Palaeogeography, Palaeoclimatology, Palaeoecology 309 (2011) 186–200
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Palaeogeography, Palaeoclimatology, Palaeoecology
j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / p a l a e o
The effect of global warming and global cooling on the distribution of the latest
Permian climate zones
Marco Roscher a, b,⁎, Frode Stordal c, Henrik Svensen b
a
b
c
Geological Institute, TU Bergakademie Freiberg, B.-v.-Cotta Str. 2, D-09599 Freiberg, Germany
Physics of Geological Processes (PGP), University of Oslo, PO Box 1048 Blindern, NO-0316 Oslo, Norway
Department of Geosciences, University of Oslo, PO Box 1047 Blindern, NO-0316 Oslo, Norway
a r t i c l e
i n f o
Article history:
Received 16 November 2010
Received in revised form 22 April 2011
Accepted 27 May 2011
Available online 1 June 2011
Keywords:
Permian Triassic boundary
Palaeoclimate
Global warming
Global cooling
Siberian Traps
a b s t r a c t
The end-Permian biotic crisis is commonly associated with rapid and severe climatic changes. These climatic
changes are commonly suggested to have originated from solid Earth carbon degassing (leading to global
warming), but aerosol- and ash-induced cooling induced by lava degassing has been suggested as well. The
application of an Earth System Model of Intermediate Complexity has enabled a visualisation of the major
climatic shifts on the supercontinent Pangaea caused by rapid temperature changes due to changed radiative
properties from greenhouse gases. The reconstructed reference climate was validated by latest Permian
climate indicative sediments to investigate the possible climatic shifts. From a set of 22 reconstructions which
varied with temperature a minimum global annual mean temperature of 18.2 °C for the late Permian climate
prior to the climatic perturbation event was determined. Starting from this pre-event setup, global warming
and global cooling scenarios were simulated. The response of the end Permian climate system to temperature
increase and decrease show marked differences. While global cooling is followed by major climatic changes in
the high latitudes and replacement of boreal biomes by tundra and polar frost, the changes during global
warming are less pronounced with only locally increasing aridity compensated by humidisation in other
regions. The different behaviour of the climatic belts under warm and cold conditions is accompanied by
different climate sensitivities caused by different strength of the snow cover–albedo feedback. Thus, changes
in the energy balance of the latest Permian surface–troposphere system have a 30% higher perturbation
potential during cold climate conditions than during warmhouse conditions. Therefore substantial global
cooling resulting in coldhouse climate conditions and an annual global mean temperature below 18 °C is more
efficient in perturbing the Earth palaeoclimate during the end-Permian warmhouse. The results suggest that
global cooling mechanisms as injection of sulphur aerosols and ash particles from the Siberian Traps Large
Igneous Province into the Late Permian palaeoatmosphere have a higher climate perturbation potential than a
warming due to carbon greenhouse gases with a similar magnitude of radiative forcing.
© 2011 Elsevier B.V. All rights reserved.
1. Introduction
The biggest mass extinction on Earth happened just before the
Permian–Triassic boundary (PTB). The strongest effects on the
biosphere are visible in the marine realm (Sepkoski, 1981) especially
in shallow waters (Kozur, 1980) likely due to anoxic and euxinic
conditions in the deep ocean (Kiehl and Shields, 2005; Kump et al.,
2005). The terrestrial system suffered as well, but the extinction was
not as severe as in the oceans (Erwin, 2006). The climate prior to the
Permian–Triassic boundary (PTB) was significantly warmer than
today and the supercontinent constellation was marked by a highly
continental climate (Roscher et al., 2008). This is expressed by the
huge intra-continental desert spanning from the northern to the
⁎ Corresponding author at: Geological Institute, TU Bergakademie Freiberg, B.-v.-Cotta
Str. 2, D-09599 Freiberg, Germany.
E-mail address: roscherm@geo.tu-freiberg.de (M. Roscher).
0031-0182/$ – see front matter © 2011 Elsevier B.V. All rights reserved.
doi:10.1016/j.palaeo.2011.05.042
southern subtropics accompanied by the disappearance of the tropical
everwet biomes next to the equator (Ziegler, 1990; Roscher and
Schneider, 2006). Knowledge of the continental climatic development
across the PTB is limited because the vast arid area hinders both life
and its preservation in the geologic record and thus detailed studies of
terrestrial sedimentary sections crossing the PTB are scarce. The
coincidence of the Siberian Trap Large Igneous Province formation
and the end-Permian mass extinction within a very short time frame
suggests that the extensive volcanism may have triggered changes
that significantly hampered the biosphere. One possible driving
mechanism might be the influence of solid Earth generated carbon
greenhouse gases, toxic gases or ozone destroying components
(Wignall, 2001; Svensen et al., 2009). Degassing induced by volcanic
activity also releases huge amounts of sulphur dioxide that has the
potential to initiate global cooling (Campbell et al., 1992). Thus the
Siberian Large Igneous Province could trigger climatic changes via
global warming, global cooling or a composite of both. Therefore, the
M. Roscher et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 309 (2011) 186–200
end-Permian event is often explained by severe climatic changes (e.g.
Stanley, 1988; Wignall, 2001; Courtillot and Renne, 2003; Twitchett,
2006).
It is well known that the whole Siberian Trap basalt was extruded
in less than 1 Ma at about 251.4 ± 0.3 Ma (Bowring et al., 1998) and
Rampino et al. (2000) showed that the faunal change in the endPermian happened within 60 ka or possibly less than 8 ka. Following
the hypothesis of Svensen et al. (2009), the release of various gases
from the East Siberian Tunguska Basin to the atmosphere is realised
by century scale degassing events. Therefore, the duration of potential
climatic effect could be very short. Because the stratigraphic
resolution in most sedimentary sections is commonly not better
than several thousand years, an investigation of the influence of
theoretic global temperature changes on the terrestrial climate to test
the response on irresolvable and geochemically invisible events was
undertaken.
The potential global warming of solid Earth carbon degassing is
influenced by various parameters. The major parameters are 1) the
greenhouse gas flux to the atmosphere, 2) the composition of the
released gas (CO2 and CH4), and 3) the Late Palaeozoic climate
sensitivity. Assuming a carbon gas release into the atmosphere of
1000 Gt carbon over 100 years, the global annual mean temperature
will rise approximately by 2–5 °C.
In addition to century scale warming following carbon gas release
from the Tunguska Basin, LIP lava flows released sulphur gases to the
atmosphere. In line with studies from other LIPs, sulphur aerosol and
volcanic ash injection into the latest Permian atmosphere could have
played a significant role in the end-Permian crisis (Campbell et al.,
1992; Courtillot and Renne, 2003; Self et al., 2005).
In order to evaluate the total degassing effects from volcanic basins
and subaerial lava flows, an Earth System Model of Intermediate
Complexity (EMIC) was used to test the response on global warming
and cooling scenarios. Moreover, we identify the regions in the endPermian world with the strongest response to the changed temperature, in order to use this as a predictive tool for future targeted proxy
data studies.
