Directory UMM :Data Elmu:jurnal:A:Advances In Water Resources:Vol23.Issue2.1999:
Advances in Water Resources 23 (1999) 121±131
Global hydrological changes associated with a perturbation of the
climate system: the role of atmospheric feedbacks, their uncertainty
and their validation
Herve le Treut
*
Laboratoire de Meteorologie Dynamique du CNRS, Universite Paris VI, Case courrier 99, 4 Place Jussieu, 75252 Paris Cedex 05, France
Received 5 March 1998; received in revised form 14 September 1998; accepted 6 April 1999
Abstract
The anthropogenic increase of the atmospheric greenhouse eect is expected to bring important perturbations of the climate
system during the next century. The models which are used to compute scenarios of this future climate change nevertheless suer
from important uncertainties which make impossible the detailed prediction of regional impacts. Characterizing these uncertainties
as precisely as possible constitutes a necessary step to assess a climate risk and realize local impact studies. We describe the
manifestation of water vapour and cloud feedbacks in the present models, and show that satellite data, in particular, may constitute
an important source of information to constrain more eciently the models. Ó 1999 Elsevier Science Ltd. All rights reserved.
1. Introduction
The atmospheric concentration of greenhouse gases
has been increasing since the beginning of the century at
a rate which has no equivalent over the last millenia.
The concentration of carbon dioxide (CO2 ), for example, has risen from the preindustrial value of 280 ppmv
(parts per million in volume) to more than 360 ppmv,
whereas measurements throughout the last glacial/interglacial oscillation show a range of variation between
180 and 300 ppm roughly. Similarly the methane (CH4 )
concentration has risen from 0.8 to 1.6 ppm, while,
again, paleoclimate records from ice core data show that
the preindustrial value did not exceed 0.8 ppmv. Other
gases (N2 O, CFCs) have also seen their concentration
increase dramatically due to human in¯uence. Altogether these gases are responsible for an increased radiative forcing ± de®ned as the perturbation of the Earth
radiative balance at the tropopause ± of about 2.5 W
mÿ2 [22]. This value may appear modest compared to
the mean absorbed solar radiation, which is about 240
W mÿ2 . But this 1% perturbation of the Earth energetics, although small in relative value, is able to bring
about important consequences. The diminution in the
*
Corresponding author. Tel.: +33-01-4427-8406; fax: +33-01-44276272.
incident solar radiation which might have caused the
XVIIth Century Little Ice Age was about half of this
value [38]. Moreover the anthropogenic greenhouse effect is expected to increase importantly in the future, as
greenhouse gases have generally a long residence time,
and tend to accumulate within the atmosphere. Due to
this long residence time, the greenhouse gases are also
well mixed within the atmosphere, and instead of being
considered individually, their eect is often summarized
through an equivalent-CO2 concentration. The hypothesis of an equivalent CO2 -doubling, which has been used
for some of the scenarios reviewed below, corresponds
roughly to a forcing of 4 W mÿ2 [8] and may be attained
during the ®rst part of the next century [21,23], irrespective of the reductions in the greenhouse gas emissions which are presently considered.
Evaluating the possible impacts of this anthropogenic
greenhouse forcing is therefore of immediate concern.
But model predictions are not free from uncertainties.
Although all models coincide in that they show a signi®cant change of the climate system to the anthropogenic forcing, a signi®cant divergence also appears in the
quanti®cation or geographical distribution of these impacts. This re¯ects the very subtle balance between opposite feedback processes which control the climate
system. In Section 2 we review a few model experiments
which show how eective this control is. We then review
some of the methods which are available to validate the
0309-1708/99/$ - see front matter Ó 1999 Elsevier Science Ltd. All rights reserved.
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H. l Treut / Advances in Water Resources 23 (1999) 121±131
models, focusing in Section 3 on the use of contemporaneous satellite data, and concluding in Section 4 with
the use of past data, in particular over the last century.
2. The climate response to anthropogenic forcing: global
features
2.1. Generalities
Many model simulations of the climate response to
an anthropogenic forcing have used atmospheric General Circulation Models (GCM) coupled to simple slab
ocean representations.
GCMs use the Navier±Stokes equations to describe
the general motion of the atmosphere over the globe. In
addition to the components of the wind, the models also
predict the pressure and temperature ®eld, and hydrological or surface variables, such as atmospheric water
vapour and cloud water content, or soil moisture estimate and snow cover. The equations are solved over
discretization grids whose horizontal resolution varies
strongly from model to model, from a grid size of about
500 km for coarser models, to a grid size of about 50 km,
for the higher resolution models used for weather forecast. The lack of representation of the smaller spatial
scales is therefore always a ®rst limitation of the GCMs.
The actual numerical solving of the equations may be
done in a spectral domain, or through ®nite dierencing.
The number of vertical levels may vary from about 10 to
30. The AMIP experiment [16] has provided an exhaustive review of the models currently available.
Whereas for weather forecast applications, the speci®cation of the initial atmospheric state from which the
model is run is very obviously of utmost importance,
this is no longer true for climatic applications. In this
case one is mostly interested in the statistical behaviour
of the atmosphere over long periods of time, which is
primarily controlled by the energetics of the system. All
models include a representation of the radiative transfer
in the solar and terrestrial domains, of the energy exchanges with the surface, of the main atmospheric hydrological features, such as latent heat release within
clouds, or cloud/radiation interaction. An accurate and
balanced representation of those energy and water
sources and sinks is of speci®c importance for climatological studies.
Most of these physical processes, however, correspond to unresolved spatial scales: the energy exchanges
over continental surfaces are controlled by the vegetation cover, and by motions in the boundary layer which
are organized at the scale of about 100 m; the tropical
convection is one of the main sources of energy for the
atmosphere, but corresponds to motions organized primarily at the scale of a few kilometers. All those processes need to be represented in a simpli®ed,
parametrical manner in the GCMs. But there is a large
variety of possible approaches to these parameterization
problems, a situation which is responsible for the large
number of existing climate models (about 30 groups
have participated in the AMIP project).
For climate sensitivity experiments, the role of the
ocean component is also crucial. Climate change can
occur and organize itself over long periods of time essentially because of the thermic inertia of the ocean.
There is a whole hierarchy of ocean models used for
climate studies. Slab ocean models constitute one of the
simplest approaches, in which the ocean passively stores
heat in a slab layer of about 50 m, with no representation of the changes in the ocean vertical and horizontal
energy transport. These models can describe the equilibrium response of the atmosphere/surface ocean system to prescribed changes in the climate forcing. They
cannot take into account the eects of ocean dynamics ±
which are represented in the newer generation of coupled models using ocean general circulation models. But
comparison between those two approaches [35,36] has
shown that, if the equilibrium response fails to represent
the patterns which are associated with a slower ocean
heating, particularly in the regions of deep water formation around Antarctica or in the Norwegian Sea, it
nevertheless constitutes a good approximation of the
climate perturbation in most areas. These simpler
models are also very precious, because they isolate the
contribution of the atmosphere in the climate response
to an anthropogenic forcing, and therefore the contribution of the atmosphere to current uncertainties in our
evaluation of future climate changes.
This crucial role of the atmosphere has been evidenced in many studies, perhaps most spectacularly by
the recent comparisons of the climate response to CO2
and aerosol increase. The motivation of those studies
was primarily to understand the climate variations
throughout the XXth Century, during which, in addition to greenhouse forcing, other radiative perturbations
such as those due to aerosols cannot be neglected
[27,14,39]. But, as some of these simulations consider
separately the impact of the greenhouse and aerosol
perturbations, using the same model [49,42,11,29,30],
they also provide useful information on the climate response to rather dierent perturbations. The CO2 forcing is distributed almost uniformly over the globe. The
aerosol forcing on the contrary is very unevenly distributed with a maximum over the continents of the
Northern Hemisphere, as shown by the sulphate aerosol
distribution for present and preindustrial conditions
[26]. Also, the aerosol negative forcing is due to a change
in solar re¯ection, either directly when solar radiations
are scattered by the aerosols, or indirectly, when the
aerosols change the size and density of the cloud droplets. The aerosol impact is therefore correspondingly
stronger in summer.
