The most comprehensive such study has been made by Fawcett
et al. (1997), who compared GENESIS version 1.02A
annual P ⫺ E predictions from an extensive temporal sequence of experiments (Fawcett 1994;
Fawcett and Barron 1998) with the University of
47
Chicago Paleogeographic Atlas Project’s global
compilations of Mesozoic and Cenozoic coals and
evaporites.
Model Precipitation and Brackish Water Deposits.
Ziegler et al. (1998) outlined a method for reconstructing Permian surface-water masses (in terms
of salinity, temperature, and organic productivity)
based on climate-sensitive sediments from shallow
marine settings or adjacent terrestrial environments. Their method is particularly applicable to
restricted settings, such as broad epeiric seas, where
extreme salinity values could be expected. This approach is of value in understanding biogeographic
provinces and faunal evolution, as well as determining controls on oil source rock deposition. One
environment of formation for marine organic-rich
shales is in upwelling zones. Another environment
is in areas where a positive P ⫺ E balance leads to
an “estuarine circulation” pattern (Demaison and
Moore 1980; Hay 1995). In geographically or bathymetrically restricted settings, such as the Baltic Sea
today, nutrient-rich waters from surface runoff enhance surface productivity, while the low-density
brackish surface waters contribute to stratification
of the water column, thus limiting oxygenation of
the bottom waters while enhancing the preservation of organic richness.
Middle Permian oil source rocks occur in offshore basins in South China, which Ziegler et al.
(1998) relate to brackish water–induced stratification of the water column. High rates of rainfall (fig.
6) and P ⫺ E (fig. 9) associated with the ITCZ occur
directly over the area in which these deposits are
found (fig. 9), and this fits with the interpretation
of the Cathaysian floras as representing tropical
rain forests (Rees et al. 1999, 2002). Elsewhere, oil
source rocks were deposited in the North Caspian
Depression in the Early Permian (Medvedeva et al.
1994), probably as a result of the silled nature of
the basin. Ziegler et al. (1998) observed that an additional factor could have been the development of
a freshwater cap derived from runoff from the
southern end of the Urals mountain range. Even
though the model cannot fully resolve these uplands, annual average P ⫺ E is positive in this area,
in contrast to the rest of the Russian seaway region
to the north. A similar pattern is observed in the
Permian Basin of west Texas, where Early Permian
source rocks occur near the paleo-equator and grade
north into the evaporites of the subtropics. In the
higher latitudes, a few such deposits are found
around Angara in both the Sakmarian and Wordian.
In all cases, the annual average P ⫺ E is positive,
and it seems likely that here conditions also fa-
48
M . T. G I B B S E T A L .
vored delivery of a high rate of runoff to confined
shallow basins.
Model Wind Directions and Eolianite Transport Patterns. Most sand dunes today form in desert areas
with less than 30 mm/yr annual precipitation, and
this limits the development of vegetation and allows the transportation of the sand grains (Parrish
1998). GENESIS predicts negative annual average
P ⫺ E for most areas in which eolian sand deposits
are found from the Sakmarian and Wordian (fig. 9).
Eolian sand deposits can, in principle, be used to
evaluate model predictions of both wind speed (6
m/s or greater is needed for dune formation; Fryberger 1979) and direction from foreset dip directions. However, these interpretations are complicated by the fact that the model results are here
averaged by seasons, and, therefore, information
about extreme wind speeds and directions, conditions that might be important for dune formation,
were not available.
Regional compilations of Permian eolianites are
available in which hundreds of crossbedding dip
vectors have been averaged to reconstruct wind patterns (Glennie 1983b; Peterson 1988). However, experimental work and modern dune studies have
shown that the sand transport is not necessarily
parallel to the wind direction (Parrish 1998). Reliable directions may be obtained in the case of dunes
that are transverse to the wind direction but not
for oblique or longitudinal dunes, which are common in modern deserts, and the dune morphology
is not easy to deduce except in well-exposed outcrops. Thus, we have a middle Permian dune field
in northeast England that was initially assumed to
be dominated by northeasterly winds (Glennie
1983b) but was interpreted by Sneh (1988) to represent oblique dune action formed by northerly
winds, and subsequently, a closer study reinterpreted the dune morphology as longitudinal and
deposited under the influence of alternating northerly and southeasterly winds (Chrintz and Clemmensen 1993). In the latter case, the mean does
conform to Glennie’s direction and may be the
equivalent of a seasonal average transport. There
seems to be general agreement that the steepest
foresets yield the vector indicative of the original
wind, but since this information is not generally
available, we simply rely on the average directions
available in the literature (see table 3). Where the
original measurements are available for examination, it seems that the scatter generally spans up
to two quadrants, but the regional consistency and
general agreement with the model results gives us
confidence that the original wind directions are indicated by the foreset measurements.
In the following discussion, we first review the
Sakmarian and then the Wordian eolianites. We
must admit that uncertainty exists in the correlation of many eolianites, simply because they generally lack fossils. The basic data, with references,
are provided in table 3.