2. The numeric model
The IPCC AR4 (Solomon et al., 2007) proposes the utilisation of
Earth System Models of Intermediate Complexity (EMICs) for investigations of continental-scale climate changes and long-term,
large-scale effects. Palaeoclimate reconstructions, especially in the
Palaeozoic and Mesozoic are commonly focused on regional changes
and periods of large scale changes are the most targeted fields of
investigation. To reduce the complexity of the problem a restriction of
the model study to a few input parameters is necessary. Tests on the
effect of changes in the radiative properties in the latest Permian were
performed with the PlanetSimulator model (PLASIM) (Fraedrich et al.,
2005). This model is capable of reconstructing historic climates
(Grosfeld et al., 2007) and was used to determine the younger history
of the Andean uplift (Garreaud et al., 2010). Furthermore, it enables
investigations of climates very different from recent Earth conditions
as shown in applications for Mars (Stenzel et al., 2007) and the
Neoproterozoic snowball earth (Micheels and Montenari, 2008). The
model is composed of an atmospheric core with coupled sea-ice, slab
ocean and biome module. To initialize, it requires palaeogeographic
and palaeotopographic information as well as boundary conditions
such as the CO2 content of the atmosphere and the solar constant.
The usage of a slab ocean model without convective heat transport
and an upper layer of 50 m is considered sufficient for simple
sensitivity analysis focusing on the continents as it allows seasonal
heat storage and acts as moisture source (Gibbs et al., 2002).
Additionally, the lack of knowledge about the Permian bathymetry
(cf. Kiehl and Shields, 2005) as well as the crude assumptions on the
palaeosalinity (Hay et al., 2006) could bias the result of the climate
187
model. Thus, the usage of an ocean module without horizontal
convection does not necessarily imply a higher uncertainty compared
to modules that are implemented in a fully coupled atmosphere–
ocean model. In further support of modelling with a non-convective
ocean, palaeontological and sedimentological data from various endPermian marine environments support the hypothesis of a sluggish to
non-circulating ocean by the occurrence of anoxic deposits (e.g.
Isozaki, 1997; Kidder and Worsley, 2004). Furthermore, numerical
experiments indicate a weakened oceanic circulation due to a low
equator to pole temperature gradient during the considered time slice
(e.g. Kiehl and Shields, 2005).
3. Input data
Critical input data for palaeoclimate modelling approaches are the
uncertainties in the palaeogeography, palaeotopography and atmospheric composition. The investigations conducted here focus on the
effects of global temperature changes to the palaeo-environment and
thus the absolute positions of the continents and mountains are not as
crucial as for regional and local climate reconstructions. Digital maps
for the PLASIM were generated on the base of the palaeogeography of
Roscher et al. (2008), with small modifications in the positioning of the
Chinese blocks. This reconstruction is based on a Pangaea A
configuration, which is undisputed at the PTB (e.g. Ziegler et al.,
1997; Scotese, 2004). In contrast to other latest Permian reconstructions, a close relationship between the Chinese blocks and Eurasia is
preferred as indicated by palaeomagnetic reconstructions of Metelkin
et al. (2007). The palaeogeographic placement of North and South
China does not affect the gross features of the atmospheric circulations
(Parrish, 1993) and thus their positioning is not crucial for the
reconstruction of other regions. The topography for this latest Permian
map (Fig. 1) is adopted and simplified from the Tatarian reconstruction
of Ziegler et al. (1997). Topography dominates the localisation of
precipitation and an overestimation of the elevation may imply
unwarranted snow production in the model results. The elevations
used here are based on moderate elevation estimates as used by Gibbs
et al. (2002) and by Kiehl and Shields (2005), omitting questionable
elevations in excess of 5000 m for the Hercynian Mountains
(BecqGiraudon et al., 1996). The major topographic features and
their presumed maximum altitude (in brackets) are the remnants of
the Caledonides (1500 m), the Hercynian Mountains (2000 m), the
Urals (3000 m), the Altaids (1500 m), the Qinling–Dabie Mountains
(3000 m), the Gondwanides (including the ancestral Andes (3000 m),
the Cape and the New England foldbelt (2500 m)), the Windhook
highlands (1500 m), the Lambert rift shoulders (1500 m) and the
remnants of the Alice Springs orogen (1500 m). These topographies
are added to an average continent with a height of 500 m above sea
level, whereas coastal regions are flattened towards the shoreface. The
horizontal resolution of the reconstruction is 2.8° × 2.8° (T42)
representing 8192 approximately 300 km × 300 km large grid cells.
All model runs were started from the same initial file containing
palaeogeography, palaeotopography and prescribed surface temperatures. Finally, the boundary conditions for greenhouse gases, orbital
parameter and solar constant were prescribed. All model runs were
performed with a 2% reduced solar constant of 1340 W/m² (Caldeira
and Kasting, 1992) and the orbital parameters were fixed to recent
(2000 AD) conditions. To simulate greenhouse-generated global
warming a variety of different concentrations of the atmospheric
CO2 from 800 ppm to 10 000 ppm were applied in order to replicate a
great range of global annual mean temperatures (6.7 °C–30.5 °C).
4. Evaluation methods
All model runs were performed for 150 model years to achieve a
numeric equilibrium and the average of the last 10 years is used for
the evaluation here. Thus, the compared model results are
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als
Ur
an
n
nia
rcy tains
e
H un
Mo
Panthalassa
Altaids
bie
Sh
Da
Palaeotethys
Panthalassa
Go
Neotethys
nd
n
wa
Windhook
Highlands
ide
s
Alice Springs
Orogen
Lambert Rift
0
250
500
750
1000
1250
150 0
1750
2000
2250
2500
2750
3000
elevation [m]
Fig. 1. Mollweide projection of the palaeogeography adopted from (Roscher et al., 2008) and modified according to Metelkin et al. (2007) with palaeotopography from Ziegler et al.
(1997) as used for the numeric model. Major mountain ranges and oceans are labelled.
representative for different climatologically global annual mean
temperatures and not those representing extreme years. Since the
Late Palaeozoic climate sensitivity is unknown, the relationship
between a greenhouse gas concentration and a global annual mean
temperature is somewhat uncertain. Therefore, the different model
setups are discriminated by their global annual mean temperature
rather than atmospheric greenhouse gas content in order to remain
independent of the cause of temperature changes.
The end-Permian world was divided into 15 continental regions
and 3 oceanic realms (Fig. 2) to examine the regional climatic
development in respect to temperature and precipitation.
The boundaries of the regions are selected in order to group
climatic environments with small internal climatic variance. Additionally this subdivision is connected to recent continent boundaries to
keep adjacent outcrop areas within one group. For example, the
southern part of South America is separated from the southern African
region due to recent continent borders, although the Paraná and Karoo
basins were previously connected. The oceanic regions between the
tropic of Cancer and Capricorn are classified as tropical and the seas
north and south of the polar circles are separated as polar ocean from
the temperate oceanic environments.
