characteristics resembling those of ENSO. This was not the
case with the previous generation of climate models. Nevertheless, the spatial structure of these events is not generally
well simulated, such as the asymmetry between the El Niño
and La Niña episodes. In terms of the recurrence of these
events, the periodicity simulated by the models is usually too
short and too regular. In general, the strong diversity of
observed spatial and temporal characteristics of ENSO is
often poorly simulated. Research works are being done to
identify the impact of the different atmospheric and oceanic
processes on the characteristics of ENSO, and on the reasons
for model errors.
The Madden and Julian—MJO—oscillation (Madden and
Julian 1994) is the main mode of intra-seasonal variability in
the tropical region, with a periodicity of between 30 and
90 days. Unlike ENSO, whose spatial structure is stationary,
this oscillation is characterized by a wave that propagates
from west to east, the intensity of the convection alternating
between reinforced and reduced. An MJO- type signal is
present in the results of most models, but several essential
characteristics of this mode of variability (amplitude, phase,
propagation) are not realistic. The roles of the different
processes and their interactions in the characteristics of this
mode of coupled atmosphere-ocean variability have not been
well identified and several hypotheses have been proposed.
In the extratropical regions, an important mode of variability is the North Atlantic Oscillation (NAO). It is a
pressure oscillation between the temperate and the subpolar
latitudes, often defined as the difference in normalized
pressure between the Icelandic low and the Azores anticyclone. It is associated with changes in prevailing westerly
winds throughout the North Atlantic Basin, and affects the
climate of Europe and its surroundings. For example, the
positive phases of NAO (NAO+) are associated with a
northward shift of low pressure systems with mild and rainy
winters and droughts in southern Europe. Current models
correctly simulate the spatial properties of the NAO, but are
not as good at simulating its temporal properties. In particular, the current trend of the NAO (an increase in positive
phases) is underestimated by the models. The reasons for
this underestimation are diverse: poor representations of i/the
interactions between the stratosphere and the troposphere,
ii/the exchanges between stationary waves and transient
activity (storms) and iii/the exchanges with the surface of the
ocean.
Recent Evolution of the Climate
Over the last 150 years, the evolution of the global surface
temperature is documented with a large set of observations.
Simulating this evolution is therefore one way to test climate
models. Between 1850 and 2000 the steady increase in the
concentration of greenhouse gases has led to an increase in
radiative forcing of about 2.5 W/m
2
. The uncertainty in this
forcing is estimated to be quite low at less than ±10%. Since
fossil fuels contain sulfur, CO 2 emissions are accompanied
by SO 2 emissions which lead to the formation of sulfate
aerosols. In 2000, these aerosols produced a radiative forcing
of about − 1 W/m
2 , but, depending on how it is estimated,
this value varies from − 0.5 to −2 W/m
2 . In addition, other
aerosols, such as soot or aerosols from biomass fires, may
also play an important role, but their effects are even less
well known. Thus, about a third of the positive radiative
forcing (albeit with a high degree of uncertainty) from the
increase in greenhouse gases is masked by the negative
radiative forcing from aerosols. In addition to anthropogenic
forcings, there are natural forcings. At the century time scale,
aerosols are mainly injected into the stratosphere by variations in the intensity of incoming solar radiation, and by
strong volcanic eruptions where they can remain for several
months or even years. These aerosols reflect solar radiation,
creating a negative forcing. At the end of the twentieth
century, strong volcanic eruptions were more frequent than
at the beginning, resulting in an enhanced radiative forcing.
Therefore, regardless of the climate response, there is
already an inherent uncertainty in the radiative forcing of
about ± 50% (IPCC 2013).
When only natural forcings are considered, simulated
warming is not in line with observations, especially since the
1980s (Fig. 31.9). However when all forcings are taken into
account (natural + anthropogenic), all models are able to
correctly simulate the increase in the mean Earth temperature
over the past 150 years (Fig. 31.9). Models simulate a
greater increase in temperature over the continents than over
the ocean and a geographic distribution of warming in
agreement with observations (IPCC 2013). Thus, temperature changes over the past 150 years make it possible to
verify that the climate response simulated by the models is
coherent with the observed temperature variations, although
there is too much uncertainty in the forcings to be able to
constrain precisely the climate sensitivity of the models.
The aerosols have two opposing effects: one warming the
surface, the other cooling it. The first one, called the direct
effect, is the diffusion of incoming solar radiation, where part
of the solar radiation is returned to space. The second, the
indirect effect, is the modification of the optical properties of
clouds: the presence of a large number of aerosols increases
the number of condensation nuclei. For the same amount of
liquid water, more numerous drops forming the clouds tend
to have a smaller radius and thus to diffuse more solar
radiation. Aerosols are also likely to modify the formation of
rain, and therefore the liquid water content of clouds. The
complexity of the radiative properties of aerosols in the
atmosphere make it more difficult to model the impact of
cloud physics.