For the Sakmarian interval (fig. 9A, 9C), the western United States was the site of an Early Permian
sand sea (erg) extending 1600 km from Arizona to
North Dakota. A comparison of observed and
model wind directions for this region has been
made by Parrish and Peterson (1988), using a conceptual circulation model (Parrish 1982). Crossbedding “resultants” (Peterson 1988) indicate consistent northeasterly winds, which confirms both the
DJF and the JJA model wind vectors in this area
(fig. 9). This is a stable circulation pattern for the
western coast of Pangea for the Permian and early
Mesozoic, with anticyclonic circulation around an
oceanic subtropical high located over the northern
Panthalassan Ocean (Parrish and Peterson 1988).
Eolianites of probable Early Permian age are
known from the Maritimes Basin of eastern Canada
(Brisebois 1981). These deposits are younger than
the Sakmarian Stage seen on adjacent Prince Edward Island, but paleomagnetic data have been used
to assign them to the Early Permian (Tanczyk 1988;
Ziegler et al., in press); hence, they are relevant to
the discussion here. Northeasterly winds are indicated for this one site and conform to the winter
winds of the model. During the opposite season,
southerly winds are simulated, so this would imply
that sediment transport occurred mainly during the
winter.
In the Southern Hemisphere, Early Permian eolianites are developed in northwestern Argentina
(Limarino and Spalletti 1986). The sediment transport directions are interpreted to be bimodal and
indicate winds out of the southwest and north.
There is a reasonable match with the modeled Sakmarian winds of summer and winter, respectively,
although the indicated wind speeds are low in each
case. Also, this is the one area of Permian eolianites
for which the model indicates an excess of precipitation over evaporation. We assume that drier conditions would have been indicated if the paleoAndean Mountains had been portrayed as higher.
The Saudi Aramco Oil Company has found consistently east-dipping foresets in the dunes of the
Unayzah Formation, Saudi Arabia (C. Heine, pers.
comm., 2000). This formation is believed to be of
Early Permian age, most likely Sakmarian, based
on its context in the regional stratigraphy. Moderately strong westerlies in summer and winter oc-
Table 3.
Key to Paleowind Directions Entered in Figure 9
Country and
basin/region
U.S.A./Wyoming:
Powder River Basin
Laramie Uplift
U.S.A./Colorado:
White River Uplift
U.S.A./Utah:
Monument Uplift
U.S.A./Arizona:
Coconino Plateau
Canada/Quebec:
Maritimes Basin
Argentina:
San Rafael Basin (1)
San Rafael Basin (2)
Paganzo Basin
Rio Blanco Basin
Saudi Arabia:
Central Arabian Basin
East Arabian Basin
Netherlands:
South Permian Basin
North Sea:
South Permian Basin
Viking Graben
North Permian Basin
Scotland:
Moray Firth
Arran
NE England:
South Permian Basin
Central England:
Cheshire Basin
SW England:
Cornwall
Germany:
Nahe Basin
Beber Basin
Brazil:
Parana Basin
Latitude Longitude
Unit
Age
Wind No. of No. of
direction sites readings
Reference
44.5
41.8
⫺105.7
⫺106.0
Upper Minnelusa Fm.
Upper Casper Fm.
Sakmarian
Sakmarian
181
183
9
10
?
?
Peterson 1988, figs. 7, 20
Peterson 1988, figs. 7, 20
39.8
⫺107.6
Schoolhouse Mbr.
Sakmarian
184
4
?
Peterson 1988, figs. 7, 20
37.7
⫺110.0
Cedar Mesa Mbr.
Sakmarian
136
24
?
Peterson 1988, figs. 7, 20
36.5
⫺113.4
Esplanade Ss.
Sakmarian
180
15
?
Peterson 1988, figs. 7, 20
47.5
⫺61.8
Etang des Caps Mbr.
Sakmarian
230
9
747
Brisebois 1981, p. 37–39
⫺34.2
⫺34.2
⫺30.0
⫺28.8
⫺68.8
⫺68.8
⫺67.0
⫺67.8
Los Reyunos Fm.
Los Reyunos Fm.
La Colina Fm.
De la Cuesta Fm.
Sakmarian
Sakmarian
Sakmarian
Sakmarian
18
139
120
13
12
12
3
2
87
87
54
190
Limarino
Limarino
Limarino
Limarino
22.5
24.5
46.5
49.5
Unayzah Fm.
Unayzah Fm.
Sakmarian
Sakmarian
82
83
1
1
10
26
C. Heine, pers. comm., 2000
C. Heine, pers. comm., 2000
52.1
6.8
Upper Rotliegend
Wordian
280
1
24
Glennie 1983b, p. 527, fig. 1
53.1
59.2
56.5
2.2
1.7
2.0
Upper Rotliegend
Upper Rotliegend
Upper Rotliegend
Wordian
Wordian
Wordian
275
170
131
1
1
6
127
105
?
Glennie 1983b, p. 527, fig. 1
Glennie 1983b, p. 534, fig. 1
Glennie 1983a, fig. 1
57.7
55.6
⫺3.4
⫺5.2
Hopeman Ss.