Three different methods were applied to investigate the relationship between global temperature changes and the regional climatic
conditions. 1) A display of temperature and precipitation data (Fig. 3)
is made to describe the palaeo-environment. 2) A simplified Köppen
and Geiger climate classification (Köppen and Geiger, 1930–1943)
(Fig. 4) was applied to the generated numeric palaeoclimate-data, and
3) peat prediction maps using the method of Lottes and Ziegler (1994)
in combination with data from Whitmore (1975) and Morley (1981)
(Fig. 5).
polar ocean
Siberia
temperate ocean
N-North
America
tropical ocean
N-South
America
temperate ocean
N-China
Europe
S-North
America
temperate ocean
S-China
tropical ocean
N-Africa
S-South
America
Cimmeria
Arabia
S-Africa
India
temperate ocean
Australia
polar ocean
Antarctica
Fig. 2. Separation of the Late Permian world into 15 terrestrial and 3 oceanic realms to distinguish regional climate variations. Cf. Fig. 8.
M. Roscher et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 309 (2011) 186–200
189
B
A
-30
-20
-10
0
10
20
30
40
50
0
1000
2000
annual mean temperature [°C]
3000
4000
5000
6000
7000
8000
annual sum precipitation [mm]
Fig. 3. End-Permian reference climate with global annual mean temperature of 18.2 °C (A) annual mean temperature, and (B) annual sum precipitation, for detailed description see
Section 5.1.
main climates are distinguished by temperature properties except for
the arid and semi-arid climates. These dry climates are separated from
other regions by a ratio of the annual precipitation and the annual
mean temperature. All other main climates are defined by monthly
mean temperatures. Regions with the coldest month above 18 °C are
designated as tropics. If the coldest month is between −3 °C and
+18 °C it is assigned to the warm temperate region. Boreal climates
are characterised by a coldest monthly mean below − 3 °C but the
warmest still above 10 °C. In polar climates the warmest month is
colder than 10 °C.
The tropical climates are originally subdivided into fully humid,
monsoonal, winter dry and summer dry regions. For the comparison
with geological climate indicators, the subdivision due to this kind of
4.1. Simplified Köppen and Geiger climate classification
The major advantage of the used kind of the Köppen and Geiger
climate classification is its simplicity as it describes the most
necessary environments with 12 modes only and represents a
mixture of a descriptive and an effective classification. Therefore,
this classification scheme is preferred compared to interpretation of
regional climate conditions.
The Köppen and Geiger climate classification (Köppen and Geiger,
1930–1943) distinguishes five main climates. Several further subclasses describe additional precipitation and temperature characteristics so on the recent world 31 different zones are realised. As
mentioned above, a simplified version with 12 classes is utilised. The
DJF
0
200
400
JJA
600
800
1000
1200
>1400
seasonal precipitation [mm]
-50
-40
-30
-20
-10
0
10
20
30
40
50
seasonal mean temperature [°C]
Fig. 4. Seasonal sum precipitation (top) and seasonal mean temperature (bottom) for northern winter (DJF) and northern summer (JJA) with overlain wind direction vectors for the
reference climate reconstruction.
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M. Roscher et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 309 (2011) 186–200
18.2°C
ocean
tropics
desert
ever- seasonal hot
wet
cold
steppe
hot
temperate
cold
boreal
ever- seasonal ever- seasonal
wet
wet
coal
evaporite
aeolian sand
chert
tillite
reef
phosphorite
oil source rock
tundra
polar frost
www.geongrid.org
Fig. 5. Simplified Köppen and Geiger climate classification map for the reference climate reconstruction with an annual global mean temperature of 18.2 °C, overlain occurrences of
latest Permian (Changsingian) climate indicative sediments.
seasonality is not of interest, and the transcription of these climates
was restricted to ever-wet and seasonal tropics. The arid regions are
divided into desert and steppe by annual precipitation and temperature. A further subdivision into hot and cold environments is made
using a threshold of 18 °C mean annual temperature. In addition to
the equatorial climates, the warm temperate and boreal climates are
subdivided by the distribution of precipitation in the yearly cycle into
everwet and seasonal biomes. The polar regions are subdivided into
polar frost, characterised by the warmest month below zero and
tundra climate with the warmest month between 0 and 10 °C.
4.2. Peat probability maps
Peat occurrence-probability maps are created for quantifying the
effect of global temperature changes on the distribution of swamp
environments which are well traceable by coal deposits. These
calculations depend on temperature and precipitation as well as on
their annual fluctuations (Lottes and Ziegler, 1994). Regions favourable for accumulation of organic matter in a continental setting have
to be at least seasonally warm (N10 °C) and wet. Thus, the number of
months with an average temperature above 10 °C defines the length
of the growing season. During months with higher precipitation
(N40 mm) the formation of peat is favoured whereas in dryer months
the organic matter decays. Accordingly, the probability of peat
formation can be expressed as the percentage of rainy months
(N40 mm/month) with temperatures above 10 °C. Due to the higher
temperatures, and thus evaporation potential in the equatorial
regions, a higher threshold of 60 mm/month was chosen between
the tropics of Capricorn and Cancer (Whitmore, 1975; Morley, 1981).
The resulting maps indicate the regions that are, from a climatic point
of view, favourable for the formation and preservation of terrestrial
organic matter. Because conservation and coalification of these
organics depend on tectonic or sedimentary burial processes not
every location indicated on the maps actually contains coal deposits.
However, all major coal occurrences should fit with the predicted high
peat-probability regions.
5. Reference climate reconstruction
The boundary conditions for the investigations on the effect of
global warming in the latest Permian are given by the palaeogeography, palaeotopography, solar constant and atmospheric CO2
concentration. The latter is the only parameter which was modified
to simulate greenhouse gas generated global warming. A set of 22
model runs was generated for different global annual mean
temperatures in the range of 6.7 °C–30.5 °C. The lack of evidence for
polar climates (Chumakov and Zharkov, 2003) and the reports of
boreal forests in Antarctica (Taylor et al., 1992; Cuneo, 1996)
characterise the latest Permian as a warmhouse climate. To study a
range of plausible temperatures in the direction of global warming
and global cooling respectively, the coldest reconstruction matching
the distribution of climate indicative sediments was chosen as the
reference climate. These nearly tundra-free conditions are characterised by a global annual mean temperature of 18.2 °C and represent
the boundary between warmhouse and coldhouse climates.
