19.1.3. Role of Adaptation
Successful adaptation reduces vulnerability to an extent that depends greatly
on adaptive capacitythe ability of an affected system, region, or community
to cope with the impacts and risks of climate change (see Chapter
18). Enhancement of adaptive capacity can reduce vulnerability and promote
sustainable development across many dimensions.
Adaptive capacity in human systems varies considerably among regions, countries,
and socioeconomic groups. The ability to adapt to and cope with climate change
impacts is a function of wealth, technology, information, skills, infrastructure,
institutions, equity, empowerment, and ability to spread risk. Groups and regions
with adaptive capacity that is limited along any of these dimensions are more
vulnerable to climate change damages, just as they are more vulnerable to other
stresses. Enhancement of adaptive capacity is a necessary condition for reducing
vulnerability, particularly for the most vulnerable regions, nations, and socioeconomic
groups. To be sure, some development paths can increase some types of vulnerabilities,
whereas others can reduce those vulnerabilities.
Adaptive capacity in natural systems tends to be more limited than adaptive
capacity in human systems. Many species have limited ability to migrate or change
behavior in response to climate change. What may be of greater concern is the
harm that already has been done to natural systems by societal development.
Habitat fragmentation and destruction, as well as creation of barriers to migration,
will make it much more difficult for species to cope with climate change than
if natural systems were undisturbed.
We do not address adaptation explicitly in this chapter, except to the extent
that the literature cited here considers adaptation. Adaptation may have the
potential to reduce vulnerability and, in many cases, shift the threshold for
negative impacts to higher magnitudes of climate change. The degree to which
adaptation can do so is not addressed here; it should be the subject of future
Box 19-1. Uncertainties in Future Warming
Figure 19-1: Global mean temperature change (from 1990) as
a function of CO2 concentration for SRES scenarios. For
any given CO2 level, uncertainties in temperature arise
through several factors. The three most important are accounted for
here: First, different temperatures for a given future CO2
level may arise because each emissions scenario has different levels
of other GHGs and different levels of SO2 emissionsfactors
that lead to a range of possible non-CO2 forcings (results
here consider all six SRES illustrative scenarios); second, different
temperatures arise because of uncertainties in climate sensitivity
(three values1.5, 2.5, and 4.5ºC equilibrium warming for
a CO2 doublingare used here); and third, different
temperatures arise because different rates of radiative forcing change
and different climate sensitivities lead to different levels of damping
of the instantaneous equilibrium response.
Does a given atmospheric concentration of GHGs cause
a specific change in global mean temperature (or other climate variables,
for that matter)? To answer this question, we quantify uncertainties in
the change in global mean temperature for a given CO2 concentration
level. This is accomplished by using the same simple models that are used
in the TAR Working Group I report (TAR WGI Chapter
9). These models are updated versions of models used previously by
the IPCC in the Second Assessment Report (SAR) (Kattenberg et al., 1996;
see also Raper et al., 1996). We consider the effects of uncertainties
in future emissions of all radiatively important gases (particularly the
relative importance of CO2 to other forcing factors) and climate
sensitivity, but not uncertainties in translating emissions to concentrations.
These uncertainty issues are addressed by comparing CO2 concentrations
(not other GHGs) and the corresponding temperature projections for 5-year
time steps from 1990 to 2100 (i.e., using results for 1995, 2000, 2005,
etc.) for the six illustrative emissions scenarios from the IPCC Special
Report on Emissions Scenarios (SRES) (Nakicenovic et al., 2000) under
a range of climate sensitivity assumptions. The six emissions scenarios
provide a sampling of the space of the relative effects of CO2
compared with other GHGs and sulfur dioxide (SO2)-derived sulfate
aerosols. Climate sensitivity (3T2x) values of 1.5, 2.5, and
4.5°C are used.
The results are plotted as a simple scatter diagram of temperature change
against CO2 concentration (see Figure 19-1).
The scatter plot has 22 5-year values (1990 values are zero in each case)
by six scenarios by three sensitivities (396 points). The diagram is meant
only to illustrate a range of possibilities. One cannot associate any
specific confidence intervals with the ranges shown; however, simultaneous
use of realistic values in several input parameters with the judgment
that the climate sensitivity range of 1.5-4.5°C represents approximately
the 90% confidence interval (see, e.g., Morgan and Keith, 1995) suggests
that the probability of a result outside the ranges shown, during the
interval 1990-2100, is less than 10%.
The results are shown in Figure 19-1. For example,
for a future CO2 level of 550 ppmv, the global mean warming
range is 1-3°C relative to 1990. Thus, a specific CO2
concentration could lead to a range of increases in global mean temperature.
Note that this is a transient result; in other words, if CO2
concentrations were stabilized at 550 ppmv, substantial additional warming
would occur beyond this range as the climate system slowly relaxed toward
a new equilibrium state. The levels of increase in global mean temperature
displayed in the diagram are less than what would eventually happen if
CO2 concentrations were stabilized at a particular level. Note
also that there is no time (or date) associated with any particular concentration
level. For, example, in the SRES scenarios, 550 ppmv is reached at a range
of dates from about 2050 onward.