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Proc Natl Acad Sci U S A. 1997 August 5; 94(16): 8335–8342. | PMCID: PMC33750 |
Copyright © 1997, The National Academy of Sciences of the USA Can increasing carbon dioxide cause climate  change? Richard S. Lindzen Building 54, Room 1720, Massachusetts Institute of Technology, Cambridge, MA 02139 The realistic physical functioning of the greenhouse effect is
reviewed, and the role of dynamic transport and water vapor is
identified. Model errors and uncertainties are quantitatively compared
with the forcing due to doubling CO2, and they are shown to
be too large for reliable model evaluations of climate sensitivities.
The possibility of directly measuring climate sensitivity is reviewed.
A direct approach using satellite data to relate changes in globally
averaged radiative flux changes at the top of the atmosphere to
naturally occurring changes in global mean temperature is described.
Indirect approaches to evaluating climate sensitivity involving the
response to volcanic eruptions and Eocene climate change are also
described. Finally, it is explained how, in principle, a climate that
is insensitive to gross radiative forcing as produced by doubling
CO2 might still be able to undergo major changes of the
sort associated with ice ages and equable climates. Keywords: global warming, climate sensitivity, climate
modeling, greenhouse effect The title suggested for this paper (by Dave Keeling) is
tantalizing for its ambiguity. At some level, the answer is
philosophically trivial. After all, our knowledge is rarely so perfect
that we can say anything is absolutely impossible. In connection with
this question we can go a bit further, and state that increasing
CO2 is likely to cause some climate change, and that the
resulting change will involve average warming of the earth. However,
this answer is almost as trivial as the first. The climate is always
undergoing change, and if the changes due to increasing CO2
are smaller than the natural variability, then these changes will be of
only modest concern except as an exercise in weak signal detection. The
more serious question then is do we expect increasing CO2
to produce sufficiently large changes in climate so as to be clearly
discernible and of consequence for the affairs of humans and the
ecosystem of which we are part. This is the question I propose to
approach in this paper. I will first consider the question of whether
current model predictions are likely to be credible. We will see why
this is unlikely at best. I will then show how we might estimate and
bound climate sensitivity both directly and indirectly from existing
data. Finally, I will consider the relationship of changes in mean
temperature to changes in the structure of climate. It has been
suggested that small changes in mean temperature are important because
major changes in past climate were associated with major changes in the
equator-to-pole temperature difference, but only small changes in the
mean temperature. I will argue that the changes in mean temperature may
be only residuals of the changes in the meridional temperature
distribution rather than the cause. Current Forecasts Present projections of the climatic effects of increasing
CO 2 are based on models of varying degrees of complexity.
The relative similarity of all these predictions for the increase
in global mean temperature has lent a degree of plausibility
to the resulting predictions. We shall, in this section, analyze the
nature of these “traditional” results to understand what the
physical basis is for the common prediction. In the following section
we will examine some of the processes crucial to these predictions to
see whether they are known to sufficient accuracy for the purpose of
climate predictions. Before doing this, it will be necessary to briefly
review the physics of the “greenhouse effect.” Although this
process is usually summarized by the assertion that infrared-absorbing
gases inhibit the ability of the earth’s surface to emit thermal
radiation, and thus force the surface to get warmer, the reality is
substantially more complex. Möller and Manabe ( 1) made an early
start toward understanding this matter. In this one-dimensional study,
both radiative and radiative–convective equilibria were calculated
using assumed distributions for humidity and cloudiness. The simplistic
picture corresponds essentially to radiative equilibrium, for which
Möller and Manabe calculated the equilibrium temperature of the
surface to be about 350 K, which is 95 K warmer than the black-body
temperature of 255 K. When convection is included by introducing a
simple convective adjustment, the surface temperature comes down to the
observed value of 288 K. Convective adjustment reduced the greenhouse
effect by about 75%, by allowing for the fact that radiation is not