Brodick Beds
Wordian
Wordian
206
232
6
10
100⫹
100⫹
Glennie and Buller 1983, fig. 9
Piper 1970, p. 305
54.8
⫺1.3
Yellow Sands
Wordian
238
4
100⫹
Chrintz and Clemmensen 1993, fig. 8
53.1
⫺2.8
“Saxonian”
Wordian
271
5
?
Jubitz et al. 1985, Saxonian Sheet
50.6
⫺3.5
“Saxonian”
Wordian
285
1
?
Jubitz et al. 1985, Saxonian Sheet
49.9
52.3
8.0
11.4
“Saxonian”
“Saxonian”
Wordian
Wordian
273
250
2
1
?
?
Jubitz et al. 1985, Saxonian Sheet
Jubitz et al. 1985, Saxonian Sheet
⫺29.9
⫺51.1
Upper Rio do Rasto Fm. Wordian
107
1
42
and
and
and
and
Spalletti
Spalletti
Spalletti
Spalletti
1986,
1986,
1986,
1986,
table
table
table
table
2
2
2
2
Nowatzki 1997
Note.
Locations, paleolatitude and longitude, unit, stage assignment, paleowind direction, other site information, and references are included. Fm. p Formation; Mbr. p Member;
Ss. p Sandstone.
50
M . T. G I B B S E T A L .
cur over this area in the Sakmarian experiments,
consistent with the empirical observations.
Representing the Wordian interval (fig. 9B, 9D),
eolianites are known across northern Europe from
England and Scotland, to the North Sea and Germany, and possibly Poland (Jubitz et al. 1985).
Many of these deposits are identified as Upper Rotliegend, and they directly underlie the Zechstein
marine flooding unit, now correlated with the Late
Permian (Jin et al. 1997). Hence, a Middle Permian,
possibly Wordian, age may be inferred for these
rocks, which have engendered the interest of explorationists because they serve as petroleum reservoirs in the North Sea and surrounding areas.
Glennie (1983b) inferred a “Mid North Sea High”
based on predominantly easterly and northeasterly
wind directions in the main Southern Permian Basin and southwesterly directions in the smaller
Northern Permian and Moray Firth Basins. However, we do not find any indication of such a relatively small-scale circulation pattern in the model
results. Model winds are strongest in winter (DJF),
blowing uniformly from the east and northeast
tradewind direction over all of this area. Winds are
weaker and more varied in summer (JJA). One possibility for the measured southwesterly directions
is that they were influenced by local fault-bounded
mountain ranges, and the effect of local topography
has been invoked in both the southern and northern North Sea areas (Glennie 1983a; George and
Berry 1993). Glennie (1983a) suggested that the Permian Basin floor may have been a giant depression,
up to a thousand meters below sea level, while our
climate model is based on a more conservative topography. Hence, future work might focus on different topographic configurations.
Finally, a single wind direction is available from
the Parana Basin of Brazil (Nowatzki 1997). Here,
winds from the northwest are indicated by data and
model results for winter and summer.
In summary, the simulated winds of the Permian
are generally confirmed by the field measurements
in the limited areas of the subtropics in which the
eolianites are found. The problem of possible local
topographic influence is not limited to Europe. All
of the areas mentioned were active tectonically in
the Permian, and the dip vectors of the crossbedding measurements are often found to parallel the
mountain ranges.
Model Wind Directions and Upwelling Deposits.
Phosphorite deposits form in coastal upwelling
zones, as has been known for many years (Sheldon
1964), and most upwelling zones are related to
the predictably strong and consistent trade winds
within the subtropics. Specifically, coast-parallel
winds induce Ekman-type transport if the offshore
sense is to the right of the wind in the Northern
Hemisphere and vice versa, a nonintuitive relationship (Parrish 1998). The distribution of phosphorite deposits throughout the Paleozoic has been
examined paleogeographically and compared with
qualitative retrodictions of upwelling to demonstrate a close relationship (Parrish et al. 1983). Subsequently, numerical climate models have been applied to the detection of upwelling zones and have
been both tested on the Recent and applied to the
Cretaceous Period (Barron 1985).
The Permian phosphorite deposits have been
plotted on paleoceanographic maps (Ziegler et al.
1998) and have been ordered into seven provinces,
several of which seem to be upwelling related
(Ziegler and Goldberg 2000). The simulated wind
directions (fig. 9) suggest strong and persistent upwelling along western Pangea. The classic Phosphoria Formation and adjacent units (Sheldon et al.
1967; Henderson et al. 1993) of the Western North
American Shelf Margin Province is the only really
economically viable phosphorite province of this
period. The Southern Hemisphere counterpart in
western South America has not yielded phosphorites, but this area has been affected by “tectonic
erosion”; it is thought that the record of the westfacing margin has been removed by the rasping effect of subduction during the Mesozoic and Cenozoic (Ziegler et al. 1981).
The model indicates coast-parallel westerlies
along the southern margin of Tethys, and this extends across the Himalayan Shelf Margin Province
and the Western Australia Marginal Basin Province, which contain scattered phosphorites and oil
source rocks (Ziegler and Goldberg 2000). This margin lay at between 50⬚ and 60⬚ throughout the Permian, well out of the subtropics, but the collective
association of the bioproductites and the persistent
wind predictions is suggestive of an upwelling relationship. Parrish et al. (1983) suggested upwelling
for this margin prior to the application of numerical
models.