H. l Treut / Advances in Water Resources 23 (1999) 121±131
2.2. Examples using the LMD GCM
In the following we use results obtained with the
LMD (Laboratoire de Meteorologie Dynamique)
GCM. The ®rst version of the model was developed by
Sadourny and Laval [44]. Since then, the model has
evolved continuously, but some of its original features
are unchanged: the model uses a ®nite dierence discretization of the Navier±Stokes equations over an Arakawa C-grid. In the versions considered in the present
paper, the horizontal grid is regular in longitude (with a
number of points ranging from 48 to 96 depending on
the model versions) and in sine of the latitude (with a
number of points ranging from 36 to 72). The vertical
coordinate is the pressure normalized by its surface
value (r coordinate) and the number of vertical levels
varies from 11 to 19 depending on model version.
In addition to this treatment of the dynamical equations, the model includes a comprehensive representation of the ``physical'' processes: subgrid-scale processes,
radiative transfer, hydrological features and exchanges
with the surface. In the examples which follow, the
LMD Cycle 4 version is being used [28]. The shortwave
(solar) radiation transfer is parameterized using a
modi®ed version of Fouquart and Bonnel [15] where
two spectral bands corresponding to the visible and
near-infrared are distinguished. In the longwave (terrestrial) part of the spectrum, the scheme developed by
Morcrette [37] is used and six spectral bands are considered. The treatment of convection is still the original
one, where a moist adjustment is combined with a
scheme derived from the Kuo [25] parameterization. A
diusive approach is used to represent vertical mixing
within the atmospheric boundary layer. The treatment
of the surface conditions, although comprehensive, is
rather simple, with soil moisture being treated following
a single bucket approach: the inclusion of a more advanced scheme including the eects of vegetation has
been considered in LMD Cycles 5 and 6 only. This could
be problematic if we were to discuss regional impacts.
The treatment of clouds is comparatively more advanced; a prognostic cloud water budget equation is
included in the model, with a corresponding parameterization of the source and sink terms: condensation,
evaporation, conversion to precipitable water.
The results of simulations testing the response of the
LMD GCM to CO2 and aerosol forcing are shown in
Fig. 1. The response to the two perturbations are ®rst
considered separately, a third diagram showing their
combined eect. The representation of the sulphate effect within the LMD GCM, which involve both the direct and indirect eects, as de®ned above, gives a global
forcing of about ÿ1.2 W mÿ2 , which happens to be
approximately similar in amplitude but opposite in sign
to the CO2 forcing since the beginning of the industrial
era. A striking feature is the symmetry between the two
123
responses to sulphate aerosol and CO2 . In both cases the
surface temperature change is characterized by an ampli®cation over the Polar regions and over the continental areas. In a latitude±altitude zonal mean section
(Fig. 2), one can also recognize a well-known feature of
the model response [46], which provides part of the explanation for this polar ampli®cation: at high or middle
latitudes, the temperature change is larger near the
ground, whereas at low latitudes, it reaches its maximum
at about 12±15 km. This latter eect has been attributed
for a long time to the convective activity of the low
latitude regions [46]. At the same time the stratosphere
responds with a cooling (in the case of a CO2 -induced
tropospheric warming) or a warming (in the case of an
aerosol-induced tropospheric cooling). Such a stratospheric response, in the case of the aerosol forcing, can
be the consequence of internal atmospheric feedbacks
only, and re¯ects in particular the change in water vapour associated with climate cooling. Of course, the last
panel of Fig. 1, where both the CO2 and sulphate
aerosol eects are imposed on the climate system, shows
the limit of this symmetry between the response to the
two forcings. In this case (which is largely an academic
one since the role of the other greenhouse gases and
aerosols has been ignored), the Northern Hemisphere
(NH) is cooling whereas the Southern Hemisphere (SH)
is warming. This eect has been invoked to explain the
slower warming of the Northern Hemisphere throughout the century [45]. But even in this case, each of the
Hemispheres shows a very speci®c spatial pattern with
an enhancement of both the NH cooling and the SH
warming at high latitudes and over continental areas.
Our results indicate that the response to any form of
pollution is largely non-local. This is important politically, because the countries responsible for the pollution
may not be those who suer the most from its consequences, and also for the detection of the ®rst signs of a
climate change, because they will not be related in a
simple manner to the forcing.
This global organization of the response also re¯ects
the importance of the atmospheric control on the climate. Another aspect of this control is evidenced by
Fig. 3, again from results of the LMD GCM [30], where
the global surface temperature changes from a series of
sensitivity experiments to dierent forcings, when plotted against changes in the global radiative forcing, tend
to line along a unique curve which describes the model
sensitivity ± incidently larger for colder climates ± and
depends very little on the nature and distribution of the
forcing. The forcings considered here include: a doubling of the atmospheric CO2 concentration ± two sets
of experiments ± a solar constant increase, and increases
since the beginning of the industrial era of respectively,
the CO2 concentration, the sulphate aerosols, and the
tropospheric ozone. All those experiments are described
in [28,30], from which Fig. 3 is taken. Ramstein et al.
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H. l Treut / Advances in Water Resources 23 (1999) 121±131
Fig. 1. The surface temperature response of the LMD GCM, coupled to a simple slab ocean model, to a radiative forcing corresponding to: (a) the
CO2 increase since the beginning of the industrial era; (b) the sulphate aerosol increase for the same period (direct and indirect eects); (c) the sum of
the two forcings (from [30]) (See text for comments).
[40] have shown that the response to the condition of the
Last Glacial Maximum can be qualitatively dierent,
probably because of the strong modi®cation of the Pole
to equator gradient of temperature characterizing this
period. But the atmospheric feedback eects appear to
exert a strong control not only on the general geographical pattern of any climate change, but also on its
amplitude.
Unfortunately, if, for a given model, the response of
the climate system to an external perturbation seems
well behaved, the involved feedback eects are very
dicult to simulate accurately, and the response is very
model-dependent. It is well known for example that the
equilibrium temperature response to a doubling of the
CO2 , may range from 1.9 to 5.3 degrees [47]. The regional distribution of the climate change is also a delicate issue. On one side the geographical distribution of
the temperature and precipitation changes associated
with a CO2 doubling, displayed for 3 dierent models by
the ®rst IPCC report [21], or for 8 models as part of a
H. l Treut / Advances in Water Resources 23 (1999) 121±131
125
Fig. 3. Summary of equilibrium sensitivity experiments carried out
with the LMD GCM Cycle 4, coupled to a slab ocean. These experiments are described in [38,28,30]. As indicated by the legend they include sensitivity experiments to a change in the solar constant, to a
doubling of the CO2 , and to changes in CO2 , aerosols, or tropospheric
ozone concentration from preindustrial to present conditions. The plot
gives the mean global surface temperature response (in degrees) as a
function of the mean global radiative forcing (in W mÿ2 ). Regardless of
the geographical distribution of the forcing, the points tend to line
along a curve whose slope de®nes a global `climate sensitivity', which
appears larger for colder climate.
3. The main feedback processes and their validation
through satellite data
Fig. 2. Changes in the altitude/latitude distribution of the temperature
simulated by the LMD GCM, coupled to a simple slab ocean model
and corresponding to: (a) the CO2 increase since the beginning of the
industrial era; (b) the sulphate aerosol increase for the same period
(direct and indirect eects); (c) the sum of the two forcings (from [30])
(See text for comments).
more recent intercomparison held within the framework
of CLIVAR (McAvaney and Le Treut et al., 1998,
personal communication), reveals some general consistency at a very large scale, with an ampli®cation of the
surface warming over the polar regions, over the continents and in winter, and with a general increase in the
precipitation, both in the equatorial and mid-latitude
regions. On the other side, the regional response diers
largely from one model to the other: in particular some
models show a displacement of the precipitation zones,
and associated risks of drought, which are not con®rmed by other simulations.
The main feedback eects which aect the climate
response to anthropogenic perturbations have been
identi®ed for a long time (see for example the review of
Schlesinger and Mitchell [46]). The role of the atmosphere was stressed in the preceding paragraph, but
oceanic, biochemical or chemical processes are also
important. The representation of all those eects within
climate models is subject to considerable uncertainty.
The purpose of the present section is to show that
each of these feedbacks may be and must be studied
individually, if one wishes to quantify the domain of
uncertainties associated with the estimation of future
climate changes. We focus on the water vapour and
cloud feedbacks, because they are probably the processes which respond more directly to any climate
forcing, and are related to the changes in precipitation
which are also discussed. They have also been the subject of many studies, triggered in particular by the ®rst
model intercomparisons of Cess et al. [7].
3.1. Water-vapour feedbacks
The water vapour eect may appear simple in essence: as the climate gets warmer, the saturation value of
the atmospheric water vapour concentration increases.