the only form of heat transfer in the atmosphere. When infrared opacity
is high, evaporation and mechanical transport are more efficient ways
for the surface to cool. Lindzen ( 2) offered a more complete schematic
of the realistic operation of the natural greenhouse effect. One begins
by recognizing that water vapor, the atmosphere’s main greenhouse gas,
decreases in density rapidly with both height and latitude. Surface
radiative cooling in the tropics, which has the highest concentration
of water vapor, is negligible. Heat from the tropical surface is
carried upward by cumulus convection and poleward by the Hadley
circulation and planetary-scale eddies to points where radiation can
more efficiently transport the heat to space. Where radiation can more
efficiently carry the heat depends on the radiative opacity and the
motions themselves. In point of fact, without knowing the dynamical
heat fluxes, it is clear that one cannot even calculate the mean
temperature of the earth. It is interesting, in this regard, to look at
model intercomparisons of meridional heat flux, and their comparison
with observationally based estimates. An extensive study ( 3) shows that
such differences reach 2 PW (petawatts). As shall be noted later, this
is roughly equivalent to differences in vertical fluxes of about 25
W ![[center dot]](/corehtml/pmc/pmcents/middot.gif) m −2—much larger than the 4 W m −2
change that a doubling of CO 2 is expected to produce. A
particularly acute example of the problem with dynamic fluxes is
revealed when one couples models for the atmosphere with ocean models.
Here, the climate tends to drift unless one applies so-called flux
corrections. Examples of such corrections are given for all the leading
models ( 4). The corrections have to be applied on a
latitude-by-latitude basis, and the magnitude of the correction can be
as large as 100 W m −2. As can be understood from our
discussion of the realistic nature of the greenhouse effect, these
dynamic fluxes do not represent systematic biases independent of the
CO 2 forcing; rather they are essential to calculating the
response to increased CO 2. The issue is not that the
forcing due to CO 2 is buried within these larger
uncertainties, but rather whether we can reckon the response reliable. The role of water vapor is nonlinear. Assuming 80% relative humidity
in a 2-km boundary layer, and a fixed relative humidity above the
boundary layer, Fig. shows how, for a given
temperature distribution, outgoing long-wave radiative flux varies as
one perturbs the relative humidity above the boundary layer [Fig.
was calculated using the radiative transfer code ( 5); a similar
calculation appears in ref. 6]. One sees that the effect of a 5%
change in relative humidity depends on the base humidity being
perturbed. For low base humidities, a 5% change is associated with
about 5 W m −2. For high base humidities, the change
is about half of this. For purposes of comparison, the 4
W m −2, which a doubling of CO 2 is
expected to produce, is roughly equivalent to a 4–8% change in
relative humidity. Note that uncertainties in measurements of humidity
are on the order of 20% or more, though things appear to have improved
over the past 2 years. We shall look at the improved data soon.
However, it is again clear that we are dealing with uncertainties and
errors that are large compared with the climatic impact of
CO 2. Here too, these errors occur in a field that is
crucial to calculating the response to CO 2, since the water
vapor feedback is essentially responsible for the model predictions of
large warming due to increasing CO 2. Clearly, even
superficial agreement between observations and model-derived water
vapor would be inadequate to establish the model feedback.
This potentially important positive feedback was first identified by
Manabe and Wetherald ( 7). Using a simple one-dimensional
radiative–convective model, they found that assuming constant relative
humidity led to a significantly enhanced response to increased
CO 2 over what would have been obtained with fixed specific
humidity. The point, simply, is that with fixed relative humidity,
specific humidity must increase with warming. Upper-level water vapor
(above 2–3 km in the tropics) dominates the radiative role of water
vapor, despite the fact that most of the atmosphere’s water vapor is
found below 800 millibars [1 millibar (mb) = 100 Pa] ( 8). Of course,
given the nonlinearity of the radiative effect of water vapor, the
average radiative response to water vapor is not equal to the response
to an average water vapor, and, therefore, one-dimensional studies are
inappropriate. However, the results of the above one-dimensional
studies remain indicative of general properties. The most useful way of viewing feedbacks is by means of the formula
where fi is the ith feedback factor.