A high-latitude setting for phosphorites is found
in the South Africa Karoo Basin Province at about
70⬚ S. These deposits are associated with the top of
the Early Permian Dwyka Tillite and overlying marine shales and chert layers, which contain dropstones. This, we suggest, may have been an area of
“ice margin upwelling” that “occurs in response to
the differential effect of the wind stress on the ice
and water” (Hay 1995, p. 42).
The other phosphorite-bearing provinces were
formed adjacent to either reefs or coal deposits;
hence, an upwelling origin seems improbable (Zieg-
Journal of Geology
S I M U L AT I O N S O F P E R M I A N C L I M AT E
ler and Goldberg 2000). This is because the presence of reefs indicates low surface productivity, and
the coals suggest persistent rainfall, which is suppressed in upwelling zones because of the cool water anomalies and their influence on the atmosphere. Therefore, these other deposits are not
relevant to testing the climate model, but the
Pacific Northwest and Himalayan–northwestern
Australian bioproductites offer a good fit with the
retrodicted wind directions. This simulation is superior to our earlier results (Kutzbach and Ziegler
1993) as far as the southern Tethyan deposits are
concerned because our earlier model indicated seasonally reversing winds along this coast.
Model Temperatures and Lacustrine Shales. The
presence of a stratified water column is observed
in many tropical lakes today and was likely so in
the past, whereas their temperate counterparts can
experience winter temperatures that lead to the
turnover of the water column and mixing throughout (Katz 1995). Therefore, tropical lakes are characterized by anoxic bottom waters, laminated sediments that may have organic richness, and a
general lack of bottom-dwelling organisms. To produce mixing, air temperatures near freezing are required for a period of weeks to chill the surface
waters to 4⬚C, the point at which water is most
dense.
Large Permian lakes, whose sediments indicate
episodes of lake stratification, are known from midlatitudes of both hemispheres. These lakes, Middle
to Late Permian on the new timescale, coincide
with the Wordian time slice and were developed at
about 50⬚ latitude. The Gondwanan lakes were in
the interior of the continent in southern Africa, and
this gave rise to the proposition that the presence
of large water bodies must have ameliorated the
climate (Yemane et al. 1989; Yemane 1993). The
Northern Hemisphere lake occupied the 350-kmlong Junggar Basin of western China and is a major
oil producer (Carroll et al. 1992). The overall paleogeographic context of this basin is poorly understood, but it must have been along the eastern
margin of the Angaran Continent. The model, albeit only for a short simulation of 20 yr, indicates
very cold winter temperatures that would almost
certainly produce strong seasonal mixing, and
therefore, this model feature is unrealistic in relation to sedimentary evidence for stratified, or occasionally stratified, lakes.
Conclusions
We have performed climate model simulations for
two stages of the Permian with new detailed pa-
51
leogeographies. We find climatic features that are
typical of many previous Pangean climate simulations. These features, a consequence of the size
of the Pangean supercontinent, include extreme
seasonality and high aridity in continental interiors
and summer monsoons along the Tethyan margins.
We find important climate trends that resulted
from changes in geography and topography between
the two periods. The model predicts a distinct
weakening of Northern Hemisphere summer monsoon precipitation from the Sakmarian to the Wordian; this matches a diminishment in coal deposition in this area, as well as major floral changes
(Rees et al. 1999, 2002). In the model, this weakening is caused by the northward shif‘t of the northern continent, with a trend toward less land in the
northern subtropics and more land at higher latitudes and by the lowering of the topography along
the subtropical coastline. In higher northern latitudes, the colder winters of the Wordian, caused by
northward shift of land masses, cause strengthening of the westerlies and southward shift of the
storm-track precipitation maximum. In high southern latitudes, the winters are slightly colder in the
Sakmarian (the land is farther south), and the winter westerlies and storm-track precipitation occupy
a broader latitudinal band. The Southern Hemisphere summer monsoon is strengthened in the
Wordian, relative to the Sakmarian, due to an increase in southern land area in the subtropics.
Overall, the model simulations are in fair to good
agreement with the data available from climatesensitive sediments. Model simulations of annual
average P ⫺ E compare particularly well with the
distribution of coals and evaporites. Where upwelling is known from phosphorites and organicrich shales, the model predicts wind directions consistent with Ekman transport offshore. Model wind
directions are also consistent with transport vectors inferred from eolian sand dune deposits, albeit
limited in distribution and possibly temporal resolution. In all locations with marine organic-rich
shales that are believed not to be associated with
upwelling but rather with a freshwater cap and estuarine circulation, the model predicts high local
P ⫺ E and runoff rates.
Our results suggest that the major deglaciation
in the Sakmarian (Early Permian) could have been
maintained only if levels of CO2 were higher than
present—in our case, at least 4#CO2. However, our
model has not taken into account the possible role
of ocean dynamics in augmenting the flow of warm
currents near the poles.