31 From the Climates of the Past to the Climates …
463
case with the previous generation of climate models. Nevertheless, the spatial structure of these events is not generally
well simulated, such as the asymmetry between the El Niño
and La Niña episodes. In terms of the recurrence of these
events, the periodicity simulated by the models is usually too
short and too regular. In general, the strong diversity of
observed spatial and temporal characteristics of ENSO is
often poorly simulated. Research works are being done to
identify the impact of the different atmospheric and oceanic
processes on the characteristics of ENSO, and on the reasons
for model errors.
The Madden and Julian—MJO—oscillation (Madden and
Julian 1994) is the main mode of intra-seasonal variability in
the tropical region, with a periodicity of between 30 and
90 days. Unlike ENSO, whose spatial structure is stationary,
this oscillation is characterized by a wave that propagates
from west to east, the intensity of the convection alternating
between reinforced and reduced. An MJO- type signal is
present in the results of most models, but several essential
characteristics of this mode of variability (amplitude, phase,
propagation) are not realistic. The roles of the different
processes and their interactions in the characteristics of this
mode of coupled atmosphere-ocean variability have not been
well identified and several hypotheses have been proposed.
In the extratropical regions, an important mode of variability is the North Atlantic Oscillation (NAO). It is a
pressure oscillation between the temperate and the subpolar
latitudes, often defined as the difference in normalized
pressure between the Icelandic low and the Azores anticyclone. It is associated with changes in prevailing westerly
winds throughout the North Atlantic Basin, and affects the
climate of Europe and its surroundings. For example, the
positive phases of NAO (NAO+) are associated with a
northward shift of low pressure systems with mild and rainy
winters and droughts in southern Europe. Current models
correctly simulate the spatial properties of the NAO, but are
not as good at simulating its temporal properties. In particular, the current trend of the NAO (an increase in positive
phases) is underestimated by the models. The reasons for
this underestimation are diverse: poor representations of i/the
interactions between the stratosphere and the troposphere,
ii/the exchanges between stationary waves and transient
activity (storms) and iii/the exchanges with the surface of the
ocean.
Recent Evolution of the Climate
Over the last 150 years, the evolution of the global surface
temperature is documented with a large set of observations.
Simulating this evolution is therefore one way to test climate
models. Between 1850 and 2000 the steady increase in the
concentration of greenhouse gases has led to an increase in
radiative forcing of about 2.5 W/m
2
. The uncertainty in this
forcing is estimated to be quite low at less than ±10%. Since
fossil fuels contain sulfur, CO 2 emissions are accompanied
by SO 2 emissions which lead to the formation of sulfate
aerosols. In 2000, these aerosols produced a radiative forcing
of about − 1 W/m
2 , but, depending on how it is estimated,
this value varies from − 0.5 to −2 W/m
2 . In addition, other
aerosols, such as soot or aerosols from biomass fires, may
also play an important role, but their effects are even less
well known. Thus, about a third of the positive radiative
forcing (albeit with a high degree of uncertainty) from the
increase in greenhouse gases is masked by the negative
radiative forcing from aerosols. In addition to anthropogenic
forcings, there are natural forcings. At the century time scale,
aerosols are mainly injected into the stratosphere by variations in the intensity of incoming solar radiation, and by
strong volcanic eruptions where they can remain for several
months or even years. These aerosols reflect solar radiation,
creating a negative forcing. At the end of the twentieth
century, strong volcanic eruptions were more frequent than
at the beginning, resulting in an enhanced radiative forcing.
Therefore, regardless of the climate response, there is
already an inherent uncertainty in the radiative forcing of
about ± 50% (IPCC 2013).
When only natural forcings are considered, simulated
warming is not in line with observations, especially since the
1980s (Fig. 31.9). However when all forcings are taken into
account (natural + anthropogenic), all models are able to
correctly simulate the increase in the mean Earth temperature
over the past 150 years (Fig. 31.9). Models simulate a
greater increase in temperature over the continents than over
the ocean and a geographic distribution of warming in
agreement with observations (IPCC 2013). Thus, temperature changes over the past 150 years make it possible to
verify that the climate response simulated by the models is
coherent with the observed temperature variations, although
there is too much uncertainty in the forcings to be able to
constrain precisely the climate sensitivity of the models.
The aerosols have two opposing effects: one warming the
surface, the other cooling it. The first one, called the direct
effect, is the diffusion of incoming solar radiation, where part
of the solar radiation is returned to space. The second, the
indirect effect, is the modification of the optical properties of
clouds: the presence of a large number of aerosols increases
the number of condensation nuclei. For the same amount of
liquid water, more numerous drops forming the clouds tend
to have a smaller radius and thus to diffuse more solar
radiation. Aerosols are also likely to modify the formation of
rain, and therefore the liquid water content of clouds. The
complexity of the radiative properties of aerosols in the
atmosphere make it more difficult to model the impact of
cloud physics.
31 From the Climates of the Past to the Climates …
463