For fixed relative humidity, the water vapor feedback factor is about
0.4. This turns out to be much larger than the factors due to clouds
and snow in present models. However, as may be seen from the formula,
the addition of smaller factors on top of the 0.4 due to water vapor
rapidly increase the response. Without the water vapor feedback the
impact of model cloud and snow feedbacks would be small ( 2). It is worth reviewing the basis for the assumption of constant relative
humidity in ( 7). It is based on the crudely observed picture from ref.
9 reproduced in Fig. . It was argued in ( 7)
that the overall relative humidity varied only between about 30% and
50%, and that the pattern was similar for both winter and summer,
suggesting that the atmosphere was attempting to maintain a given
relative humidity regardless of temperature. There were, of course,
very few measurements available for ref. 9. However, subsequent
analyses of radiosonde data showed a fairly similar picture ( 10).
Unfortunately, the radiosonde data have proven extremely unreliable
( 11). In particular, radiosonde data tended to replace readings of very
low humidity with relative humidities of 20%. Nevertheless, these
primitive observations received a certain amount of credibility insofar
as they were consistent with humidities predicted in general
circulation models (GCMs). However, recently, the 183-GHz channel on
the SSM/T-2 satellite has provided detailed data on the global
distribution of relative humidity. Fig. shows
a global daily map for relative humidity between 500 and 300 mb for May
5, 1995. We see hugely more variability than was suggested in ref. 9.
We also see confined moist regions associated with active convection
and comparatively rapid transitions to extremely dry regions away from
the convection. Incidentally, this observation resolves a problem in
ref. 12, where, in studying the moisture budget of the tropical
troposphere, it was found that it was impossible to account for the
humidities observed by radiosondes in clear subsiding regions. The
satellite data show that these regions are, indeed, dry. Some
indication of why current models misrepresent the vertical distribution
of humidity is given in ref. 13, where the authors calculated the
correlations of interannual variability of humidity at various levels
with the variability at the surface for both traditional radiosonde
data and for the output of a Geophysical Fluid Dynamics Laboratory
(GFDL) GCM. The results are shown in Fig. . In
the data, upper-level humidity rapidly decorrelates from surface
humidity, while in the model all levels are highly correlated. This
strongly points to the likelihood of strong artificial coupling of
levels in this model. Judging from the results in ref. 14, similar
problems are likely in the Goddard Institute for Space Studies (GISS)
model, and they appear to be independent of the choice of convective
parameterization. To be sure, there are the already-mentioned problems
with radiosonde data which are discussed in detail in ref. 15. Current
radiosonde data are much better (though they still display a moist bias
in dry regions) and show the decoupling of water vapor behavior above
and below the trade inversion much better. Fig.
illustrates this. Models also show a tendency
to underestimate humidity in moist regions and to overestimate it in
dry regions ( 16).
There are potential problems with the vertical distribution of
temperature as well. For simple radiative convective models, the
vertical profile of temperature in the troposphere is essentially
fixed. Thus, the response to tropopause level forcing from doubled
CO 2 must consist in warming throughout the troposphere,
including the surface. In principle, warming at the top of the
troposphere (without warming at the surface) would be sufficient to
balance the forcing. Data indicate a significant degree of independence
for temperature changes at different levels ( 17). Of course, GCMs do
not explicitly assume rigid vertical coupling of temperature in the
troposphere; however, it is possible that coupling is stronger than in
nature. The above-described problems with heat fluxes and humidity, as well as
the potential problems with vertical structure of temperature, all
serve to render model feedbacks extremely uncertain. In view of these
problems, it is important to consider whether there are alternative
approaches to determining climate sensitivity. Observational Determinations of Climate Sensitivity The purpose of the present section is to assess various approaches
to using data to infer climate sensitivity, given that current GCMs are
unlikely to be adequate for this task. Direct Approach. As already noted, a doubling of
CO 2 is generally taken to imply a forcing at the tropopause
of about 4 W m −2. The question of climate sensitivity
amounts to asking how much must the earth’s surface warm to compensate
for this forcing. A simplistic approach to the question of climate
sensitivity would be to study the temporal variation of globally
integrated OLR with varying globally averaged temperature. The ratio of
the temperature variations to the variations in OLR would represent the
climate sensitivity. However, a priori, naturally occurring
changes in global mean temperature on time scales of from weeks to
years may not form proper surrogates for warming due to increased
CO 2 ( 18). Another problem with this approach is that OLR is
not the sole contributor to the radiative response. In principle, we
should look at the change in total radiative flux at tropopause levels.