The model simulates very cold winters in highlatitude Gondwana. This result is inconsistent
52
M . T. G I B B S E T A L .
with observations, particularly when the model
simulation is compared with fossil floral data in
our companion article (Rees et al. 2002). Possible
explanations for this disagreement between model
and data are incorrect interpretation of observations, model deficiencies, or both. The climate
model simulation may underestimate the total
ocean-heat transport, and, even more importantly,
the model makes no allowance for the dynamical/
advective transports that could bring much warmer
conditions to high latitudes in particular regions,
as emphasized by Ziegler (1998). For this reason,
we are now undertaking coupled atmosphere-ocean
simulations for idealized Permian geographies and
ocean bathymetries to test these ideas. Another
significant limitation of this study was the use of
prescribed uniform vegetation and soil. We plan future experiments using coupled climate-vegetation
models to predict climate/vegetation feedbacks
that are known to be important features of both
present and past climates. Climate models can also
amplify an initial high-latitude cold bias because
of snow cover/albedo feedbacks. Thus, the snow
cover that developed in these simulations may have
amplified the cold bias. Further experiments will
have to consider the combined effects of ocean, vegetation, snow, and sea-ice feedbacks.
ACKNOWLEDGMENTS
This research was supported by National Science
Foundation (NSF) grants ATM 96-32160, EAR 9632286, and ATM 00-00545. The climate model experiments were conducted at the National Center
for Atmospheric Research, which is supported by
the NSF. We thank Sara Rauscher for assistance
with graphics and Bob Gastaldo and Tom Crowley
for their helpful reviews.
REFERENCES CITED
Barron, E. J. 1985. Numerical climate modeling, a frontier
in petroleum source rock prediction: results based on
Cretaceous simulations. Am. Assoc. Pet. Geol. Bull.
69:448–459.
Barron, E. J., and Fawcett, P. J. 1995. The climate of Pangea: a review of climate model simulations of the Permian. In Scholle, P. A.; Peryt, T. M.; and UlmerScholle, D. S., eds. The Permian of northern Pangea.
Vol. 1. Paleogeography, paleoclimates, stratigraphy.
New York, Springer, p. 37–52.
Berger, A. L. 1978. Long-term variations of caloric insolation resulting from the earth’s orbital elements.
Quat. Res. 9:139–167.
Berner, R. A. 1994. GEOCARB II: a revised model of atmospheric CO2 over Phanerozoic time. Am. J. Sci. 294:
56–91.
———. 1997. The rise of plants and their effect on
weathering and atmospheric CO2. Science 276:
544–546.
Berner, R. A., and Barron, E. J. 1984. Comments on the
BLAG model: factors affecting atmospheric CO2 and
temperature over the past 100 million years. Am. J.
Sci. 284:1183–1192.
Bonan, G. B.; Pollard, D.; and Thompson, S. L. 1992. Effects of boreal forest vegetation on global climate. Nature 359:716–718.
Brisebois, D. 1981. Lithostratigraphie des strates PermoCarboniferes, de l’archipel des Iles de la Madeleine.
Ministere de l’Energie et des Ressources, DPV-796. 48
p.
Caldeira, K., and Kasting, J. F. 1992. The life span of the
biosphere revisited. Nature 360:721–723.
Carroll, A. R.; Brassell, S. C.; and Graham, S. A. 1992.
Upper Permian lacustrine oil shales, southern Junggar
Basin, northwest China. Am. Assoc. Pet. Geol. Bull.
76:1874–1902.
Chandler, M. A.; Rind, D.; and Ruedy, R. 1992. Pangean
climate during the Early Jurassic: GCM simulations
and the sedimentary record of paleoclimate. Geol. Soc.
Am. Bull. 104:543–559.
Chrintz, T., and Clemmensen, L. B. 1993. Draa reconstruction, the Permian Yellow Sands, northeast
England. Spec. Publ. Int. Assoc. Sediment. 16:
151–161.
Chumakov, N. M. 1994. Evidence of Late Permian glaciation in the Kolyma River Basin: a repercussion of
the Gondwanan glaciations in northeast Asia? Stratigr. Geol. Correl. 2:130–150.
Crowley, T. J., and Baum, S. K. 1992. Modeling late Paleozoic glaciation. Geology 20:507–510.
———. 1994. General circulation model study of Late
Carboniferous interglacial climates. Palaeoclimates 1:
3–21.
———. 1995. Reconciling Late Ordovician (440 Ma) glaciation with very high (14#) CO2 levels. J. Geophys.
Res. 100:1093–1101.
Crowley, T. J.; Hyde, W. T.; and Short, D. A. 1989. Seasonal cycle variations on the supercontinent of Pangea. Geology 17:457–460.
Crowley, T. J.; Short, D. A.; Mengel, J. G.; and North, G.
R. 1986. Role of seasonality in the evolution of climate
during the last 100 million years. Science 231:
579–584.
Crowley, T. J.; Yip, K.-J. J.; Baum, S. K.; and Moore, S. B.