In all models this translates into an increase in the water
vapour itself, which increases the greenhouse eect, and
almost doubles the climate response [21]. The accuracy
with which models simulate this change in water vapour
126
H. l Treut / Advances in Water Resources 23 (1999) 121±131
is of course dependent on the model ability to control
eciently the relative humidity of the atmosphere, and
in particular the contrast between the very humid regions near the InterTropical Convergence Zone (ITCZ)
and the very dry areas of the subtropical areas, in the
descending part of the Hadley±Walker cells. It is also
linked to the eciency of the convective parameterizations, which contribute to extend this increase in humidity to the higher levels of the troposphere, in low
latitude regions. The data that can be used to check the
simulated variations of the water vapour content are all
subject to limitations:
(i) the radiosonde data extend over several decades,
but their spatial coverage is limited. The quality of
the data as one gets higher into the atmosphere
may also be questioned [18,17]. Also their quality
may have varied from decade to decade.
(ii) the satellite data cover a restricted period of
about a decade. They provide indirect measurements of the radiative eect of water vapour, in different spectral bands, and need to be interpreted
with care. Indications on the behaviour of the water
vapour within the atmosphere may be obtained
from the clear-sky longwave measurements of Earth
Radiation Budget Experiment (ERBE), from microwave radiometers such as Special Sensor Microwave
Imager (SSMI) (over the oceans only), from the vertical pro®lers such as Tiros-N Operational Vertical
Sounder (TOVS), or from speci®c infrared channels
such as the Meteosat water vapour channel.
Those data are enough to reveal some systematic
errors of the models. The LMD GCM for example is
both too cold and too dry in the higher troposphere [2].
But we also want to use them in order to assess the
strength of the atmospheric water vapour feedbacks,
which means to diagnose the derivative of the water
vapour when the climate (and therefore the surface
temperature) changes. This is a more complex problem:
the only observed climate changes are the seasonal
variations, or interannual ¯uctuations such as the opposition between El Nino and La Nina conditions in
87±88, for which a complete set of satellite measurements is available, and the patterns associated with
those ``short-term'' ¯uctuations are very dierent from
those which characterize the long-term climate evolutions. The water vapour feedbacks are correspondingly
dierent. For example the seasonal changes of water
vapour over the oceans, as may be analysed from the
SSMI data [3], depend strongly on the changes of the
vertical gradients of temperature: over the oceans the
seasonal changes of temperature are smaller at the
surface, due to ocean inertia, than at higher altitudes,
where the in¯uence of the continents is being felt more
strongly. As a consequence the greenhouse eect may in
some case diminish with increasing surface temperature, because the stronger longwave emission from the
higher and warmer atmospheric layers dominate the
increased water vapour absorption. This eect is
faithfully reproduced by models and must not in any
case be interpreted as a negative water vapour feedback, as could be from a hasty interpretation. It merely
re¯ects the complexity of the seasonal response. In
general, in spite of some quantitative dierences the
models reproduce correctly the seasonal cycle or interannual ¯uctuations of the clear-sky greenhouse eect
[4]. The results of Roca et al. [41], from satellite measurements in the Meteosat water vapour channel, also
show the ability of the models to successfully reproduce
the negative correlation between the surface of the ascending and descending branches of the Hadley-Walker
circulation, measured in monthly averages throughout
the seasonal cycle. All those features add some credibility to the capacity of the models to simulate the
water vapour feedbacks in scenarios of future climate
changes.
But ultimately no perfect validation is yet possible. In
particular the radiative eect of the water vapour
changes depend on the changes of the vertical stability
of the atmosphere, which are very dierent at the seasonal or interannual time scale, or for climate sensitivity
experiments. This is illustrated in Fig. 4. The sensitivity
of the clear-sky greenhouse eect to surface temperature
is diagnosed from the output of the LMD GCM, using
the GCM radiative code in o-line mode. The sensitivity
at the seasonal and interannual scales have been veri®ed
using observed data, and the model is in good qualitative agreement with these observations. The very large
dierences between the dierent cases, illustrated in the
upper panel, are reduced when the o-line computations
are carried out with a ®xed relative humidity and a ®xed
temperature lapse rate. The sensitivity value of 2 W mÿ2
Kÿ1 , is characterizing the water vapour feedback in
climate scenarios, and it corresponds to a weak perturbation of the atmospheric vertical strati®cation in
temperature and humidity. That such a weak change
should characterize a modi®ed climate is however a
model prediction that cannot be veri®ed from observations.
Lindzen [32] has proposed a mechanism of model
error which has been the source of many debates and
may be summarized as follows: if the increase in water
vapour in the moist ascending regions is accompanied
with a decrease in the drier descending regions, the latter
eect could be dominant because a change of water
vapour water content in a dry area has more radiative
impact. This could in principle constitute a negative
feedback eect that models might misrepresent because
of their inability to represent correctly the contrast between the very dry subtropics, and the moist convective
regions. There are no model results, nor observational
records to fully support such a mechanism, but it is also
impossible to rule it out completely.
H. l Treut / Advances in Water Resources 23 (1999) 121±131
Fig. 4. Sensitivity of the clear-sky longwave outgoing ¯ux to sea-surface temperature (SST) (from [4]). It is computed using dierent
modi®cations of the climate to de®ne the SST perturbation: seasonal
cycle, interannual variations, and two climate warming experiments
using the LMD GCM (sensitivity to solar constant and CO2 doubling).
The diagnostics are carried out over the oceans from the output of the
LMD GCM and the results are plotted as a function of the mean SST.
In the lower panels the same o-line diagnostics have been carried out
while keeping unchanged either the relative alone in the climate perturbation (b) or the both the relative humidity and the temperature
lapse-rate (c). This indicates that the successful prediction of the small
time scales by the model is a strong test, because those scales have a
complex behaviour.
3.2. Cloud feedbacks
The largest uncertainty as regards the evolution of
future climate is probably the behaviour of clouds.
Cloud feedbacks include a wide range of eects which
have been discussed over the years. The eect of cloud
altitude, for example, has been described by Stephen and
Webster [48], who have illustrated through a simple
127
model that an increase in low cloudiness is dominated by
the eect of cloud albedo, and contributes to a climate
cooling, whereas an increase in high cloudiness, is
dominated by the cloud greenhouse eect and contributes to a climate warming. But they have also shown
that changes in cloud optical properties have to be
considered simultaneously. For a low cloud whose eect
in the infrared is already saturated, an increase in water
content results in an increased albedo eect and therefore a cooling, whereas for high clouds the competition
between the cloud albedo and the cloud greenhouse effect is more uncertain. All those eects have been recognized as essential since the ®rst model studies of the
greenhouse eect [34].
Since then, new processes have emerged which have
added even more to the complexity of the problem. In
particular the importance of the microphysical structure
of the clouds has been recognized. First the size of the
hydrometeors has a great importance for the scattering
of solar radiation: for the same cloud water content, a
dimininution of the droplet size increases both the
number of droplets and the surface which they cover.
This eect is responsible for the sulphate aerosol indirect
eect, but may also be aected by natural processes,
such as the ocean biology which produces di-methylsulphate [9]. The transition between ice and liquid
phases is another microphysical process of very large
importance. Liquid water clouds tend to precipitate
more eciently, but only when a certain threshold
necessary for an ecient coalescence of cloud droplets is
attained. Senior and Mitchell [47] have demonstrated
that a global warming could then be damped by the
transformation of ice clouds into more re¯ective liquid
water clouds. Li and Le Treut [31] have shown that the
choice of the temperature range throughout which the
liquid/ice transition takes place may aect the sign of
this radiative feedback.
Most of these processes have slowly been integrated
into models and a number of qualitative features are
now well understood. For a CO2 increase, in most cases,
the models show a decrease of the cloudiness in the low
and middle troposphere and an increase in the upper
troposphere (results of the LMD GCM are shown in
Fig. 5 as an example). This partly re¯ects the fact that,
as the water vapour saturation level increases with increasing temperature in the lower troposphere, it becomes more dicult to reach saturation and form a
cloud through water vapour condensation. This low
level cloudiness decrease is therefore by no way contradictory to the increase in the water vapour concentration noted above. The increase in high cloudiness
proceeds from the reverse mechanism and is also associated with a higher altitude of the tropopause level. In
the ITCZ, in addition, most models show an increase in
convective clouds. This eect can be easily understood:
although the smaller Pole-to-Equator temperature
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H. l Treut / Advances in Water Resources 23 (1999) 121±131
Fig. 5. The changes in the mean zonal cloudiness (in percents) associated with a CO2 increase from preindustrial to present condition
(from [30]).
gradients associated with a warmer climate generally tend
to slow the Hadley cell meridional circulation [1,43,38],
the low-level convergence of both warmer and moister
air creates more favourable conditions for convection.