For the tropics, however, OLR in clear sky regions appears to be the
dominant contributor to the total flux change ( 19). Still another part
of the problem is that naturally occurring changes in mean temperature
on these time scales are significantly associated with changing
regional patterns of warming rather than global warming ( 20). Insofar
as the water vapor feedback is involved in climate sensitivity, Fig.
shows that moisture changes in dry regions are much more important than
changes in moist regions. A global change involving an intensification
or reduction of existing differences between moist and dry regions can
lead to a change in OLR even in the absence of change in mean
temperature. It will clearly be necessary to distinguish such changes
from those specifically associated with changes in the mean
temperature. It should be noted that changing patterns can be
associated with changes in circulation and changes in temperature, both
of which play a role in the moisture budget ( 12). Fig. , in fact,
suggests the interesting possibility that the primary feedback process
might consist in the change in areal coverage of the very dry regions.
Presumably, natural variations include a full range of such
possibilities so that observed ratios of average temperature variations
to variations in total OLR would show a significant scatter. A primary
problem associated with the direct measurement of climate sensitivity
will be to distinguish changes in flux associated with changes in mean
temperature from those associated with pattern changes not associated
with changes in the mean temperature. There is, moreover, no assurance
that all changes in mean temperature will be appropriate surrogates for
global warming. The question of the sensitivity of tropical temperature is an important
matter in its own right. In particular, the tropics have distinctly
different basic physical balances from those in the extratropics ( 21).
Tropical sensitivity is also an important factor in global sensitivity.
GCM results characteristically indicate no special difference between
tropical and extratropical sensitivity to a doubling of
CO 2. This is seen in Fig. .
Although there is enhanced response at polar latitudes, the response is
relatively flat from the equator to about 40°. While there are
reasons to suppose that the model response in the tropics is excessive,
this has been widely argued about and is not essential to the present
discussion; it will, however, be important for the discussion in the
next section. What is relevant here is that the changing tropical
sensitivity has a profound effect on the response to increased
CO 2 globally. In calculations performed with the Center for
Oceans, Land, Atmosphere GCM, it was found that constraining surface
temperature in small regions of the tropics was sufficient to
substantially reduce the globally averaged response ( 23). Moreover,
recent work ( 24) leads one to conclude that models underestimate the
degree of mixing from the tropics to the extratropics, and hence may
underestimate the effect of the tropics on the extratropics. In
general, therefore, reduced tropical sensitivities will imply reduced
global sensitivity, though the extent of the reduction may well be
greater than indicated in ref. 23, since models appear to understate
the degree of coupling between the tropics and extratropics.