1996. Modelling Carboniferous coal formation. Palaeoclimates 1:159–177.
Journal of Geology
S I M U L AT I O N S O F P E R M I A N C L I M AT E
DeConto, R. M.; Hay, W. W.; Thompson, S. L.; and Bergengren, J. 1999. Late Cretaceous climate and vegetation interactions: the cold continental interior paradox. In Barrera, E., and Johnson, C., eds. Evolution
of the Cretaceous oceans/climate systems. Geol. Soc.
Am. Spec. Publ. 332:391–406.
Demaison, G. J., and Moore, G. T. 1980. Anoxic environments and oil source bed genesis. Am. Assoc. Pet.
Geol. Bull. 64:1179–1209.
Dorman, J. L., and Sellers, P. J. 1989. A global climatology
of albedo, roughness length and stomatal resistance
for atmospheric general models as represented by the
simple biosphere model (SiB). J. Appl. Meteorol. 28:
833–855.
Dutton, J. F., and Barron, E. J. 1997. Miocene to present
vegetation changes: a possible piece of the Cenozoic
cooling puzzle. Geology 25:39–41.
Fawcett, P. J. 1994. Simulation of climate-sedimentary
evolution: a comparison of climate model results with
the geologic record for India and Australia. Ph.D. dissertation, Pennsylvania State University, University
Park.
Fawcett, P. J., and Barron, E. J. 1998. The role of geography and atmospheric CO2 in long term climate
change: results from model simulations for the Late
Permian to the present. In Crowley, T. J., and Burke,
K., eds. Tectonic boundary conditions for climate
reconstructions. Oxford, Oxford University Press,
p. 21–36.
Fawcett, P. J.; Barron, E. J.; Robison, V. D.; and Katz, B.
J. 1994. The climatic evolution of India and Australia
from the Late Permian to mid-Jurassic: a comparison
of climate model results with the geologic record. In
Klein, G. D., ed. Pangea: paleoclimate, tectonics, and
sedimentation during accretion, zenith, and breakup
of a supercontinent. Geol. Soc. Am. Spec. Pap. 288:
139–157.
Fawcett, P. J.; Gibbs, M. T.; Ziegler, A. M.; Hulver, M.
L.; and Barron, E. J. 1997. Global precipitation minus
evaporation (P ⫺ E) over the last 280 Myr: a comparison of climate model results with the geologic record.
Geol. Soc. Am. Abstr. Program 29:A-238.
Foley, J. A.; Kutzbach, J. E.; Coe, M. T.; and Levis, S.
1994. Feedbacks between climate and boreal forests
during the Holocene epoch. Nature 371:52–54.
Fryberger, S. G. 1979. Dune forms and wind regime. U.S.
Geol. Surv. Prof. Pap. 1052:141–169.
George, G. T., and Berry, J. K. 1993. A new lithostratigraphy and depositional model for the Upper Rotliegend of the UK sector of the southern North Sea. In
North, C. P., and Prosser, D. J., eds. Characterization
of fluvial and aeolian reservoirs. Geol. Soc. Spec. Publ.
73:291–319.
Glennie, K. W. 1983a. Early Permian (Rotligendes) paleowinds of the North Sea. Sediment. Geol. 34:
245–265.
———. 1983b. Lower Permian Rotliegend desert sedimentation in the North Sea area. In Brookfield, M. E.,
and Ahlbrandt, T. S., eds. Eolian sediments and pro-
53
cesses. (Developments in Sedimentology, vol. 38.)
Amsterdam, Elsevier, p. 521–541.
Glennie, K. W., and Buller, A. T. 1983. The Permian Weisliegend of NW Europe: the partial deformation of aeolian dune sands caused by the Zechstein transgression. Sediment. Geol. 35:43–81.
Hay, W., and Wold, C. N. 1998. The role of mountains
and plateaus in a Triassic climate model. In Crowley,
T. J., and Burke, K. C., eds. Tectonic boundary conditions for climate reconstructions. New York, Oxford
University Press, p. 116–143.
Hay, W. H. 1995. Paleoceanography of marine organicrich sediments. In Huc, A. Y., ed. Paleogeography, paleoclimate, and source rocks. Am. Assoc. Pet. Geol.
Stud. Geol. 40:21–59.
Henderson, C. M.; Bamber, E. W.; Richards, B. C.; Higgins, A. C.; and McGugan, A. 1993. Permian. In Stott,
D. F., and Aitken, J. D., eds. Geological survey of Canada. Geol. Can. 5:272–293.
Hyde, W. T.; Crowley, T. J.; Tarasov, L.; and Peltier,
W. R. 1999. The Pangean ice age: studies with a
coupled climate–ice sheet model. Clim. Dyn. 15:
619–629.
Jin, Y.-G.; Wardlaw, B. R.; Glenister, B. F.; and Kotlyar,
G. V. 1997. Permian chronostratigraphic subdivisions.
Episodes 20:10–15.
Jubitz, K. B.; Znosko, J.; and Franke, D. 1985. Lithologicpalaeogeographical map. International Geological
Correlation Program Project 86. Berlin, Zentrales Geologisches Institut, Saxonian Sheet.