Finally a last feature is shown by most models, at least
those including a physical representation of cloud formation: cloud fraction and cloud liquid water content
increase at the liquid/ice phase transition, for a warmer
climate. This eect is due to the very dierent microphysical properties of liquid water and of ice clouds.
The mechanisms which contribute to cloud modi®cation are also very largely the ones that are responsible
for rain modi®cations. The increase in equatorial convective cloudiness is accompanied by a corresponding
increase in equatorial rain. At mid-latitudes the transport of water vapour, depends on the latitudinal gradient of humidity, which is dominated by the exponential
increase in the saturation level of water vapour, following the Clausius±Clapeyron law.
The combination of these dierent processes, in spite
of the qualitative convergence of the model simulations,
leads to a very large scatter in the quantitative radiative
eect. This, again, raises the problem of validation.
As for water vapour, two types of data sets can be
used.
(i) Cloudiness data from conventional in situ measurements at weather stations. Such data have been
gathered through a very long eort by Warren et al.
[51]. Henderson-Sellers [20] has shown some longterm trends in cloud data, which may relate to climate change.
(ii) Satellite data, and most notably the ISCCP climatology (International Cloud Satellite Climatology Project) which was developed speci®cally for
the purpose of model validation and covers the
whole period from July 1983 up to now. A large variety of other instruments give a relevant information about clouds. One should perhaps give a
special mention to broad-band measurements such
as the ERBE measurements, which provide some access to the cloud radiative impact. Also, the cloud
water content is measured through microwave radiometers such as the SSMI one, but the uncertainty
of the retrieval is very large: the annual mean over
the oceans is 0.081 kg mÿ2 in the estimate of Greenwald et al. [19], compared to 0.059 kg mÿ2 in the estimate of Weng and Grody [52].
An interesting and early example of how those data
may be used to point out possible errors in the design of
models can be found in the work of Tselioudis et al. [50].
They have used correlations between cloud optical
thickness and cloud temperature to show that empirical
relations where cloud condensed water content increases
with temperature may be wrong in many situations and
may introduce arti®cial feedbacks in the model. Other
examples [12,13] show how useful the study of correlations between parameters may be to validate the models.
But again an important diculty comes from the peculiarities of the seasonal and interannual changes to
which observed data give access: at these time scales
cloud changes are both due to large displacements of the
Fig. 6. Derivation of cloud properties with respect to SST (plotted as a
function of mean SST) (from [5]). The diagnostics are carried out over
the oceans and results are plotted as a function of the mean SST. The
information from independent observations (ERBE longwave and
shortwave forcing, ISCCP retrievals of the cloud fraction, cloud top
pressure and cloud optical properties, TOVS retrieval of the cloud
fraction) is very consistent. The dotted curves correspond to a restriction of the correlation to changes characterized by a weak modi®cation of the dynamics (referred to as Case III), de®ned using the
NCEP or DAO reanalysis of the atmospheric circulation. These diagnostics provides a very powerful constraint on the models.
H. l Treut / Advances in Water Resources 23 (1999) 121±131
meteorological patterns, and to thermodynamical feedbacks such as those relevant to study a global warming.
Bony et al. [5] show a method to separate those eects:
when studying the regression between dierent cloud
parameters they stratify the relation using the vertical
velocity as an index of the circulation and its changes
(Fig. 6). The consistency of the results when they consider dierent cloud parameters, and therefore dierent
satellite instruments, is a good indication of their relevance for model validation.
4. Other approaches to model validation
The reference to past climates oers other possibilities
to evaluate the models. We review them brie¯y in this
last section. In all cases these methods allow a better
insight into the qualitative behaviour of the climate
system, but also bring new elements of quantitative
uncertainty (linked for example to the measure of past
SSTs, of past radiative forcing). Also, the atmospheric
processes can only be considered indirectly.
For long time scales, one may consider the climate
evolution over the last glacial cycle [33] as a way to
determine a climate sensitivity: both the forcings (astronomical changes of the insolation, greenhouse gases
concentration) and the SST evolutions are known from
astronomical calculations and ice or deep-sea records.
Alternatively one may also reconstruct climate extrema,
such as the last glacial maximum (21 000 yr Before
Present), or the warmer conditions of the Holocene
(6000 yr Before Present): this is in particular the objective of the PMIP programme [24].
But the near past is also an important reference period for the models. Whether the global temperature
increase of about 0.6°C since the beginning of the industrial area constitutes a ®rst sign of the warming to
come, or is due to natural ¯uctuations of the climate, is a
matter of debate [23]. To interpret the changes that occurred since the beginning of the industrial area, however,
one has to add ± or substract ± the eect of at least two
other anthropogenic perturbations: the changes in ozone
chemistry and the increased aerosol loading of the atmosphere. A characteristic feature of both ozone and
aerosols is that they have a short life within the atmosphere, and, as a result, are very unevenly distributed.
Ozone is principally formed in the stratosphere, through
speci®c photochemistry, whose perturbation by CFC
leads to an ``ozone hole'' mostly apparent over Antarctica
during the Southern Hemisphere Spring, and also to a
weaker diminution of stratospheric ozone at all latitudes.
This stratospheric depletion causes a negative perturbation of the atmospheric system (of the order of 0.2 W mÿ2
± from IPCC [23]. But ozone is also formed in the lower
layers of the atmosphere, though the transformation of
nitrous oxides (NOx ) in the presence of hydrocarbons
129
such as methane. This tropospheric ozone formation,
which depends upon temperature and is felt strongly
during the Northern Hemisphere summer, over the continental areas, causes a positive forcing of the climate
system, whose present estimation is about 0.3 W mÿ2 [23].
Aerosols are also largely released over the Northern
Hemisphere continents (although this image may be
biased because the aerosols taken into account so far in
climate simulations are sulphate aerosols: aerosols from
biomass burning, for example, have a very dierent
distribution). Their main impact is to cool the climate
system by increasing the re¯ection of solar radiation,
both directly by Mie scattering, or indirectly because
they contribute to the nucleation of cloud droplets,
which are then more numerous, and re¯ect the solar
radiation more eectively (for a given amount of cloud
water) [10]. Smaller droplets also diminish the eciency
of precipitation and lead to thicker clouds. A considerable uncertainty aects our estimations of the negative
aerosol forcing since the beginning of the industrial era:
it is known with a factor 2 or 3 at best, but might be
important, under ÿ1 W mÿ2 [22,6,30].
The history of the climate over the last century, as can
be reconstructed by models is therefore the product of
an uncertain forcing by an uncertain climate sensitivity.
Many processes are generally ignored in the models: the
possible non-linear response of the ocean circulation,
which has been observed in the past and is beyond the
reach of present models, because they do not represent
the dynamics of continental glaciers; the possible release
of methane from the permafrost; the role of solar ¯uctuations, of volcanic eruptions. As in the case of the
atmospheric feedbacks discussed above, the progress of
our understanding will most certainly reduce those uncertainties.
5. Conclusions
If the eventuality of an anthropogenic climate change
cannot be questioned, it is doubtful that the climate
system may ever be completely predictable, in view of its
incredible complexity. The examples of water vapour
and cloud feedbacks given in the present paper concern
the role of the atmosphere only, which is already responsible for a large uncertainty. The role of the continental hydrology, of the vegetation, of the oceans, of the
ice sheets, of the ocean biochemistry, of the atmospheric
chemistry have all been overlooked in current GCMs.
The application of scenarios at the local scale must
therefore be considered as some exercise of risk analysis.
At the same time the results reviewed here show that we
have now enough data to constrain more eciently the
models than is usually done, and modellers should
progressively be in a position to de®ne more precisely
the uncertainties attached to their scenarios. This
130
H. l Treut / Advances in Water Resources 23 (1999) 121±131
approach, which is slow and unglamorous, may nevertheless constitute the main source of information towards more useable scenarios.
Acknowledgements
As evidenced by the citations in the text, this review
owes a lot to discussion with, and work from S. Bony,
Z.X. Li and J.P. Durel.