In dealing with the climate sensitivity of the tropics, we are dealing
with the sensitivity of a system open not only to changes in top of
atmosphere (TOA) radiative forcing but also to changes in meridional
flux. This is illustrated in Fig. . Sensitivity
would essentially be the ratio of average tropical temperature change
to change in total flux. However, for the meridional flux, we can be
reasonably confident that for increasing temperature,
Δ Fmeridional ≥ 0, provided that we are
considering zonal averages over the whole tropics. In this case, if we
include only TOA flux changes, we will get an upper bound for
sensitivity, as is readily seen from Eq. 2:
If the average is over only a sector of the tropics, we have no
such assurance. This is one of the main problems in ref. 19. The
results there are nonetheless both suggestive and instructive. Chou
used Earth Radiation Budget Experiment data to assess the changes in
net flux over the region (−30° ≤ latitude ≤ +30°, −100°
≤ longitude ≤ +100°) between April 1987 (a warm El Niño
year) and April 1985 (a colder La Niña year). The average surface
temperature for the region he examined was about 0.3°C warmer in 1987
than in 1985. The change in net flux was about 4
W m −2. This flux change was almost entirely due to
OLR over clear sky regions (as opposed to clear sky OLR, which commonly
refers to the calculated OLR that would occur in the absence of
clouds). The changes over cloudy regions were dominated by clouds whose
infrared and visible effects tended to cancel to a large extent
locally, but to an important extent there is also cancellation between
different regions. As we see from Fig. , clear sky regions tend to be
very dry. The radiative response must be due to drying over these
regions, and this is consistent with Chou’s results, which show that
the flux changes are almost exclusively restricted to the subsiding
region of the Pacific. The explicit drying of already dry regions
appears to be more important than net drying. Indeed, there can be
moistening of already moist regions and even net moistening while still
having a negative water vapor feedback. Taken at face value, this
suggests a very low sensitivity for the tropics compared with most
GCMs, where a change of about 2°C is associated with 4
W m −2. Using Eq. 1, this would imply a
water vapor feedback factor of about −2 rather than +0.4, which is
typical of current models. However, given that Chou considered only a
sector, we do not know if this is an over- or underestimate of the
actual tropical sensitivity, since feedbacks require a consideration of
complete systems including both convective and subsiding regions, and
limited sectors include unknown proportions of each. Indeed,
consideration of other months and years can even lead to apparent
feedbacks of opposite sign for such limited regions. We also are unable
to distinguish pattern changes not directly related to mean temperature
from changes that are. It is nonetheless useful to examine any
differences between GCM-generated TOA flux changes and those found by
Chou for runs using the same sea surface temperatures used by Chou. A
preliminary attempt has been made in ref. 25, focusing only on OLR and
using the Atmospheric Model Intercomparison Program’s data for various
GCMs. This is by no means a test of sensitivities. However, it does
provide some information on how a very important component of
sensitivity is replicated in models. The results demonstrate that most
models overestimated the observed “sensitivity” appreciably
(though one, in fact, underestimated it). However, this work did not
check in detail as to how much of the difference was due to errors in
pattern or to water vapor feedbacks directly, nor did it focus on the
OLR in clear regions which dominated Chou’s results. In particular, it
would appear from Fig. that a very important consideration ought to
be how dry and how large the areal coverage is of the very dry
subsiding regions. One important methodological point which emerged
from Covey’s study ( 25) was that model results for regional
“sensitivity” varied pronouncedly from the models’ global
sensitivity, indicating rather clearly that what Chou was observing was
not global sensitivity. Such a situation is not remedied by
considering the statistics of many month pairs as opposed to the
use of a single pair by Chou.