5.1. Temperature and precipitation
The distribution of the annual mean temperature (Fig. 3A) in the
latest Permian climate is mainly controlled by latitude. Negative
annual mean temperatures (in °C) occur north and south of the polar
circles whereas the hot tropics span the whole continent between 30°
N and S respectively. The continent-wide isothermal belts are
modified by topography as in central Pangaea, the Urals and China
(cf. Fig. 1). Coastal regions are influenced by a milder maritime
climate buffering the temperature extremes. This effect is visible
especially at western coasts as in south-western Gondwana. In the
lower latitudes the annual average temperature does not exceed 30 °C
whereas in the higher latitudes on Antarctica the coastal temperatures
are about 20 °C higher than in the continental interior of southern
Gondwana.
Three tropical and two mid-latitude regions are characterised by
high annual precipitation rates in the latest Permian with 2000 mm or
M. Roscher et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 309 (2011) 186–200
more. The highest annual precipitation rate is reached in the western
Dabie Shan Mountains between North and South China with more
than 7000 mm per year. The precipitation in that region is bound to
the rising air masses in front of the Dabie Shan Mountains that were
formed by the continental collision of North and South China (Fig. 1).
The rainfall at the northern Tethyan coast in southern and central
Europe of about 1500–2000 mm per year is caused by convective
precipitation within the Inter Tropical Convergence Zone (ITCZ)
mainly during summer times (Fig. 4). The higher annual rainfall
(N3500 mm) in westernmost tropical Pangaea is caused by westerly
equatorial winds hitting the continent from the Panthalassan side. The
two mid-latitude precipitation regions are bound to the westerly
wind belt at about 50° north and south respectively and they are
characterised by annual precipitation slightly above 1000 mm. The
intensity within these belts decreases from the west-coasts towards
the continental interiors of Siberia, India and Australia. The reconstructed precipitation on the intra-Tethyan Cimmerian islands is not
markedly increased due to the absence of topographic features that
could initiate substantial orographic rainfall.
The spatial distribution of the precipitation throughout the year is
mainly controlled by the monsoonal circulation. In the western
tropical region in southern North America and northern South
America, the equatorial easterlies changed their direction to westerly
winds already in the Early Permian (Tabor and Montanez, 2002). Their
absolute position changes slightly during the year from 5°N to 5–8°S
(Fig. 4). Next to the equator it rains throughout the whole year but
further north and south the precipitation is strongly seasonal. In the
eastern topics of central Pangaea most of the rain falls in the northern
summer on the northern Tethyan coast. Although the precipitation in
the boreal regions has seasonal variations and intensifies during the
corresponding summer, the north-western parts of the boreal regions
on both hemispheres are marked by year-round rainfall that is
sufficient to produce everwet conditions.
The highest seasonal average temperatures with up to 45 °C are
reconstructed in the arid subtropical regions at about 20–25° N and S,
respectively. In central equatorial Pangaea the temperatures are
191
lowered by up to 20 °C in respect to the surroundings, by higher
elevation and higher precipitation (Figs. 3 and 4). Buffering effects of
the oceans along coast are well established for instance in the western
part of Gondwana. The four regions (cf. Fig. 2) with the warmest
monthly mean are northern Africa (40 °C), northern South America
(38 °C), northern North America (37 °C) and northern China (37 °C).
These temperatures exceed the modern day warmest month
temperatures from the Sahara desert by up to 5 °C (www.
weatherbase.com). The lowest values for annual (Fig. 3) and seasonal
temperatures (Fig. 6) are reconstructed in south-eastern Gondwana.
Whereas the annual mean temperature is not below − 25 °C the
coldest month temperatures are locally below − 40 °C. The coldest
monthly averages occurred on Antarctica (− 40 °C), India (−31 °C)
and Australia (− 26 °C). These temperatures are above the current
coldest monthly average (− 70 °C) from the Vostok 2 site in Antarctica
by more than 30 °C (www.weatherbase.com). All reconstructed
temperatures on the latest Permian Pangaea are above recent
analogues due to the higher global annual mean temperature with
the most significant differences in higher latitudes.
5.2. Köppen and Geiger climate classification
The climate in the Late Permian is dominated by an intracontinental desert that expands to a width of about 3000 km separating the
eastern and western tropics in the model. This huge arid to semiarid
region reaches from about 45°N to 45°S in extremes to 60°S in
southern Africa. The European region is dominated by seasonal
tropics. In western Pangaea small everwet tropical regions are
surrounded by seasonal tropics and hot steppe biomes. East Pangean
equatorial regions in China are assigned to tropical everwet and
seasonal biomes. The Cimmerian continents also reached a tropical
position during the Late Permian and are marked by a tropical
seasonal climate. The high latitude climates are characterised by
boreal environments. These boreal regions are separated from the
intra Pangean desert by cold steppe environments of various extents.
Temperate seasonal to everwet regions occur only in single spots in
peat probability
0%
10%
20%
30%
40%
50%
60%
coal
evaporite
aeolian sand
chert
tillite
reef
phosphorite
oil source rock
70%
80%
90%
100%
www.geongrid.org
Fig. 6. Peat probability map after the method of Lottes and Ziegler (1994) for the latest Permian reference climate, overlain occurrences of latest Permian (Changsingian) climate
indicative sediments.
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northern Siberia, north-eastern Scandinavia and southern Arabia.
Eastern Siberian and northern Australia are dominated by everwet
boreal environment, whereas Antarctica and southern Australia are
covered by seasonal boreal climates. Only the northernmost tip of
Siberia, the near-polar regions of Antarctica and a hundred kilometre
wide band at the south-eastern coast of Gondwana belong to the
tundra biome. Polar frost regions are not reconstructed for this global
annual mean temperature of 18.2 °C.
Comparisons with the climate indicative sediment data, obtained
from the PalaeoIntegration Project (www.geongrid.org), show that
the Late Permian coal deposits in south-eastern Africa, India and
Australia formed under boreal conditions. Some tropical, paralic coal
deposits are reported from China (Shao et al., 2003). The coal
occurrences in north-eastern Laurasia were laid down under boreal
and temperate everwet environments matching the reconstruction.
Oil source rocks are described from Madagascar, South China, and
northwest China where the two latter are related to marine upwelling
regions induced by wind-driven surface currents. The Late Permian
reef complexes are restricted to the Tethyan tropical environments in
China and Cimmeria. The spatial distribution of aeolian sand and
evaporite sediments fit well with the modelled arid regions.
useful to know the climate sensitivity of the utilised model. Because
this sensitivity depends not only on the atmospheric composition but
also on palaeogeography, palaeotopography, glaciers, vegetation
cover and other parameters, it was calculated for the PTB from the
performed model runs.
To calculate the climate sensitivity, defined as temperature
increase due to a doubling of the atmospheric CO2-concentration,
comparisons between the global annual mean temperature and the
radiative changes in the troposphere-surface system were made.
These changes in the net irradiance at the level of the tropopause are
defined as Radiative Forcing (RF in W/m²) going from a base CO2value to an elevated concentration. The RF of the different utilised CO2
concentrations was calculated with the equation of Myhre et al.
(1998). The relation between the global annual mean temperature
and the radiative forcing allows the calculation of the climate
sensitivity for PLASIM with the given boundary conditions (Fig. 7).