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Global hydrological changes associated with a perturbation of the
climate system: the role of atmospheric feedbacks, their uncertainty
and their validation
Herve le Treut
*
Laboratoire de Meteorologie Dynamique du CNRS, Universite Paris VI, Case courrier 99, 4 Place Jussieu, 75252 Paris Cedex 05, France
Received 5 March 1998; received in revised form 14 September 1998; accepted 6 April 1999
Abstract
The anthropogenic increase of the atmospheric greenhouse eect is expected to bring important perturbations of the climate
system during the next century. The models which are used to compute scenarios of this future climate change nevertheless suer
from important uncertainties which make impossible the detailed prediction of regional impacts. Characterizing these uncertainties
as precisely as possible constitutes a necessary step to assess a climate risk and realize local impact studies. We describe the
manifestation of water vapour and cloud feedbacks in the present models, and show that satellite data, in particular, may constitute
an important source of information to constrain more eciently the models. Ó 1999 Elsevier Science Ltd. All rights reserved.
1. Introduction
The atmospheric concentration of greenhouse gases
has been increasing since the beginning of the century at
a rate which has no equivalent over the last millenia.
The concentration of carbon dioxide (CO2 ), for example, has risen from the preindustrial value of 280 ppmv
(parts per million in volume) to more than 360 ppmv,
whereas measurements throughout the last glacial/interglacial oscillation show a range of variation between
180 and 300 ppm roughly. Similarly the methane (CH4 )
concentration has risen from 0.8 to 1.6 ppm, while,
again, paleoclimate records from ice core data show that
the preindustrial value did not exceed 0.8 ppmv. Other
gases (N2 O, CFCs) have also seen their concentration
increase dramatically due to human in¯uence. Altogether these gases are responsible for an increased radiative forcing ± de®ned as the perturbation of the Earth
radiative balance at the tropopause ± of about 2.5 W
mÿ2 [22]. This value may appear modest compared to
the mean absorbed solar radiation, which is about 240
W mÿ2 . But this 1% perturbation of the Earth energetics, although small in relative value, is able to bring
about important consequences. The diminution in the
*
Corresponding author. Tel.: +33-01-4427-8406; fax: +33-01-44276272.
incident solar radiation which might have caused the
XVIIth Century Little Ice Age was about half of this
value [38]. Moreover the anthropogenic greenhouse effect is expected to increase importantly in the future, as
greenhouse gases have generally a long residence time,
and tend to accumulate within the atmosphere. Due to
this long residence time, the greenhouse gases are also
well mixed within the atmosphere, and instead of being
considered individually, their eect is often summarized
through an equivalent-CO2 concentration. The hypothesis of an equivalent CO2 -doubling, which has been used
for some of the scenarios reviewed below, corresponds
roughly to a forcing of 4 W mÿ2 [8] and may be attained
during the ®rst part of the next century [21,23], irrespective of the reductions in the greenhouse gas emissions which are presently considered.
Evaluating the possible impacts of this anthropogenic
greenhouse forcing is therefore of immediate concern.
But model predictions are not free from uncertainties.
Although all models coincide in that they show a signi®cant change of the climate system to the anthropogenic forcing, a signi®cant divergence also appears in the
quanti®cation or geographical distribution of these impacts. This re¯ects the very subtle balance between opposite feedback processes which control the climate
system. In Section 2 we review a few model experiments
which show how eective this control is. We then review
some of the methods which are available to validate the
0309-1708/99/$ - see front matter Ó 1999 Elsevier Science Ltd. All rights reserved.
PII: S 0 3 0 9 - 1 7 0 8 ( 9 9 ) 0 0 0 1 6 - 0
122
H. l Treut / Advances in Water Resources 23 (1999) 121±131
models, focusing in Section 3 on the use of contemporaneous satellite data, and concluding in Section 4 with
the use of past data, in particular over the last century.
2. The climate response to anthropogenic forcing: global
features
2.1. Generalities
Many model simulations of the climate response to
an anthropogenic forcing have used atmospheric General Circulation Models (GCM) coupled to simple slab
ocean representations.
GCMs use the Navier±Stokes equations to describe
the general motion of the atmosphere over the globe. In
addition to the components of the wind, the models also
predict the pressure and temperature ®eld, and hydrological or surface variables, such as atmospheric water
vapour and cloud water content, or soil moisture estimate and snow cover. The equations are solved over
discretization grids whose horizontal resolution varies
strongly from model to model, from a grid size of about
500 km for coarser models, to a grid size of about 50 km,
for the higher resolution models used for weather forecast. The lack of representation of the smaller spatial
scales is therefore always a ®rst limitation of the GCMs.
The actual numerical solving of the equations may be
done in a spectral domain, or through ®nite dierencing.
The number of vertical levels may vary from about 10 to
30. The AMIP experiment [16] has provided an exhaustive review of the models currently available.
Whereas for weather forecast applications, the speci®cation of the initial atmospheric state from which the
model is run is very obviously of utmost importance,
this is no longer true for climatic applications. In this
case one is mostly interested in the statistical behaviour
of the atmosphere over long periods of time, which is
primarily controlled by the energetics of the system. All
models include a representation of the radiative transfer
in the solar and terrestrial domains, of the energy exchanges with the surface, of the main atmospheric hydrological features, such as latent heat release within
clouds, or cloud/radiation interaction. An accurate and
balanced representation of those energy and water
sources and sinks is of speci®c importance for climatological studies.
Most of these physical processes, however, correspond to unresolved spatial scales: the energy exchanges
over continental surfaces are controlled by the vegetation cover, and by motions in the boundary layer which
are organized at the scale of about 100 m; the tropical
convection is one of the main sources of energy for the
atmosphere, but corresponds to motions organized primarily at the scale of a few kilometers. All those processes need to be represented in a simpli®ed,
parametrical manner in the GCMs. But there is a large
variety of possible approaches to these parameterization
problems, a situation which is responsible for the large
number of existing climate models (about 30 groups
have participated in the AMIP project).
For climate sensitivity experiments, the role of the
ocean component is also crucial. Climate change can
occur and organize itself over long periods of time essentially because of the thermic inertia of the ocean.
There is a whole hierarchy of ocean models used for
climate studies. Slab ocean models constitute one of the
simplest approaches, in which the ocean passively stores
heat in a slab layer of about 50 m, with no representation of the changes in the ocean vertical and horizontal
energy transport. These models can describe the equilibrium response of the atmosphere/surface ocean system to prescribed changes in the climate forcing. They
cannot take into account the eects of ocean dynamics ±
which are represented in the newer generation of coupled models using ocean general circulation models. But
comparison between those two approaches [35,36] has
shown that, if the equilibrium response fails to represent
the patterns which are associated with a slower ocean
heating, particularly in the regions of deep water formation around Antarctica or in the Norwegian Sea, it
nevertheless constitutes a good approximation of the
climate perturbation in most areas. These simpler
models are also very precious, because they isolate the
contribution of the atmosphere in the climate response
to an anthropogenic forcing, and therefore the contribution of the atmosphere to current uncertainties in our
evaluation of future climate changes.
This crucial role of the atmosphere has been evidenced in many studies, perhaps most spectacularly by
the recent comparisons of the climate response to CO2
and aerosol increase. The motivation of those studies
was primarily to understand the climate variations
throughout the XXth Century, during which, in addition to greenhouse forcing, other radiative perturbations
such as those due to aerosols cannot be neglected
[27,14,39]. But, as some of these simulations consider
separately the impact of the greenhouse and aerosol
perturbations, using the same model [49,42,11,29,30],
they also provide useful information on the climate response to rather dierent perturbations. The CO2 forcing is distributed almost uniformly over the globe. The
aerosol forcing on the contrary is very unevenly distributed with a maximum over the continents of the
Northern Hemisphere, as shown by the sulphate aerosol
distribution for present and preindustrial conditions
[26]. Also, the aerosol negative forcing is due to a change
in solar re¯ection, either directly when solar radiations
are scattered by the aerosols, or indirectly, when the
aerosols change the size and density of the cloud droplets. The aerosol impact is therefore correspondingly
stronger in summer.