Katz, B. J. 1995. Factors controlling the development
of lacustrine petroleum source rocks—an update. In
Huc A. E., ed. Paleogeography, paleoclimate and
source rocks. Am. Assoc. Pet. Geol. Stud. Geol. 40:
61–79.
Kiehl, J. T., and Dickinson, R. E. 1987. A study of the
radiative effects of enhanced atmospheric CO2 and
CH4 on early earth surface temperatures. J. Geophys.
Res. 92:2991–2998.
Kutzbach, J. E., and Gallimore, R. G. 1989. Pangaean climates: megamonsoons of the megacontinent. J. Geophys. Res. 94:3341–3357.
Kutzbach, J. E.; Guetter, P. J.; and Washington, W. M.
1990. Simulated circulation of an idealized ocean for
Pangaean time. Paleoceanography 5:299–317.
Kutzbach, J. E.; Prell, W. L.; and Ruddiman, W. F. 1993.
Sensitivity of Eurasian climate to surface uplift of the
Tibetan plateau. J. Geol. 101:177–190.
Kutzbach, J. E., and Ziegler, A. M. 1993. Simulation
of Late Permian climate and biomes with an atmosphere/ocean model: comparison with observations. Philos. Trans. R. Soc. Lond. B Biol. Sci. 341:
327–340.
Limarino, C. O., and Spalletti, L. A. 1986. Eolian Permian
deposits in west and northwest Argentina. Sediment.
Geol. 49:109–127.
Liu, G. 1990. Permo-Carboniferous paleogeography and
coal accumulation and their tectonic control in the
North and South China continental plates. Int. J. Coal
Geol. 16:73–117.
54
M . T. G I B B S E T A L .
Manabe, S., and Stouffer, R. J. 1980. Sensitivity of a
global climate model to an increase in CO2 concentration in the atmosphere. J. Geophys. Res. 85:
5529–5554.
Medvedeva, A. M.; Bulekbayev, Z. Y.; and Dal’yan, I. B.
1994. Direct indications of vertical migration of oil in
east of north Caspian depression. Pet. Geol. 28:
243–248.
Moore, G. T.; Sloan, L. C.; Hayashida, D. N.; and Umrigar, N. P. 1992. Paleoclimate of the Kimmeridge/
Tithonian (Late Jurassic) world. II. Sensitivity tests
comparing three different paleotopographic settings. Palaeogeogr. Palaeoclimatol. Palaeoecol. 95:
229–252.
Nowatzki, C. H. 1997. Revisão estratigráfica da Bacia do
Paraná, intervalo abrangido entre as aloformações Rio
do Rasto e Botucatu, Folha de São Leopoldo, RS, Brasil.
Master’s dissertation, Universidade do Vale do Rio dos
Sinos (UNISINOS), São Leopoldo, 246 p.
Otto-Bliesner, B. L. 1993. Tropical mountains and coal
formation: a climate model study of the Westphalian
(306 Ma). Geophys. Res. Lett. 20:1947–1950.
———. 1998. Effects of tropical mountain elevations
on the climate of the Late Carboniferous: climate
model simulations. In Crowley, T. J., and Burke, K.
C., eds. Tectonic boundary conditions for climate
reconstructions. New York, Oxford University
Press, p. 100–115.
Otto-Bliesner, B. L., and Upchurch, G. R., Jr. 1997. Vegetation-induced warming of high-latitude regions during the Late Cretaceous period. Science 385:804–807.
Parrish, J. T. 1982. Upwelling and petroleum source beds,
with reference to the Paleozoic. Am. Assoc. Pet. Geol.
Bull. 66:750–774.
———. 1998. Interpreting pre-Quaternary climate from
the geologic record. New York, Columbia University
Press, 338 p.
Parrish, J. T., and Peterson, F. 1988. Wind directions predicted from global circulation models and wind directions determined from eolian sandstones of the
western United States—a comparison. Sediment.
Geol. 56:261–282.
Parrish, J. T.; Ziegler, A. M.; and Humphreville, R. G.
1983. Upwelling in the Paleozoic Era. In Thiede, J.,
and Suess, E., eds. Coastal upwelling: its sediment record. Pt. B. Sedimentary records of ancient coastal upwelling. New York, Plenum, p. 553–578.
Peterson, F. 1988. Pennsylvanian to Jurassic eolian transportation systems in the western United States. Sediment. Geol. 56:207–260.
Piper, D. J. W. 1970. Eolian sediments in the basal New
Red Sandstone of Arran. Scott. J. Geol. 6:295–308.
Pollard, D., and Schulz, M. 1994. A model for the potential locations of Triassic evaporite basins driven by
paleoclimatic GCM simulations. Global Planet.
Change 9:233–249.
Pollard, D., and Thompson, S. L. 1997. Driving a highresolution dynamic ice-sheet model with GCM climate: ice-sheet initiation at 116,000 BP. Ann. Glaciol.
25:296–304.
Price, G. D.; Valdes, P. J.; and Sellwood, B. W. 1997. Quantitative palaeoclimate GCM validation: Late Jurassic
and mid-Cretaceous case studies. J. Geol. Soc. Lond.
154:769–772.