The calculated climate sensitivity can be described by three different
linear relations. The lowermost three data points represent a climate
sensitivity parameter (λ) of 8.6 °C/W/m². This results in a climate
sensitivity of 32 °C per doubling of CO2. The second branch between a
RF of 4.9 and 8 W/m² has a lower slope. The corresponding climate
sensitivity is 7.0 °C. The highest part of the graph in Fig. 7 represents a
climate sensitivity of 4.7 °C. It is concluded that the climate sensitivity
in a warmhouse is about 30% lower than in a coldhouse. All climate
sensitivities calculated for the late Permian setup are above the
recently used sensitivities of 1.5–4 °C global warming per doubling of
atmospheric CO2 (IPCC AR4, Solomon et al., 2007). To minimise the
effect of the different climate sensitivities on the investigations of the
impact of temperature changes on the distribution of climatic belts,
usage of the global annual mean temperature rather than the CO2concentration as discriminator between different cases (cf. Section 4)
has been preferred. Additionally this allows an easier comparison of
the results presented here with other investigations.
5.3. Peat probability
The calculated peat probability show similar patterns to the annual
precipitation with three low latitude regions with high peat forming
potential in western Pangaea, southern Europe and the western Dabie
Shan Mountains. The reported coal deposits of the Siberian boreal
environment fit very well with the reconstructed high probability
region. The Gondwana coals of the southern hemisphere match the
high probability region (N50%) of the southern boreal belt. The partial
mismatch of the Chinese coals and the presented peat prediction map
can be explained either by the paralic depositional environments
(Xingxue and Xiuyuan, 1996) or by overestimation of the Dabie Shan
topography leading to an extensive rain shadow.
6.2. Temperature and precipitation
The global annual mean temperature of the modelled climates
ranges from 6.7 °C to 30.5 °C. In respect to the 18.2 °C reference
climate this is a range of about ±12 °C (cf. Figs. 7, 8). Due to the
different climate sensitivities for global warming and global cooling
starting from the chosen reference the regional effects of warming
and cooling are considered separately (Fig. 8).
6. Changes during global warming/global cooling
6.1. Climate sensitivity
temperature change [°C] in respect to reference climate
(18.2°C global annual mean)
To compare the reference climate described here with other
datasets generated from different atmospheric compositions, it is
15
10
λ = 1.27
climate sensitivity
4.7°C per doubling CO2
5
0
λ = 1.88
climate sensitivity
6.96°C per doubling CO2
-5
λ = 8.63
- 10
climate sensitivity
32°C per doubling CO2
-15
4
6
8
10
12
14
16
18
radiative forcing [W/m²] (reference concentration 360 ppm CO2)
Fig. 7. Relation between radiative forcing and the global annual mean temperature within the PLASIM model with coupled slab ocean, sea-ice and biome module for a latest Permian
reconstruction. The slope of regression lines represents the climate sensitivity parameter λ. The adopted solar constant is 1340 W/m².
M. Roscher et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 309 (2011) 186–200
B
20
ANT
18
sAFR
regional warming [°C]
16
sSAM
14
AUS SIB
nNAM
nAFR
nSAM
nCHI
sNAM
IND
12
10
ARA
8
EUR CIM
sCHI
6
4
2
0
0
2
4
6
8
10
12
regional precipitation in percent of reference climate
A
320
nCHI
300
280
260
240
220
200
ANT
nAFR
EUR
sCHI
IND
nSAM
sNAM
CIM
AUS
sAFR
180
160
140
ARA
120
nNAM
100
SIB
sSAM
80
0
2
4
global warming [°C]
6
8
10
12
global warming [°C]
D
0
-5
CIM
sNAM
sCHI
EUR
nSAM
nAFR nCHI
nNAM ARA
-10
sSAM
SIB
-15
sAFR
AUS
IND
-20
ANT
-25
-12
-10
-8
-6
-4
-2
0
global cooling [°C]
regional precipitation in percent of reference climate
C
regional cooling [°C]
193
110
nNAM
100
sSAM
90
CIM
sCHI
nAFR
SIB
80
nCHI
nSAM
EUR
ARA
sNAM
70
60
50
AUS
sAFR
IND
ANT
-12
-10
-8
-6
-4
-2
0
global cooling [°C]
Fig. 8. Regional effects of a global temperature change on the continents; (A) regional warming during global warming, (B) regional precipitation changes during global warming, (C)
regional cooling during global cooling, (D) regional precipitation changes during global cooling. Colours only for better distinction of the labelled graphs, ANT = Antarctica, ARA =
Arabia, AUS = Australia, CIM = Cimmeria, EUR = Europe, IND = India, nAFR = northern Africa, nCHI = northern China, nNAM = northern North America, nSAM = northern South
America, sAFR = southern Africa, sCHI = southern China, SIB = Siberia, sNAM = southern North America, sSAM = southern South America.
The relation between global and regional warming is different for
every region but remains rather constant throughout the whole range
of temperature increase. Antarctica appears to have a 50% higher
warming than the global average whereas southern China warms 50%
less (Fig. 8). Variations in the regional temperature change during
global warming are related mainly to the latitudinal position.
Variations in the temperature change due to global warming between
regions with the same distance to the equator are caused by different
humidity of the regional climate. The dryer boreal regions of southern
Africa and southern South America experience higher regional
warming than the boreal everwet Australia do. The change in the
regional precipitation due to changes in the global annual mean
temperature vary from +330% to 80% of the reference climate
precipitation. The most affected region is in northern China with
increasing precipitation in the high precipitation area of the Dabie
Shan. The only two regions which experience significant aridisation
during global warming are Siberia and southern South America.
The regional temperature change during the reconstructed global
cooling is dominated by the palaeolatitudes as well. A marked change
in the regional cooling in respect to the global average is reconstructed for Australia and India for larger temperature reductions than
8 °C. This difference is caused by the spread of the polar frost regions
towards lower latitudes and a glaciation starts as they affect the
coastal mid latitudes. The reconstructed precipitation changes during
global cooling are very variable from region to region. Thus the
changes in the water cycle that are initiated by cooling are quite
complex, as known from climate model studies of the present climate
and climate change which occurs in this regime (Solomon et al.,
2007).
The temperature change over the oceanic regions shows the same
latitudinal relationship between regional and global temperature as
on the continents. The temperate oceanic regions are characterised by
a similar temperature change as the global average. Higher latitudes
warm up and cool down much more than the global average and the
low latitude tropical regions react only slightly to global temperature
changes. Similar patterns are observable in the precipitation changes
due to global warming or cooling respectively. The relation between
global temperature, regional temperature and precipitation over the
oceans is nearly linear because it is not perturbed by different
elevations and heat storage capacities (Fig. 9).