H. l Treut / Advances in Water Resources 23 (1999) 121±131
2.2. Examples using the LMD GCM
In the following we use results obtained with the
LMD (Laboratoire de Meteorologie Dynamique)
GCM. The ®rst version of the model was developed by
Sadourny and Laval [44]. Since then, the model has
evolved continuously, but some of its original features
are unchanged: the model uses a ®nite dierence discretization of the Navier±Stokes equations over an Arakawa C-grid. In the versions considered in the present
paper, the horizontal grid is regular in longitude (with a
number of points ranging from 48 to 96 depending on
the model versions) and in sine of the latitude (with a
number of points ranging from 36 to 72). The vertical
coordinate is the pressure normalized by its surface
value (r coordinate) and the number of vertical levels
varies from 11 to 19 depending on model version.
In addition to this treatment of the dynamical equations, the model includes a comprehensive representation of the ``physical'' processes: subgrid-scale processes,
radiative transfer, hydrological features and exchanges
with the surface. In the examples which follow, the
LMD Cycle 4 version is being used [28]. The shortwave
(solar) radiation transfer is parameterized using a
modi®ed version of Fouquart and Bonnel [15] where
two spectral bands corresponding to the visible and
near-infrared are distinguished. In the longwave (terrestrial) part of the spectrum, the scheme developed by
Morcrette [37] is used and six spectral bands are considered. The treatment of convection is still the original
one, where a moist adjustment is combined with a
scheme derived from the Kuo [25] parameterization. A
diusive approach is used to represent vertical mixing
within the atmospheric boundary layer. The treatment
of the surface conditions, although comprehensive, is
rather simple, with soil moisture being treated following
a single bucket approach: the inclusion of a more advanced scheme including the eects of vegetation has
been considered in LMD Cycles 5 and 6 only. This could
be problematic if we were to discuss regional impacts.
The treatment of clouds is comparatively more advanced; a prognostic cloud water budget equation is
included in the model, with a corresponding parameterization of the source and sink terms: condensation,
evaporation, conversion to precipitable water.
The results of simulations testing the response of the
LMD GCM to CO2 and aerosol forcing are shown in
Fig. 1. The response to the two perturbations are ®rst
considered separately, a third diagram showing their
combined eect. The representation of the sulphate effect within the LMD GCM, which involve both the direct and indirect eects, as de®ned above, gives a global
forcing of about ÿ1.2 W mÿ2 , which happens to be
approximately similar in amplitude but opposite in sign
to the CO2 forcing since the beginning of the industrial
era. A striking feature is the symmetry between the two
123
responses to sulphate aerosol and CO2 . In both cases the
surface temperature change is characterized by an ampli®cation over the Polar regions and over the continental areas. In a latitude±altitude zonal mean section
(Fig. 2), one can also recognize a well-known feature of
the model response [46], which provides part of the explanation for this polar ampli®cation: at high or middle
latitudes, the temperature change is larger near the
ground, whereas at low latitudes, it reaches its maximum
at about 12±15 km. This latter eect has been attributed
for a long time to the convective activity of the low
latitude regions [46]. At the same time the stratosphere
responds with a cooling (in the case of a CO2 -induced
tropospheric warming) or a warming (in the case of an
aerosol-induced tropospheric cooling). Such a stratospheric response, in the case of the aerosol forcing, can
be the consequence of internal atmospheric feedbacks
only, and re¯ects in particular the change in water vapour associated with climate cooling. Of course, the last
panel of Fig. 1, where both the CO2 and sulphate
aerosol eects are imposed on the climate system, shows
the limit of this symmetry between the response to the
two forcings. In this case (which is largely an academic
one since the role of the other greenhouse gases and
aerosols has been ignored), the Northern Hemisphere
(NH) is cooling whereas the Southern Hemisphere (SH)
is warming. This eect has been invoked to explain the
slower warming of the Northern Hemisphere throughout the century [45]. But even in this case, each of the
Hemispheres shows a very speci®c spatial pattern with
an enhancement of both the NH cooling and the SH
warming at high latitudes and over continental areas.
Our results indicate that the response to any form of
pollution is largely non-local. This is important politically, because the countries responsible for the pollution
may not be those who suer the most from its consequences, and also for the detection of the ®rst signs of a
climate change, because they will not be related in a
simple manner to the forcing.
This global organization of the response also re¯ects
the importance of the atmospheric control on the climate. Another aspect of this control is evidenced by
Fig. 3, again from results of the LMD GCM [30], where
the global surface temperature changes from a series of
sensitivity experiments to dierent forcings, when plotted against changes in the global radiative forcing, tend
to line along a unique curve which describes the model
sensitivity ± incidently larger for colder climates ± and
depends very little on the nature and distribution of the
forcing. The forcings considered here include: a doubling of the atmospheric CO2 concentration ± two sets
of experiments ± a solar constant increase, and increases
since the beginning of the industrial era of respectively,
the CO2 concentration, the sulphate aerosols, and the
tropospheric ozone. All those experiments are described
in [28,30], from which Fig. 3 is taken. Ramstein et al.
124
H. l Treut / Advances in Water Resources 23 (1999) 121±131
Fig. 1. The surface temperature response of the LMD GCM, coupled to a simple slab ocean model, to a radiative forcing corresponding to: (a) the
CO2 increase since the beginning of the industrial era; (b) the sulphate aerosol increase for the same period (direct and indirect eects); (c) the sum of
the two forcings (from [30]) (See text for comments).
[40] have shown that the response to the condition of the
Last Glacial Maximum can be qualitatively dierent,
probably because of the strong modi®cation of the Pole
to equator gradient of temperature characterizing this
period. But the atmospheric feedback eects appear to
exert a strong control not only on the general geographical pattern of any climate change, but also on its
amplitude.
Unfortunately, if, for a given model, the response of
the climate system to an external perturbation seems
well behaved, the involved feedback eects are very
dicult to simulate accurately, and the response is very
model-dependent. It is well known for example that the
equilibrium temperature response to a doubling of the
CO2 , may range from 1.9 to 5.3 degrees [47]. The regional distribution of the climate change is also a delicate issue. On one side the geographical distribution of
the temperature and precipitation changes associated
with a CO2 doubling, displayed for 3 dierent models by
the ®rst IPCC report [21], or for 8 models as part of a
H. l Treut / Advances in Water Resources 23 (1999) 121±131
125
Fig. 3. Summary of equilibrium sensitivity experiments carried out
with the LMD GCM Cycle 4, coupled to a slab ocean. These experiments are described in [38,28,30]. As indicated by the legend they include sensitivity experiments to a change in the solar constant, to a
doubling of the CO2 , and to changes in CO2 , aerosols, or tropospheric
ozone concentration from preindustrial to present conditions. The plot
gives the mean global surface temperature response (in degrees) as a
function of the mean global radiative forcing (in W mÿ2 ). Regardless of
the geographical distribution of the forcing, the points tend to line
along a curve whose slope de®nes a global `climate sensitivity', which
appears larger for colder climate.
3. The main feedback processes and their validation
through satellite data
Fig. 2. Changes in the altitude/latitude distribution of the temperature
simulated by the LMD GCM, coupled to a simple slab ocean model
and corresponding to: (a) the CO2 increase since the beginning of the
industrial era; (b) the sulphate aerosol increase for the same period
(direct and indirect eects); (c) the sum of the two forcings (from [30])
(See text for comments).
more recent intercomparison held within the framework
of CLIVAR (McAvaney and Le Treut et al., 1998,
personal communication), reveals some general consistency at a very large scale, with an ampli®cation of the
surface warming over the polar regions, over the continents and in winter, and with a general increase in the
precipitation, both in the equatorial and mid-latitude
regions. On the other side, the regional response diers
largely from one model to the other: in particular some
models show a displacement of the precipitation zones,
and associated risks of drought, which are not con®rmed by other simulations.
The main feedback eects which aect the climate
response to anthropogenic perturbations have been
identi®ed for a long time (see for example the review of
Schlesinger and Mitchell [46]). The role of the atmosphere was stressed in the preceding paragraph, but
oceanic, biochemical or chemical processes are also
important. The representation of all those eects within
climate models is subject to considerable uncertainty.
The purpose of the present section is to show that
each of these feedbacks may be and must be studied
individually, if one wishes to quantify the domain of
uncertainties associated with the estimation of future
climate changes. We focus on the water vapour and
cloud feedbacks, because they are probably the processes which respond more directly to any climate
forcing, and are related to the changes in precipitation
which are also discussed. They have also been the subject of many studies, triggered in particular by the ®rst
model intercomparisons of Cess et al. [7].
3.1. Water-vapour feedbacks
The water vapour eect may appear simple in essence: as the climate gets warmer, the saturation value of
the atmospheric water vapour concentration increases.