Despite the problems in ref. 19, it does point the way toward a proper
observational determination of the sensitivity to global forcing. It
would consist, at best, in the measurement of the complete TOA flux
integrated over the whole earth (averaged over, say, a month) for
several years, and the measurement of surface temperature over the same
period. One would form the pattern correlation of temperature for each
pair of months in the record, as well as the average rms difference of
the temperatures and the difference of the globally averaged
temperatures. By sorting according to these three quantities, one
might, hopefully, be able to disentangle the dependence of flux on both
patterns and mean temperature. Presumably the latter would be
indicative of the climate sensitivity we are seeking. Comparing pairs
of months separately would avoid the problems in averaging associated
with the nonlinearity of the effect of water vapor. Performing such a
study for tropical latitudes separately would allow some insight into
the physical origins of the sensitivity. Of, course, there would remain
the problem of whether states differing only in mean temperature formed
proper surrogates for global climate change. There is also the problem
that total insolation varies with an annual cycle due to the varying
distance of the earth from the sun. This may require that comparisons
be restricted to the interannual variability of each month. However,
none of the quantities needed for such a study require any truly new
instruments. Indeed, it appears that the needed data may be marginally
available from existing satellites and surface data. The necessary
length of record will likely be determined by the need to obtain
sufficiently large numbers of month pairs to populate all relevant
possibilities. This number of appropriate month pairs is greatly
reduced if one cannot find a suitable correction for the varying solar
distance. A caveat that requires some consideration is the obvious fact
that Chou’s results ( 19) suggest how it is possible for OLR to change
in response to changes in circulation without accompanying changes in
mean temperature. If our question is how much must the earth’s
temperature change to compensate for 4 W m −2 forcing,
then Chou’s results show that it is at least physically possible for
such compensation to occur without net warming. This should alert us to
the possibility that simple definitions of climate sensitivity are by
no means guaranteed to be relevant. It should be mentioned that there have been attempts other than Chou’s
to directly measure climate sensitivity. Unfortunately, these generally
assumed that local or seasonal changes in temperature could be
considered as surrogates for climate change. However, as noted in ref.
12, the warmest regions are associated with convection and high upper
level humidities, while dry subsiding regions are associated with
cooler temperatures regardless of feedbacks. Thus, a study like that of
Raval and Ramanathan ( 26) inevitably shows a positive correlation of
surface temperature and “enhanced” greenhouse effect. Indeed,
should there be a strong negative feedback associated with enhanced
drying in subsiding regions (and/or expanded dry regions), such an
approach would indicate a spuriously increased water vapor feedback.
(This, itself, might lead to a useful test.) A similar problem pertains
to the study by Rind et al. ( 27). They compared the summer
tropics with the winter tropics. However, the summer tropics are
associated with ascending moist air, while the the winter tropics are
associated with dry subsiding air—again independent of the actual
feedback. Indirect Approach: Volcanic Sequences. It has long been noted
that volcanic veils provide a short-term perturber of global
temperature. Whether, the climatic response to such perturbations
provides a test of climate sensitivity is less clear. The problem was
addressed crudely in ref. 28. In that paper, a simple energy balance
climate model with a box-diffusion ocean was used. The ocean was taken
to have an insulated boundary at 300 m to simulate the effect of
upwelling and avoid the problems associated with unbounded oceans.
Climate sensitivity was specified. Volcanic veils were assumed to set
up within 3 months of eruption and decay with an exponential decay time
of 13 months. Diffusion, in such models, is a surrogate for all the
processes in real oceans that couple the mixed layer with the
thermocline. The coefficient is chosen to match chemical tracer data.
This is, of course, extremely crude, but might be adequate for global
response to global forcing. Using such a model, it was noted that the
response to a volcano during the first 2 years following eruption was,
given the uncertainties in both temperature measurements and aerosol
optical properties, unable to distinguish between sensitivities ranging
(in terms of the equilibrium response to double CO 2) from
0.15°C to 6°C. In this connection, it should be noted that a study
of the response of the GISS GCM to Pinatubo did mention that it was
only a test of the short-term physics in their model ( 29). Recently, C.
Giannitsis and I have recalculated the response to volcanos with a
model that, at least, distinguishes land and sea, tuning the coupling
between the two by using the seasonal cycle (R.S.L. and C. Giannitsis,
unpublished work). The results, for the purposes of this discussion,
are similar to those reported in ref. 28 in that a reasonable
correspondence between calculated response and observed response is
obtained for a wide range of sensitivities, at least for the first 2
years following eruption. For longer periods, there is an interesting
dependence on sensitivity. For low sensitivities, the response rapidly
decays to essentially zero. However, for higher sensitivities, there is
a rapid decay of the response to about 30% of the maximum response,
with the remainder decaying on the ocean response scale, which is very
long. The reason for this difference is that climate sensitivity is
also a measure of how tightly air and sea temperatures are coupled.
