G. Advancing Understanding
The previous sections have contained descriptions of
the current state of knowledge of the climate of the past and present, the current
understanding of the forcing agents and processes in the climate system and how
well they can be represented in climate models. Given the knowledge possessed
today, the best assessment was given whether climate change can be detected and
whether that change can be attributed to human influence. With the best tools
available today, projections were made of how the climate could change in the
future for different scenarios of emissions of greenhouse gases.
Figure 28: The cascade of uncertainties in projections to be considered
in developing climate and related scenarios for climate change impact, adaptation,
and mitigation assessment. [Based on Figure
This Section looks into the future in a different way. Uncertainties are present
in each step of the chain from emissions of greenhouse gases and aerosols, through
to the impacts that they have on the climate system and society (see Figure
28). Many factors continue to limit the ability to detect, attribute, and
understand current climate change and to project what future climate changes
may be. Further work is needed in nine broad areas.
Arrest the decline of observational networks in many parts of the world. Unless
networks are significantly improved, it may be difficult or impossible to detect
climate change in many areas of the globe.
Expand the observational foundation for climate studies to provide accurate,
long-term data with expanded temporal and spatial coverage. Given the complexity
of the climate system and the inherent multi-decadal time-scale, there is a
need for long-term consistent data to support climate and environmental change
investigations and projections. Data from the present and recent past, climate-relevant
data for the last few centuries, and for the last several millennia are all
needed. There is a particular shortage of data in polar regions and data for
the quantitative assessment of extremes on the global scale.
G.2 Climate Processes and Modelling
Estimate better future emissions and concentrations of greenhouse gases and
aerosols. It is particularly important that improvements are realised in deriving
concentrations from emissions of gases and particularly aerosols, in addressing
biogeochemical sequestration and cycling, and specifically, and in determining
the spatial-temporal distribution of CO2 sources and sinks, currently
and in the future.
Understand and characterise more completely dominant processes (e.g., ocean
mixing) and feedbacks (e.g., from clouds and sea ice) in the atmosphere, biota,
land and ocean surfaces, and deep oceans. These sub-systems, phenomena,
and processes are important and merit increased attention to improve prognostic
capabilities generally. The interplay of observation and models will be the
key for progress. The rapid forcing of a non-linear system has a high prospect
of producing surprises.
Address more completely patterns of long-term climate variability. This
topic arises both in model calculations and in the climate system. In simulations,
the issue of climate drift within model calculations needs to be clarified better
in part because it compounds the difficulty of distinguishing signal and noise.
With respect to the long-term natural variability in the climate system per
se, it is important to understand this variability and to expand the emerging
capability of predicting patterns of organised variability such as ENSO.
Explore more fully the probabilistic character of future climate states
by developing multiple ensembles of model calculations. The climate system
is a coupled non-linear chaotic system, and therefore the long-term prediction
of future exact climate states is not possible. Rather the focus must be upon
the prediction of the probability distribution of the system's future possible
states by the generation of ensembles of model solutions.
Improve the integrated hierarchy of global and regional climate models with
emphasis on improving the simulation of regional impacts and extreme weather
events. This will require improvements in the understanding of the coupling
between the major atmospheric, oceanic, and terrestrial systems, and extensive
diagnostic modelling and observational studies that evaluate and improve simulative
performance. A particularly important issue is the adequacy of data needed to
attack the question of changes in extreme events.
G.3 Human Aspects
Link more formally physical climate-biogeochemical models with models of the
human system and thereby provide the basis for expanded exploration of possible
cause-effect-cause patterns linking human and non-human components of the Earth
system. At present, human influences generally are treated only through emission
scenarios that provide external forcings to the climate system. In future more
comprehensive models are required in which human activities need to begin to interact
with the dynamics of physical, chemical, and biological sub-systems through a
diverse set of contributing activities, feedbacks and responses.
G.4 International Framework
Accelerate internationally progress in understanding climate change by strengthening
the international framework that is needed to co-ordinate national and institutional
efforts so that research, computational, and observational resources may be used
to the greatest overall advantage. Elements of this framework exist in the
international programmes supported by the International Council of Scientific
Unions (ICSU), the World Meteorological Organization (WMO), the United Nations
Environment Programme (UNEP), and the United Nations Education, Scientific and
Cultural Organisation (UNESCO). There is a corresponding need for strengthening
the co-operation within the international research community, building research
capacity in many regions and, as is the goal of this assessment, effectively describing
research advances in terms that are relevant to decision making.