In all models this translates into an increase in the water
vapour itself, which increases the greenhouse eect, and
almost doubles the climate response [21]. The accuracy
with which models simulate this change in water vapour
126
H. l Treut / Advances in Water Resources 23 (1999) 121±131
is of course dependent on the model ability to control
eciently the relative humidity of the atmosphere, and
in particular the contrast between the very humid regions near the InterTropical Convergence Zone (ITCZ)
and the very dry areas of the subtropical areas, in the
descending part of the Hadley±Walker cells. It is also
linked to the eciency of the convective parameterizations, which contribute to extend this increase in humidity to the higher levels of the troposphere, in low
latitude regions. The data that can be used to check the
simulated variations of the water vapour content are all
subject to limitations:
(i) the radiosonde data extend over several decades,
but their spatial coverage is limited. The quality of
the data as one gets higher into the atmosphere
may also be questioned [18,17]. Also their quality
may have varied from decade to decade.
(ii) the satellite data cover a restricted period of
about a decade. They provide indirect measurements of the radiative eect of water vapour, in different spectral bands, and need to be interpreted
with care. Indications on the behaviour of the water
vapour within the atmosphere may be obtained
from the clear-sky longwave measurements of Earth
Radiation Budget Experiment (ERBE), from microwave radiometers such as Special Sensor Microwave
Imager (SSMI) (over the oceans only), from the vertical pro®lers such as Tiros-N Operational Vertical
Sounder (TOVS), or from speci®c infrared channels
such as the Meteosat water vapour channel.
Those data are enough to reveal some systematic
errors of the models. The LMD GCM for example is
both too cold and too dry in the higher troposphere [2].
But we also want to use them in order to assess the
strength of the atmospheric water vapour feedbacks,
which means to diagnose the derivative of the water
vapour when the climate (and therefore the surface
temperature) changes. This is a more complex problem:
the only observed climate changes are the seasonal
variations, or interannual ¯uctuations such as the opposition between El Nino and La Nina conditions in
87±88, for which a complete set of satellite measurements is available, and the patterns associated with
those ``short-term'' ¯uctuations are very dierent from
those which characterize the long-term climate evolutions. The water vapour feedbacks are correspondingly
dierent. For example the seasonal changes of water
vapour over the oceans, as may be analysed from the
SSMI data [3], depend strongly on the changes of the
vertical gradients of temperature: over the oceans the
seasonal changes of temperature are smaller at the
surface, due to ocean inertia, than at higher altitudes,
where the in¯uence of the continents is being felt more
strongly. As a consequence the greenhouse eect may in
some case diminish with increasing surface temperature, because the stronger longwave emission from the
higher and warmer atmospheric layers dominate the
increased water vapour absorption. This eect is
faithfully reproduced by models and must not in any
case be interpreted as a negative water vapour feedback, as could be from a hasty interpretation. It merely
re¯ects the complexity of the seasonal response. In
general, in spite of some quantitative dierences the
models reproduce correctly the seasonal cycle or interannual ¯uctuations of the clear-sky greenhouse eect
[4]. The results of Roca et al. [41], from satellite measurements in the Meteosat water vapour channel, also
show the ability of the models to successfully reproduce
the negative correlation between the surface of the ascending and descending branches of the Hadley-Walker
circulation, measured in monthly averages throughout
the seasonal cycle. All those features add some credibility to the capacity of the models to simulate the
water vapour feedbacks in scenarios of future climate
changes.
But ultimately no perfect validation is yet possible. In
particular the radiative eect of the water vapour
changes depend on the changes of the vertical stability
of the atmosphere, which are very dierent at the seasonal or interannual time scale, or for climate sensitivity
experiments. This is illustrated in Fig. 4. The sensitivity
of the clear-sky greenhouse eect to surface temperature
is diagnosed from the output of the LMD GCM, using
the GCM radiative code in o-line mode. The sensitivity
at the seasonal and interannual scales have been veri®ed
using observed data, and the model is in good qualitative agreement with these observations. The very large
dierences between the dierent cases, illustrated in the
upper panel, are reduced when the o-line computations
are carried out with a ®xed relative humidity and a ®xed
temperature lapse rate. The sensitivity value of 2 W mÿ2
Kÿ1 , is characterizing the water vapour feedback in
climate scenarios, and it corresponds to a weak perturbation of the atmospheric vertical strati®cation in
temperature and humidity. That such a weak change
should characterize a modi®ed climate is however a
model prediction that cannot be veri®ed from observations.
Lindzen [32] has proposed a mechanism of model
error which has been the source of many debates and
may be summarized as follows: if the increase in water
vapour in the moist ascending regions is accompanied
with a decrease in the drier descending regions, the latter
eect could be dominant because a change of water
vapour water content in a dry area has more radiative
impact. This could in principle constitute a negative
feedback eect that models might misrepresent because
of their inability to represent correctly the contrast between the very dry subtropics, and the moist convective
regions. There are no model results, nor observational
records to fully support such a mechanism, but it is also
impossible to rule it out completely.
H. l Treut / Advances in Water Resources 23 (1999) 121±131
Fig. 4. Sensitivity of the clear-sky longwave outgoing ¯ux to sea-surface temperature (SST) (from [4]). It is computed using dierent
modi®cations of the climate to de®ne the SST perturbation: seasonal
cycle, interannual variations, and two climate warming experiments
using the LMD GCM (sensitivity to solar constant and CO2 doubling).
The diagnostics are carried out over the oceans from the output of the
LMD GCM and the results are plotted as a function of the mean SST.
In the lower panels the same o-line diagnostics have been carried out
while keeping unchanged either the relative alone in the climate perturbation (b) or the both the relative humidity and the temperature
lapse-rate (c). This indicates that the successful prediction of the small
time scales by the model is a strong test, because those scales have a
complex behaviour.
3.2. Cloud feedbacks
The largest uncertainty as regards the evolution of
future climate is probably the behaviour of clouds.
Cloud feedbacks include a wide range of eects which
have been discussed over the years. The eect of cloud
altitude, for example, has been described by Stephen and
Webster [48], who have illustrated through a simple
127
model that an increase in low cloudiness is dominated by
the eect of cloud albedo, and contributes to a climate
cooling, whereas an increase in high cloudiness, is
dominated by the cloud greenhouse eect and contributes to a climate warming. But they have also shown
that changes in cloud optical properties have to be
considered simultaneously. For a low cloud whose eect
in the infrared is already saturated, an increase in water
content results in an increased albedo eect and therefore a cooling, whereas for high clouds the competition
between the cloud albedo and the cloud greenhouse effect is more uncertain. All those eects have been recognized as essential since the ®rst model studies of the
greenhouse eect [34].
Since then, new processes have emerged which have
added even more to the complexity of the problem. In
particular the importance of the microphysical structure
of the clouds has been recognized. First the size of the
hydrometeors has a great importance for the scattering
of solar radiation: for the same cloud water content, a
dimininution of the droplet size increases both the
number of droplets and the surface which they cover.
This eect is responsible for the sulphate aerosol indirect
eect, but may also be aected by natural processes,
such as the ocean biology which produces di-methylsulphate [9]. The transition between ice and liquid
phases is another microphysical process of very large
importance. Liquid water clouds tend to precipitate
more eciently, but only when a certain threshold
necessary for an ecient coalescence of cloud droplets is
attained. Senior and Mitchell [47] have demonstrated
that a global warming could then be damped by the
transformation of ice clouds into more re¯ective liquid
water clouds. Li and Le Treut [31] have shown that the
choice of the temperature range throughout which the
liquid/ice transition takes place may aect the sign of
this radiative feedback.
Most of these processes have slowly been integrated
into models and a number of qualitative features are
now well understood. For a CO2 increase, in most cases,
the models show a decrease of the cloudiness in the low
and middle troposphere and an increase in the upper
troposphere (results of the LMD GCM are shown in
Fig. 5 as an example). This partly re¯ects the fact that,
as the water vapour saturation level increases with increasing temperature in the lower troposphere, it becomes more dicult to reach saturation and form a
cloud through water vapour condensation. This low
level cloudiness decrease is therefore by no way contradictory to the increase in the water vapour concentration noted above. The increase in high cloudiness
proceeds from the reverse mechanism and is also associated with a higher altitude of the tropopause level. In
the ITCZ, in addition, most models show an increase in
convective clouds. This eect can be easily understood:
although the smaller Pole-to-Equator temperature
128
H. l Treut / Advances in Water Resources 23 (1999) 121±131
Fig. 5. The changes in the mean zonal cloudiness (in percents) associated with a CO2 increase from preindustrial to present condition
(from [30]).
gradients associated with a warmer climate generally tend
to slow the Hadley cell meridional circulation [1,43,38],
the low-level convergence of both warmer and moister
air creates more favourable conditions for convection.
