How well do we understand climate change feedback processes?
Christopher S. Bretherton
Department of Atmospheric Sciences
University of Washington
Seattle, WA USA
This talk will review the concept of climate sensitivity to greenhouse gas concentration changes,
and how the historical climate record constrains climate sensitivity. We will discuss the main
feedbacks of climate change – water vapor, snow and ice albedo, clouds, and carbon cycle
changes, and how accurately we can model these feedbacks. We will also compare how these
feedbacks affect climate change over the next few decades vs. over longer timescales. Chapters
8-10 of the climate science working group contribution to the 2007 IPCC Assessment present an
authoritative picture for further reading.
1.
What is climate sensitivity?
Global warming is one of the central environmental challenges of this century, because it has
long impact timescales and because addressing this problem will require worldwide adoption of
huge changes in energy-production technology over the next few decades.
At heart, the science of global warming is very simple. The Earth absorbs energy from sunlight,
which heats it up. A warm object itself emits radiation. The amount of radiated energy increases
with temperature, while its wavelength decreases with temperature. The earth radiates in infrared
wavelengths, and its temperature adjusts until the energy it radiates out to space balances that
the energy it absorbs from the sun. The burning of fossil fuels produces CO2, much of which
stays in the atmosphere for a century or more. CO2 is a greenhouse gas, which absorbs some of
the infrared radiation emitted by the earth and prevents that energy from freely escaping to
space. If CO2 increases, the earth’s temperature must also increase until enough infrared
radiation is emitted to reestablish a balance with the incoming sunlight. This argument would
predict a 1.2°C global-average surface warming from a doubling of CO2 if the atmospheric
composition and surface changes remained unchanged,
The actual climate responds more strongly than this due to ‘climate feedbacks’ such as changes
in snow and ice, water vapor, and clouds that change the radiative characteristics of the planet as
CO2 warms. Climate models are used to predict these feedbacks. These models all agree that
overall, climate feedbacks are positive, so the actual climate warms more than 1.2°C for a given
greenhouse gas input. The predicted global-mean temperature response after many centuries to
a CO2 doubling (the ‘equilibrium climate sensitivity’) ranges from 2-4.5°C for most models. This
significant range leads to less reliable predictions of the climate changes expected to result from
a given greenhouse gas emissions scenario, and is sometimes used to cast doubt on the overall
utility of climate models. This talk will address why this range still exists, and why climate models
agree more closely on the climate change of the next 50 years that this range might suggest.
2.
The two-forcing problem – why observations can’t yet tell us climate sensitivity
Long temperature records from around the world suggest that in global average, there has
already been roughly 1°C of surface warming in the last 150 years, with more over land and at
high latitudes. During that time, atmospheric CO2 has increased 40%. This should apparently
give us a measure of climate sensitivity. The main complication is that human activities such as
fossil fuel and biomass burning have also greatly increased global aerosol concentrations. There
is scientific consensus that aerosols cool the planet, but not on the amount of cooling. Thus,
during the 20th century there have been two major human agents of climate change competing
with each other. Globally averaged aerosol concentrations are no longer increasing, a testament
to air pollution control measures in Europe and the USA, and are expected to decrease in future
as developing countries adopt similar air quality standards. However, until 1970, aerosols may
have masked at least half of human greenhouse-induced global warming. Uncertainty about this
cancellation affects all estimates of climate sensitivity based on the historical record.
3.
Climate feedbacks and timescales
Imagine a sudden global increase in atmospheric CO2. The climate does not instantly respond.
First land surfaces start to warm, then the surface waters of the ocean, while deep oceans and
continental ice sheets like Greenland can take hundreds to thousands of years to respond.
Similarly, some CO2 itself quickly moves from the atmosphere into the ocean surface waters,
more slowly interacts with land and ocean biological processes and with the deep ocean, and
ultimately after many thousands of years in sequestered into sedimentary rocks. Thus, we must
specify a timescale of interest in considering any climate feedback, e.g. the decade-to-century
timescale on which human greenhouse emissions are changing CO 2.
The classical climate feedbacks are natural responses to the increased land and ocean surface
temperature. The most important is water vapor feedback. Air that is 1°C warmer can hold 7%
more water vapor. Water vapor is the most important naturally-occurring greenhouse gas. The
additional water vapor also affects the vertical temperature structure of the atmosphere (‘lapserate feedback’). The combination of water vapor and lapse rate feedback causes a 30% reduction
in the CO2 required to induce a 1°C global temperature, i. e. a 30% positive feedback. Climate
models agree quite closely on the strength of the combined water vapor and lapse rate feedback,
and are consistent with water vapor trends seen in 25 years of satellite observations.
A second important feedback is snow-ice albedo feedback. In a warmer climate, snow cover
lessens. Snow reflects much more sunlight than bare ground or vegetation, so less snow means
that more sunlight is absorbed over the earth’s surface. Sea ice melts back to reveal a much
darker ocean surface. This 5-10% positive feedback is also fairly well understood and simulated
by climate models. It is one reason that climate models, like observations, imply warming is
amplified over high northern latitudes. The observed seasonal cycle of snow and sea-ice cover
and albedo provides a useful test of climate models that is highly relevant to this feedback.
The most uncertain feedback is due to clouds, which both reflect sunlight and absorb and emit
infrared radiation. Clouds are short-lived, often thin, and are often associated with physical
processes like turbulence and cumulus convection that occur on scales too small to represent
accurately in climate models. Satellite and in-situ observations have given us an excellent global
view of cloud systems in the current climate, but the satellite record is too short to reliably show
cloudiness trends. Cloud feedbacks in different climate models vary from near zero to strongly
positive (0-30%) across climate models. Despite modeling and observational advances, this
uncertainty, which dominates model-to-model variability of climate sensitivity, has persisted for
decades and seems unlikely to greatly decrease over the next 5-10 years.
4. Transient vs. equilibrium climate sensitivity
The large heat capacity of the oceans delays global warming. At current rates of CO2 increase
(0.6% per year), GCMs predict a globally-averaged warming of 1.5-2.5°C at the time CO2 doubles
from pre-industrial values. This ‘transient climate sensitivity’ is smaller than the equilibrium
climate sensitivity and is what is important for predicting the climate of the next 50 years. It is
impacted by climate feedbacks somewhat less than is the equilibrium climate sensitivity, but it
also depends on ocean heat uptake (also variable between models). Different emissions
scenarios do not have time to greatly impact CO2 concentrations over that period. Hence,
transient climate sensitivity is that main source of climate change prediction uncertainty through
2050 unless we find radical technological solutions such as large-scale geological sequestration
of atmospheric CO2.
Climate feedback uncertainties particularly affect longer-term climate predictions, which are
important to understanding the risk of irreversible melting of the Greenland and West Antarctic ice
sheets, sea-level rise, and long-term changes in natural rainfall and vegetation patterns.
However, those predictions are more strongly dependent on the cumulative effect of human
energy production choices.