High sensitivity is associated with weak coupling, allowing the
establishment of significant disequilibration of the sea surface
temperature. This was noted in detail in ref. 31. As a practical
matter, 30% of the peak response is too small relative to natural
variability to be detected. However, it was suggested in ref. 28 that a
sequence of strong volcanos occurring over several decades would
produce a measurably different response for different sensitivities.
Such a sequence did occur between Krakatoa in 1883 and Katmai in 1912,
with a noticeable absence of large eruptions until the 1950s. Of
course, there is a great deal of uncertainty over the exact strength of
the forcing due to these volcanos. Our results were based on what we
believe to be the conservative assumption that Krakatoa was no stronger
than Pinatubo. The results show that for sensitive climates (>0.6°C
for a doubling of CO 2), each volcano builds on the residual
base of earlier volcanos leading to a substantial long-term cooling
(≈0.5°C between 1883 and 1912). For low sensitivity, the response
consists in a sequence of essentially independent “blips.” The
observed temperature record certainly shows nothing more than isolated
“blips.” Given the uncertainties in the volcanic forcing, it
would be inappropriate to place undue confidence in this result.
However, it is consistent with low sensitivity. The results stem from
the long response time associated with large sensitivity, and argue for
short response times. It is also possible to reduce response times by
assuming lower ocean heat diffusivity. However, this gives rise to
larger discrepancies between predictions and observations of
temperature change over the past century. The commonly claimed
“broad consistency” depends on long ocean delays. Indirect Approach: Eocene. Fig. suggests another possibility
for the indirect estimate of tropical sensitivity. Past climates
involved marked changes in the equator-to-pole temperature difference.
In the case of ice ages, this difference may have been due in part to
the increased meridional gradient in radiative forcing due to the
increased high-latitude albedo associated with the ice itself. This
renders difficult the specification of the forcing that was acting on
the tropics. However, for warmer climates, like that of the Eocene, the
change in albedo from the present may not have been large, and the
reduced equator-to-pole temperature difference almost certainly called
for an increased heat flux out of the tropics. At present, this flux is
about 5 PW, of which the ocean contributes about 1 PW ( 10). It may be
estimated that a reduction of the equator-to-pole temperature
difference from about 40°C to 20°C will require that the present
flux be increased to about 6 PW. Although it is currently popular to
seek such changes as arising from shifts in ocean circulation, they can
also arise quite readily from changes in atmospheric heat flux. The
strength of forcing of atmospheric eddies depends not only on the
meridional gradient of radiative forcing but also on the intensity of
the tropical Hadley circulation, which supplies the momentum to the
unstable subtropical jet. The latter is strongly influenced by both
orbital parameters and the distribution of land and sea ( 2, 32), both
of which were almost certainly different during the Eocene. Such
forcings are potentially much larger than one expects from the net
external radiative forcing (especially from orbital variations), and do
not, in fact, call for net average external forcing. In any event, a
positive Δ Fmeridional of about 1 PW is
equivalent to a Δ FTOA of about 12
W m −2 for the tropics. This ought to have cooled the
tropics, and, indeed, early estimates of Eocene equatorial temperatures
indicated that the tropics may have been as much as 5°C cooler than
they are today. This is only modestly less than current model
sensitivity. However, recent corrections to these early estimates have
reduced the equatorial cooling to less than 1°C ( 33), which is more
in line with the sensitivity estimates based on the sequence of
volcanos around the turn of the past century. The response in the
extratropics is consistent with meridional temperature structure being
significantly determined by dynamic processes rather than detailed
radiative responses at each latitude ( 34, 35). Again, there are
legitimate questions about this procedure, not the least of which
concern the reliability and representativeness of the paleoclimatic
data. The role of potentially higher levels of CO 2 during
the Eocene could have contributed to reduced equatorial cooling, though
current assessments ( 36) suggest that CO 2 levels during the
Eocene were only double present values, and such changes would cancel
only 4 W m −2. The Nature of Past Climate Change The primary variable in most global warming discussions is global