6.3. Köppen and Geiger climate classification
The simplified Köppen and Geiger (1930–1943) climate classification scheme was used to produce maps for each step of global
warming or cooling to review the regional changes in temperature
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B
polar
16
regional temperature change [°C]
12
temperate
8
tropical
4
0
-4
-8
-12
-16
-20
-24
-12
-10
-8
-6
-4
-2
0
2
4
6
8
10
12
regional precipitation in percent of reference climate
A
180
polar
160
140
temperate
120
tropical
100
80
60
40
-12
-10
-8
global temperature change [°C]
-6
-4
-2
0
2
4
6
8
10
12
global temperature change [°C]
Fig. 9. Regional effects of a global temperature change over the oceans; (A) regional temperature during global change, (B) regional precipitation changes during global temperature
change.
and precipitation in combination. The selection presented in Fig. 10
spans the entire range of reconstructed temperatures. The major
features of the latest Permian climate with an interrupted tropical
belt, a huge intracontinental desert covering nearly half of the
supercontinent and everwet boreals in northern Angara and Australia
remain the same in nearly all reconstructions.
The major climatic shift during global warming is reconstructed to
occur in Antarctica. Although the precipitation in this region nearly
doubled in respect to the reference run (cf. Fig. 8) the temperature
and thus the evaporation increases much faster in southern
Gondwana and an aridisation appeared with increasing global
temperature. Simultaneous with this drying, the area of the everwet
boreal belt in northern Australia expands as does the tropical everwet
region in western equatorial Pangaea.
The major climatic change during global cooling is reconstructed
for southern Gondwana. The spread of the polar frost regions starts
from the south pole and reaches 55° S in the reconstruction of a 6.7 °C
warm world.
The calculated area covered by each climate zone visualises the
shifts in the global distribution of climatic belts related to changes in
the annual mean temperature in the latest Permian (Fig. 11). In the
coldest case, the area polar frost and tundra covers about a quarter of
the landmasses. These climate zones vanish at temperatures slightly
above the reference case. Except for this, the increase in the global
annual mean temperature leads only to moderate changes in the
global land cover. Although the arid regions spread out in southern
South American and southern Africa, the total area covered by desert
and steppe biomes changes only by a few percent (Fig. 11).
A change in the global annual mean temperature is accompanied
by a 0.3% increase in area of dry biomes (desert and steppe) per
centigrade of warming, independent of the absolute global temperature. The global temperature has only minor influence on the
occurrences of deserts. Different response to a temperature increase
during warm and coldhouse conditions can be observed in every other
biome. A warming in a coldhouse climate is marked by an increasing
size of the boreal, temperate and tropical biomes (1.9%/°C) and a
retreat of polar and tundra biomes (− 2.2%/°C). After the transition
from coldhouse to warmhouse the area of these climate zones
remains rather constant, but temperature changes within hothouses
are responsible for changes in the quantity of everwet and seasonal
environments. Whereas the everwet regions spread out with 0.7%/°C
below and 0.3%/°C above the reference climate, the area of seasonal
biomes increase (1.2%/°C) during cooler conditions and decrease
(−0.4%/°C) in warm environments. The increase in temperature in
the latest Permian would be accompanied by a spread of everwet
biomes in respect to seasonal environments.
6.4. Peat probability
The global average peat formation probability increases nearly
linearly with temperature, with a change in the slope near the
reference temperature (Fig. 12). During cool climates the peat area
increases by 1.8% per centigrade but in warmer climates this
relationship reduces to one quarter (0.5% per centigrade) (Fig. 12).
The higher ratio in the cold house conditions is caused by the
replacement of polar and tundra biomes by boreal swampy climates.
Under warmhouse conditions, the increase in the area with high peat
forming potential is related to the increase in everwet biomes.
Summarising these findings about shifts in the distribution of
climatic belts, regional temperature and precipitation as well as peat
forming potential, the major temperature-related changes occur
during cooler climates. Changes in these factors as a result of
variations in the atmospheric greenhouse gas concentration are less
pronounced in warmer climates.
7. Discussion
7.1. Reference climate (pre-event climate)
Because of the lack of evidence for the occurrence of glacial
environments (Chumakov and Zharkov, 2003) in the latest Permian, a
climate reconstruction at the transition between coldhouse and
warmhouse climates was chosen as reference to cover a wide range
of possible global temperature changes through the whole warm
house and cold house. The cold–warm boundary is marked by the
presence versus absence of snowy climates as polar frost and tundra
biomes.
The presented numeric reconstruction (reference climate) of
climate zones at the Permian–Triassic boundary is in accordance
with geologic climate indicators. This model run is characterised by
a global annual mean temperature of 18.2 °C. This temperature is
about 3 °C above the current average. Kiehl and Shields (2005)
reconstructed a latest Permian world which was 8 °C warmer than
today. The dissimilarity between these temperatures is related to
the difference in focus of the two investigations and probably also
due to slightly different palaeogeo- and -topography and also the
M. Roscher et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 309 (2011) 186–200
195
6.7°C
10.8°C
12.2°C
14.6°C
reference
ocean
tropics
everwet
seasonal
desert
hot
cold
climate
16.2°C
18.2°C
20.4°C
23.2°C
26.0°C
30.5°C
steppe
hot
cold
temperate
everwet
seasonal
boreal
everwet
seasonal
tundra
polar frost
Fig. 10. Distributions of climatic belts at different global annual mean temperatures; simplified Köppen and Geiger climate classification, Mollweide projection; tropical and
subtropical climates are nearly unaffected by temperature changes, the boreal biomes of southern Gondwana are replaces by tundra and polar frost during global cooling and by
steppe and desert environments during warming.
difference in climate sensitivity of the two models adopted. While
Kiehl and Shields (2005) reconstructed the latest Permian climate
during the climate perturbation event with an atmospheric CO2-
concentration of 3550 ppm and investigated the oceanic currents in
a fully coupled model, a simpler model with a slab ocean only was
applied to test the stability of the latest Permian climate. Therefore
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70
m= 0.27%/°C
m= 0.33%/°C
desert + steppe
covered area on Pangaea [%]
60
50
40
boreal + temperate
m= 1.9%/°C
m= -0.15%/°C
30
m= -2.25%/°C
seasonal boreal + seasonal temperate
m= -0.4%/°C
20
m= 1.2%/°C
everwet boreal + everwet temperate
m= 0.3%/°C
10
m= 0.7%/°C
polar frost + tundra
m= -0.1%/°C
0
-12
-10
-8
-6
-4
-2
0
2
4
6
8
10
12
temperature change [°C] in respect to reference climate (18.2°C global annual mean)
Fig. 11. Percentage of land covered by different climate zones at various global annual mean temperatures; m = slope gradient of regression lines.
the pre-event reconstruction was chosen as reference climate. By
selecting the coldest reconstruction that matches the geologic
climate indicators, coverage of a wide range of possible temperature changes due to variations in the radiative forcing is realised.
Besides this difference in the approach, the model results for a
palaeoworld with 3300 ppm atmospheric CO2 (Fig. 13) are in
respect to seasonal mean temperatures very similar to the results of
Kiehl and Shields (2005).