Finally a last feature is shown by most models, at least
those including a physical representation of cloud formation: cloud fraction and cloud liquid water content
increase at the liquid/ice phase transition, for a warmer
climate. This eect is due to the very dierent microphysical properties of liquid water and of ice clouds.
The mechanisms which contribute to cloud modi®cation are also very largely the ones that are responsible
for rain modi®cations. The increase in equatorial convective cloudiness is accompanied by a corresponding
increase in equatorial rain. At mid-latitudes the transport of water vapour, depends on the latitudinal gradient of humidity, which is dominated by the exponential
increase in the saturation level of water vapour, following the Clausius±Clapeyron law.
The combination of these dierent processes, in spite
of the qualitative convergence of the model simulations,
leads to a very large scatter in the quantitative radiative
eect. This, again, raises the problem of validation.
As for water vapour, two types of data sets can be
used.
(i) Cloudiness data from conventional in situ measurements at weather stations. Such data have been
gathered through a very long eort by Warren et al.
[51]. Henderson-Sellers [20] has shown some longterm trends in cloud data, which may relate to climate change.
(ii) Satellite data, and most notably the ISCCP climatology (International Cloud Satellite Climatology Project) which was developed speci®cally for
the purpose of model validation and covers the
whole period from July 1983 up to now. A large variety of other instruments give a relevant information about clouds. One should perhaps give a
special mention to broad-band measurements such
as the ERBE measurements, which provide some access to the cloud radiative impact. Also, the cloud
water content is measured through microwave radiometers such as the SSMI one, but the uncertainty
of the retrieval is very large: the annual mean over
the oceans is 0.081 kg mÿ2 in the estimate of Greenwald et al. [19], compared to 0.059 kg mÿ2 in the estimate of Weng and Grody [52].
An interesting and early example of how those data
may be used to point out possible errors in the design of
models can be found in the work of Tselioudis et al. [50].
They have used correlations between cloud optical
thickness and cloud temperature to show that empirical
relations where cloud condensed water content increases
with temperature may be wrong in many situations and
may introduce arti®cial feedbacks in the model. Other
examples [12,13] show how useful the study of correlations between parameters may be to validate the models.
But again an important diculty comes from the peculiarities of the seasonal and interannual changes to
which observed data give access: at these time scales
cloud changes are both due to large displacements of the
Fig. 6. Derivation of cloud properties with respect to SST (plotted as a
function of mean SST) (from [5]). The diagnostics are carried out over
the oceans and results are plotted as a function of the mean SST. The
information from independent observations (ERBE longwave and
shortwave forcing, ISCCP retrievals of the cloud fraction, cloud top
pressure and cloud optical properties, TOVS retrieval of the cloud
fraction) is very consistent. The dotted curves correspond to a restriction of the correlation to changes characterized by a weak modi®cation of the dynamics (referred to as Case III), de®ned using the
NCEP or DAO reanalysis of the atmospheric circulation. These diagnostics provides a very powerful constraint on the models.
H. l Treut / Advances in Water Resources 23 (1999) 121±131
meteorological patterns, and to thermodynamical feedbacks such as those relevant to study a global warming.
Bony et al. [5] show a method to separate those eects:
when studying the regression between dierent cloud
parameters they stratify the relation using the vertical
velocity as an index of the circulation and its changes
(Fig. 6). The consistency of the results when they consider dierent cloud parameters, and therefore dierent
satellite instruments, is a good indication of their relevance for model validation.
4. Other approaches to model validation
The reference to past climates oers other possibilities
to evaluate the models. We review them brie¯y in this
last section. In all cases these methods allow a better
insight into the qualitative behaviour of the climate
system, but also bring new elements of quantitative
uncertainty (linked for example to the measure of past
SSTs, of past radiative forcing). Also, the atmospheric
processes can only be considered indirectly.
For long time scales, one may consider the climate
evolution over the last glacial cycle [33] as a way to
determine a climate sensitivity: both the forcings (astronomical changes of the insolation, greenhouse gases
concentration) and the SST evolutions are known from
astronomical calculations and ice or deep-sea records.
Alternatively one may also reconstruct climate extrema,
such as the last glacial maximum (21 000 yr Before
Present), or the warmer conditions of the Holocene
(6000 yr Before Present): this is in particular the objective of the PMIP programme [24].
But the near past is also an important reference period for the models. Whether the global temperature
increase of about 0.6°C since the beginning of the industrial area constitutes a ®rst sign of the warming to
come, or is due to natural ¯uctuations of the climate, is a
matter of debate [23]. To interpret the changes that occurred since the beginning of the industrial area, however,
one has to add ± or substract ± the eect of at least two
other anthropogenic perturbations: the changes in ozone
chemistry and the increased aerosol loading of the atmosphere. A characteristic feature of both ozone and
aerosols is that they have a short life within the atmosphere, and, as a result, are very unevenly distributed.
Ozone is principally formed in the stratosphere, through
speci®c photochemistry, whose perturbation by CFC
leads to an ``ozone hole'' mostly apparent over Antarctica
during the Southern Hemisphere Spring, and also to a
weaker diminution of stratospheric ozone at all latitudes.
This stratospheric depletion causes a negative perturbation of the atmospheric system (of the order of 0.2 W mÿ2
± from IPCC [23]. But ozone is also formed in the lower
layers of the atmosphere, though the transformation of
nitrous oxides (NOx ) in the presence of hydrocarbons
129
such as methane. This tropospheric ozone formation,
which depends upon temperature and is felt strongly
during the Northern Hemisphere summer, over the continental areas, causes a positive forcing of the climate
system, whose present estimation is about 0.3 W mÿ2 [23].
Aerosols are also largely released over the Northern
Hemisphere continents (although this image may be
biased because the aerosols taken into account so far in
climate simulations are sulphate aerosols: aerosols from
biomass burning, for example, have a very dierent
distribution). Their main impact is to cool the climate
system by increasing the re¯ection of solar radiation,
both directly by Mie scattering, or indirectly because
they contribute to the nucleation of cloud droplets,
which are then more numerous, and re¯ect the solar
radiation more eectively (for a given amount of cloud
water) [10]. Smaller droplets also diminish the eciency
of precipitation and lead to thicker clouds. A considerable uncertainty aects our estimations of the negative
aerosol forcing since the beginning of the industrial era:
it is known with a factor 2 or 3 at best, but might be
important, under ÿ1 W mÿ2 [22,6,30].
The history of the climate over the last century, as can
be reconstructed by models is therefore the product of
an uncertain forcing by an uncertain climate sensitivity.
Many processes are generally ignored in the models: the
possible non-linear response of the ocean circulation,
which has been observed in the past and is beyond the
reach of present models, because they do not represent
the dynamics of continental glaciers; the possible release
of methane from the permafrost; the role of solar ¯uctuations, of volcanic eruptions. As in the case of the
atmospheric feedbacks discussed above, the progress of
our understanding will most certainly reduce those uncertainties.
5. Conclusions
If the eventuality of an anthropogenic climate change
cannot be questioned, it is doubtful that the climate
system may ever be completely predictable, in view of its
incredible complexity. The examples of water vapour
and cloud feedbacks given in the present paper concern
the role of the atmosphere only, which is already responsible for a large uncertainty. The role of the continental hydrology, of the vegetation, of the oceans, of the
ice sheets, of the ocean biochemistry, of the atmospheric
chemistry have all been overlooked in current GCMs.
The application of scenarios at the local scale must
therefore be considered as some exercise of risk analysis.
At the same time the results reviewed here show that we
have now enough data to constrain more eciently the
models than is usually done, and modellers should
progressively be in a position to de®ne more precisely
the uncertainties attached to their scenarios. This
130
H. l Treut / Advances in Water Resources 23 (1999) 121±131
approach, which is slow and unglamorous, may nevertheless constitute the main source of information towards more useable scenarios.
Acknowledgements
As evidenced by the citations in the text, this review
owes a lot to discussion with, and work from S. Bony,
Z.X. Li and J.P. Durel.
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