Rees, P. M.; Gibbs, M. T.; Ziegler, A. M.; Kutzbach, J. E.;
and Behling, P. J. 1999. Permian climates: evaluating
model predictions using global paleobotanical data.
Geology 27:891–894.
Rees, P. M.; Ziegler, A. M.; Gibbs, M. T.; Kutzbach, J. E.;
Behling, P. J.; and Rowley, D. B. 2002. Permian phytogeographic patterns and climate data/model comparisons. J. Geol. 110:1–31.
Sheldon, R. P. 1964. Paleolatitudinal and paleogeographic
distribution of phosphorite. U.S. Geol. Surv. Prof. Pap.
501-C:C106–C113.
Sheldon, R. P.; Maughan, E. K.; and Cressman, E. R.
1967. Sedimentation of rocks of Leonard (Permian)
age in Wyoming and adjacent states. In Hale, L. A.,
ed. Anatomy of the western phosphate field. Salt
Lake City, Intermontane Association of Geologists,
p. 1–13.
Sneh, A. 1988. Permian dune patterns in northwestern
Europe challenged. J. Sediment. Petrol. 58:44–51.
Tanczyk, E. I. 1988. Paleomagnetic investigations of the
Iles de la Madeleine, Gulf of St. Lawrence. Geol. Surv.
Can. Pap. 88-1B:79–89.
Thompson, S. L., and Pollard, D. 1995. A global climate model (GENESIS) with a land-surface transfer
scheme (LSX). I. Present-day climate. J. Clim. 8:
732–761.
———. 1997a. Greenland and Antarctic mass balances
for present and doubled atmospheric CO2 from the
GENESIS version 2 global climate model. J. Clim. 10:
871–900.
———. 1997b. Ice-sheet mass balance at the Last Glacial
Maximum from the GENESIS version 2 global climate
model. Ann. Glaciol. 25:250–258.
Veevers, J. J., and Powell, C. M. 1987. Late Paleozoic
glacial episodes in Gondwanaland reflected in transgressive-regressive depositional sequences in Euramerica. Geol. Soc. Am. Bull. 98:475–487.
Visser, J. N. J. 1997. A review of the Permo-Carboniferous
glaciation in Africa. In Martini, I. P., ed. Late glacial
and postglacial environmental changes: Pleistocene,
Carboniferous-Permian, and Proterozoic. Oxford, Oxford University Press, p. 169–191.
Wessel, P., and Smith, W. H. F. 1991. Free software helps
map and display data. EOS: Trans. Am. Geophys. Union 72:441.
Wilson, K. M.; Pollard, D.; Hay, W. W.; Thompson, S. L.;
and Wold, C. N. 1994. General circulation model simulations of Triassic climates: preliminary results. In
Klein, G. D., ed. Pangea: paleoclimate, tectonics, and
sedimentation during accretion, zenith, and breakup
of a supercontinent. Geol. Soc. Am. Spec. Pap. 288:
91–116.
Yemane, K. 1993. Contribution of Late Permian palaeogeography in maintaining a temperate climate in
Gondwana. Nature 361:51–54.
Yemane, K.; Siengenthaler, C.; and Kelts, K. 1989. La-
Journal of Geology
S I M U L AT I O N S O F P E R M I A N C L I M AT E
custrine environment during Lower Beaufort (Upper
Permian) Karoo deposition in northern Malawi. Palaeogeogr. Palaeoclimatol. Palaeoecol. 70:165–178.
Ziegler, A. M. 1998. Warm polar currents. EOS: Trans.
Am. Geophys. Union, Spring Meeting 98(suppl.):
S50.
Ziegler, A. M.; Barrett, S. F.; and Scotese, C. R. 1981.
Palaeoclimate, sedimentation and continental accretion. Philos. Trans. R. Soc. Lond. A301:235–264.
Ziegler, A. M.; Gibbs, M. T.; and Hulver, M. L. 1998. A
mini-atlas of oceanic water masses in the Permian
period. Proc. R. Soc. Vic. 110:323–343.
Ziegler, A. M., and Goldberg, K. 2000. Permian phosphorite provinces and their diverse paleogeographic
settings. Rio de Janeiro, Brazil, 31st International Geological Congress Abstracts.
55
Ziegler, A. M.; Hulver, M. L.; and Rowley, D. B. 1997.
Permian world topography and climate. In Martini, I.
P., ed. Late glacial and postglacial environmental
changes: Pleistocene, Carboniferous-Permian, and
Proterozoic. Oxford, Oxford University Press, p.
111–146.
Ziegler, A. M.; Rees, P. M.; and Naugolnyk, S. V. In press.
The Early Permian floras of Prince Edward Island,
Canada: differentiating global from local effects of climate change. Can. J. Earth Sci.
Ziegler, A. M.; Rees, P. M.; Rowley, D. B.; Bekker, A.; Li,
Q.; and Hulver, M. L. 1996. Mesozoic assembly of
Asia: constraints from fossil floras, tectonics and paleomagnetism. In Yin, A., and Harrison, T. M., eds.
The tectonic evolution of Asia. Cambridge, Cambridge University Press, p. 371–400.