Nevertheless, comparison of the reconstructed palaeoclimate in
the reference case established here, to a world perturbed to a similar
global annual mean temperature similar to the one of Kiehl and
Shields (2005) shows only moderate impacts on the distribution of
climatic belts (Fig. 5). Climate indicative sediments cannot be used to
prefer one climatic perturbation or the other and thus the results from
the two investigations are not in contradiction. In addition to the
climate indicative sediments the distribution of palaeobotanic
provinces can be used to validate the model. While large leafed
plants survived in wet biomes until the Triassic in southern China,
they disappeared in northern China (Xingxue and Xiuyuan, 1996).
This is in accordance with the reconstructed climatic belts (Fig. 4)
where the rise of the Dabie Shan Mountains in latest Permian times
acted as an orographic barrier dividing an everwet south-western
biome from the steppe and desert in the north-eastern rain shadow.
The strongly localised high precipitation rates in this mountain chain
additionally explain the huge flysch basin of the Song pan Ganzi
(Chang, 2000).
45
global average peat probability [%]
40
m= 0.51%/°C
35
30
m= 1.77%/°C
25
20
15
10
-15
-10
-5
0
5
10
15
temperature change [°C] in respect to reference climate (18.2°C global annual mean)
Fig. 12. Global average peat probability at various global annual mean temperatures; m = slope of regression lines.
M. Roscher et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 309 (2011) 186–200
197
23.2°C
ocean
tropics
desert
ever- seasonal hot
wet
cold
steppe
hot
temperate
cold
boreal
ever- seasonal ever- seasonal
wet
wet
coal
evaporite
aeolian sand
chert
tillite
reef
phosphorite
oil source rock
tundra
polar frost
www .geongrid.org
Fig. 13. Simplified Köppen and Geiger climate classification map of the reconstructed climate 8 °C warmer than recent climate and 5 °C warmer than the reference climate used here,
versus climate indicative sediments, major differences to Fig. 5 only in the dryer central Antarctica.
7.2. Effects of global temperature changes during the climate
perturbation event
Regional temperature changes related to global warming are
modulated by the latitudinal position. High latitude regions appear to
have a stronger temperature change than low latitude ones. This
relationship allows a better interpretation of regional proxy data and
their global implications. A low latitude warming of 5 °C (Holser et al.,
1989) can be readily transferred to an assumed global warming of 7 °C
and a temperature shift of +10 °C in Siberia and +12 °C in Antarctica.
The climate sensitivity of the utilised numeric climate model
changes with the global annual mean temperature. Below 11–12 °C
the temperature change related to a doubling of the atmospheric CO2concentration is 32 °C (Fig. 7). This represents a very strong
dependence on the snow and ice cover–albedo feedback within this
model during extremely low global annual mean temperatures. The
difference between the two sensitivities below and above the
reference climate can be explained by the change in the polar regions.
The climate sensitivity changes at the point where the polar climate
and the tundra disappears during warming (Fig. 7). Beyond this point
the important positive feedback loop connected to snow and ice
retreat, reduced albedo and amplified warming is no longer working,
and the climate sensitivity is reduced by about 30%.
The changing sensitivity of the climate system is also due to
changes in the response of the climatic belts to additional warming.
While the total size of dry biomes increase slowly with temperature, a
different response during warm and coldhouse conditions can be
observed in boreal, temperate and tropical biomes. They experience
large changes in their size and distribution during a coldhouse
warming but only minor shifts in warmhouses.
Commonly the transition from the Late Palaeozoic Ice Age (Late
Carboniferous–Early Permian) to the Mesozoic warmhouse is seen as
reason for the continental aridisation on Pangaea (Chumakov and
Zharkov, 2003). The results obtained here indicate a relatively weak
relationship between global temperature and size of dry environments. This supports the suggestion that the major climatic changes,
especially the Permian aridisation after the Gondwana Glaciation,
were rather caused by changes in the palaeogeography (Roscher and
Schneider, 2006; Roscher et al., 2008).
If existent, snowy climates disappear during global warming, but
boreal biomes are not replaced by temperate environments. The light
and thereby heat limitation during polar winters hampers the
increase of the winter temperatures. Thus stability of the boreal
biomes is bound to the light-availability in higher latitudes.
The changes in the size of the seasonal environments in respect to
the everwet ones can be explained by changes in the fluxes within the
water cycle. The increasing global temperature causes increasing
evaporation and thus the amount of precipitation is higher. If
precipitation increases in seasonal biomes they might change to
everwet conditions. Changes will mainly affect westernmost equatorial Pangaea, greater India, and southern Australia. These regions are
predefined by the wind systems for changes in the precipitation. The
equatorial very wet westerlies, which have occurred since the early
Permian (Tabor and Montanez, 2002) in the southern US, rain out
completely when hitting the continent. The Tethyan margin of
Gondwana is strongly influenced by the Permotriassic supermonsoon
system (Parrish and Peterson, 1988). Rising air masses in this system
take place during southern hemispheric summer over Gondwana and
during winter slightly north over the Neo-Tethys. An increase in the
atmospheric moisture load will therefore affect these regions. The
stability of the tropical environments in respect to temperature
changes during the latest Permian is shown here. Palynological
studies on the PETM event showed a similar stability of the tropical
rain forest biome during global warming (Jaramillo et al., 2010).
7.3. Geologic climate indicators
The geologic record provides few indications of climatic changes
exactly at the end of the Palaeozoic, because most of the continental
sections are incomplete. Succeeding tectonism and erosion led, for
instance, to a hiatus across the Permian–Triassic boundary in Africa
(Catuneanu et al., 2005). Nevertheless, where available, the Late
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Permian and Early Triassic sediments indicate contrasting depositional environments. Commonly, fine grained siliciclastics are
replaced by sandy river deposits as in the Karoo Basin, South Africa
(Smith, 1995; Ward et al., 2000), the Santa Maria Basin, southern
Brazil (Zerfass et al., 2003), the Sydney Basin, Australia (Miall and
Jones, 2003), the eastern Iberian Ranges, Spain (Arche and LopezGomez, 2005), the Russian platform and the South Uralian foredeep
(Newell et al., 2010). The change in sedimentary style is interpreted
by most of these authors to be caused by a rapid killing of plants
leading to a breakdown of the vegetation cover. Additional increase in
the rainfall, as modelled here, will amplify this effect. This proposed
incision in the palaeoflora seems to be in accordance with the Early
Triassic coal gap as first proposed by Retallack et al. (1996). However,
from the climatic point of view the non-deposition of coals in the early
Triassic cannot readily be related to harmful global warming. The
increase of the global peat-forming potential with increasing
temperature is bound to the areal spread of everwet biomes
(Fig. 11). Thus it remains difficult to explain either the coal gap or
the breakdown of the vegetation cover around the PTB by climatic
changes due to increasing global temperature.