mean temperature. The suggested values for change on the order of 2°C
do not, on the face of it, seem catastrophic. However, it is commonly
noted that major changes in past climate were, in fact, associated with
relatively small changes in global mean temperature, but that the
global changes were well correlated with changes in the mean. The basis
for these claims is essentially Fig. , which is
based on ref. 37 but is generally attributed to ref. 38. What is shown
in this figure is the meridional distribution of surface temperature
for various past climates scaled by the change in global mean
temperature. The fact that temperatures so scaled seem to lie on a
single curve has led to the conclusion that mean temperature determines
the meridional distribution uniquely. However, the “universality”
of the relation is almost certainly an artifact of the fact that
equatorial temperature changes are, according to this curve, very
small. Thus, climate changes involving primarily changes in the
equator-to-pole temperature difference will inevitably scale
approximately with the mean temperature, since changes in the mean
temperature are simply a residual of the changes in the equator-to-pole
temperature when equatorial temperatures are approximately fixed. If,
as suggested by GCM results in Fig. , equatorial temperature changes
are not much smaller than extratropical changes, then the
“universality” of the curve in Fig. would disappear. In either
case, we no longer have any direct relation between global mean
temperature and overall climate. This is consistent with the fact that
we have no convincing mechanism whereby changes in mean temperature
automatically determine the changes in meridional heat flux. At the
same time, we do have mechanisms for changing the meridional heat flux
even in the absence of changes in the mean external radiative forcing
( 32). In view of the above, there appears to be little reason to assume
the modest changes in mean temperature that are claimed for increased
CO 2 will automatically be associated with major global
climate change. Similarly, there is no reason to suppose that a climate
insensitive to changing CO 2 cannot, nonetheless, undergo
profound climate change.
Conclusion The brief conclusion of this paper is that current GCMs are
inadequate for the purpose of convincingly determining whether the
small changes in TOA flux associated with an increase in
CO2 are capable of producing significant climate change.
However, we may not be dependent on uncertain models to ascertain
climate sensitivity. Observations can potentially directly and
indirectly be used to evaluate climate sensitivity to forcing of the
sort produced by increasing CO2 even without improved GCMs.
The observations needed for direct assessment are, indeed, observations
that we are currently capable of making, and it is possible that the
necessary observations may already be in hand, though the accuracy
requirements may be greater than current data provide. Still, the
importance of the question suggests that such avenues be adequately
explored. Since the feedbacks involved in climate sensitivity are
atmospheric, they are associated with short time scales. Oceanic delays
are irrelevant, since observed surface temperatures are forcing the
flux changes we are concerned with. The needed length of record must be
determined empirically. Indirect estimates, based on response to
volcanos, suggest sensitivity may be as small as 0.3–0.5°C for a
doubling of CO2, which is well within the range of natural
variability. This is not to suggest that such change cannot be
detected; rather, it is a statement that the anticipated change is well
within the range of what the earth regularly deals with. It is further
noted that the common assertion that even small changes in mean
temperature can lead to major changes in climate distribution is
ill-founded and, likely, wrong. Work reported here was done cooperatively with E. Schneider, C.
Giannitsis, and D. Kirk-Davidoff. This work was supported by Grant
914441-ATM from the National Science Foundation and Grant NAGW 525 from
the National Aeronautics and Space Administration. Ten percent of this
research was funded by the U.S. Department of Energy’s National
Institute of Global Environmental Change (NIGEC) through the NIGEC
Northeast Regional Center at Harvard University (Department of Energy
Cooperative Agreement DE-FC03–90ER61010) and through the Computer
Hardware, Advanced Mathematics and Model Physics program. Financial
support does not constitute an endorsement by the Department of Energy
of the views expressed in this article. | | OLR | outgoing long-wave radiation | | | GCM | general
circulation model | | | GFDL | Geophysical Fluid Dynamics Laboratory | | | GISS | Goddard Institute for Space Studies | | | TOA | top of atmosphere |
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