To fully explain the change in the sedimentary style in various
basins around the world during the Permian–Triassic transition it is
necessary to investigate the shifts in extreme meteorological
conditions as floods and droughts. This may solve the problem of
the low frequency but high discharge events (Newell et al., 2010) that
are necessary to explain heavy siliciclastic input into latest Permian to
earliest Triassic depositional basins. This increase in continental
weathering and erosion could also explain the shift in the strontium
isotopic composition from the low Late Permian level to a higher in
the Early Triassic.
7.4. Global warming versus global cooling
Undoubtedly the Late Palaeozoic Ice Age finished in the Early
Permian with some small ice centres persisting until the end of the
Middle Permian (Chumakov and Zharkov, 2002, 2003; Roscher and
Schneider, 2006; Fielding et al., 2008), thus the Late Permian was
definitely a warmhouse. The indications of sea ice and glaciomarine
sediments in NE Asia predate the Permian–Triassic boundary
(Chumakov, 1994; Chumakov and Zharkov, 2003). However, these
Late Permian cooler climates can be well explained by the model run
with a global annual mean temperature of 12.2 to14.6 °C. The two
major parameters defining the climatic impact of greenhouse gases in
the latest Permian are the climate sensitivity and the sensibility of
climatic belts to react to temperature changes. In respect to coldhouse
climates the climate sensitivity is reduces by about 30% in warmhouses and the shifts of climatic belts during temperature changes
within a warm house are only of minor importance. Together both
facts show that the addition of carbon greenhouse gases to the endPermian atmosphere cannot produce large changes in the distribution
of climatic belts. Using the climate sensitivity of the PLASIM model as
shown in Fig. 7 a relation between atmospheric CO2 concentration and
the land cover of different climatic belts can be established as shown
in Fig. 14.
The lowered climate sensitivity during warm house climates (to
the right of the reference climate bar) as well as the moderate
sensibility of climatic belts to react to global temperature changes
limits the large scale change in the continental climate. The estimated
latest Permian climate sensitivity (4.7–7 °C, cf. Fig. 7 next to ref.
climate) is higher than the recent IPCC consensus of 1.5–4 °C for the
present climate but a lowered sensitivity will not substantially change
the relationship between atmospheric greenhouse gas concentration
and the distribution of climatic belts. If anything it will likely reduce
the estimated changes. In fact, lowered climate sensitivity will result
in lower temperature changes and thus temporal gradients in the
graphs of Fig. 14 will be weaker above and below the reference
climate. Since no mechanism is known to reduce the atmospheric
concentration of CO2 very quickly (b1000 a) the global cooling in
Fig. 14 has to be interpreted in a different way. The change in the
greenhouse gas concentration within the PLASIM model refers to a
certain change in the radiative forcing. Similar changes could be
achieved by the reduction of incoming energy due to aerosols.
Nevertheless, regardless of the source, a reduction of the atmospheric
greenhouse effect would imply stronger climatic changes than an
increase could do, particularly at high latitudes. We conclude that
global warming due to lava degassing or venting of contact
metamorphic generated carbon greenhouse gases have an effect on
the global annual mean temperature in the latest Permian but they
will most likely have only a little effect on the distribution of climatic
belts. Global cooling by aerosols or ash particles injected to the
atmosphere by volcanic activity will cause a significant alteration of
the global climate, especially when the temperature threshold
between warmhouse and coldhouse will be crossed.
The extrapolation of the results of this end-Permian study to other
events with Large Igneous Provinces and climate perturbations has to
be made with caution. Although nearly all of these boundary events
happened during warmhouse climates (Courtillot and Renne, 2003)
the palaeogeography, palaeotopography, pre-event atmospheric composition and solar constant were different. The relation between the
climate sensitivity and the ice-cover–albedo feedback loop might be
35
70
30
land cover of climate zones [%]
60
temperature
50
25
20
40
boreal + temperate
15
30
seasonal boreal + seasonal temperate
10
20
everwet boreal + everwet temperate
5
10
0
500
polar frost + tundra
1500
2500
3500
4500
5500
6500
7500
global annual mean temperature [°C]
desert + steppe
0
8500
9500
atmospheric CO2 concentration [ppm]
Fig. 14. Atmospheric CO2 concentration versus percentage of land covered by different biomes and global annual mean temperature; 1600 ppm represents the reference climate.
M. Roscher et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 309 (2011) 186–200
similar during all times with landmass in polar proximity. Therefore
we argue that warmhouse climates are more stable than coldhouse
climates during changes of the atmospheric composition.
8. Conclusions
Numeric simulation of greenhouse gas generated global temperature changes in the latest Permian world revealed that an increase in
temperature is accompanied by only minor shifts in climatic belts
whereas the climatic belts would experience strong changes during
cooling. The response of climatic belts to temperature changes is
different when starting from warmhouse or coldhouse conditions. The
global climate on a glaciated Earth is more sensitive to changes in the
atmospheric content of greenhouse gases than a warmhouse climate,
due to a strong feedback of ice-cover and albedo changes. Thus
variations in greenhouse gas concentrations are potentially more
efficient in changing the global temperatures in a cold- as opposed to a
warm-house climate. In this respect, the recent climate change is not
representative for understanding the latest Permian climatic changes.
By investigating the regional effects of global temperature changes a
clear relationship between palaeolatitude and local temperature was
established. The high latitude regions of Angara (Siberia) and southern
Gondwana (Antarctica, southern Africa, Australia, India) showed the
highest regional temperature change in respect to the global value.
These temperature changes are accompanied by modifications of the
precipitation patterns. The amount of precipitation increases in general
during global warming except for Siberia and southern South America.
During cooling the regional precipitation reduces. The synchronous
changes of temperature and precipitation change the regional classification of the climate. By the application of a simplified Köppen and
Geiger climate classification, based only on monthly mean data, it is
shown that the model does not reproduce the rapid climatic change on
the continents due to global warming in the latest Permian. Further
investigations on the frequency of climate extremes as droughts, floods,
heat waves and freezing events should be made to extend the analysis of
possible effects of radiative changes at the Permian–Triassic boundary.
Nevertheless, the investigation showed that a reduction in the
greenhouse effect, resulting in global cooling, would be much more
efficient in disturbing the global distribution of climatic belts than a
greenhouse warming.
Acknowledgements
We thank the Norwegian research council for support through a
SFF grant to PGP and a YFF grant to H. Svensen. We also wish to thank
T. K. Berntsen for fruitful discussions about atmospheric compositions
and S. Planke for support during the project and E. Kirk and F. Lunkeit
for support during the usage of PLASIM. Further we thank K. Fristad
for the comments on a previous version of the manuscript. We
appreciated the supportive reviews of N. Chumakov and an
anonymous reviewer and the comments of the editor F. Surlyk.
Appendix A. Supplementary data
Supplementary data to this article can be found online at doi:10.
1016/j.palaeo.2011.05.042.
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