Climate change assessment can be
viewed as the use of tools and models to anticipate the impacts of climate
change on social and ecological environments. There are a number of key questions
that need to be addressed in order to improve assessment processes. Some of
the conceptual frameworks, assessment tools and data requirements for climate
change assessment are outlined below.
Conceptual
Frameworks
Top-down and bottom-up approaches to assessing climate change
impacts are modelling tools that examine the linkages between the economy
and specific GHG emitting sectors. They are applied in economic assessment
to determine mitigation potential. These conceptual approaches are outline
below.
Top-Down
Top-down approaches assess the economy wide potential of alternate approaches.
They use globally consistent frameworks and capture macro-economic and market
feedbacks. Critics to top-down approaches claim that the aggregate models
applied in the top-down approach do not capture the sectoral details and complexity
of demand and supply.
Bottom-up
Bottom-up assessment models examine technological options or project-specific
climate change mitigation policies. They emphasise specific technologies and
regulations and take the macro-economy as unchanged. Bottom-up studies are
useful for the assessment of specific policy options at the sectoral level,
for example, options to improve energy efficiency.
Assessment Tools
There are a number of tools that can assist in evaluating different
coastal management and adaptation strategies. The following notes on assessment
tools come primarily from the UNFCC ‘Compendium
on methods and tools to evaluate impacts of, vulnerability and adaptation
to, climate change’.
A select number of the coastal assessment tools outlined by the UNFCC are
described in detail below:
The IPCC Common Methodology: A framework that incorporates
expert judgment and data analysis of socioeconomic and physical characteristics
to assist the user in estimating a broad spectrum of impacts from sea level
rise, including the value of lost land and wetlands. The approach is most
useful as an initial, baseline analysis for country level studies where little
is known about coastal vulnerability.
The South Pacific Islands Methodology: An index-based approach
that uses relative scores to evaluate different adaptation options in a variety
of scenarios. This approach is most useful in coastal settings with limited
quantitative data but considerable qualitative knowledge. It can be used during
evaluation phases to analyze a range of possible adaptation options. Following
the selection of an adaptation option, more quantitative data should be applied.
Dynamic Interactive Vulnerability Assessment (DIVA): A tool
designed to explore the vulnerability of coastal areas to sea level rise.
It comprises a global database of natural system and socioeconomic factors,
relevant scenarios, a set of impact-adaptation algorithms and a customized
graphical-user interface. It is designed for national, regional and global
scale analysis of coastal vulnerability, including consideration of broad
adaptation issues.
The UNEP Handbook Methodology: Establishes a generic framework for
thinking about and responding to the problems of sea level rise and climate
change. The user goes through seven steps: (1) define the problem, (2) select
the method, (3) test the method, (4) select scenarios, (5) assess the bio-geophysical
and socioeconomic impacts, (6) assess the autonomous adjustments, (7) evaluate
adaptation strategies. The last step is itself split into seven sub-steps.
At each step, methods are suggested but the choice is left up to the user.
This methodology is most useful at the national or subnational level. The
key outcome is the evaluation of a range of user-selected impacts of sea level
rise and potential adaptation strategies according to socioeconomic and physical
characteristics.
Data Requirements
Data is an integral component to the assessment process. The
quality of the assessment directly relates to the quality of the data input
into the assessment process. In broad scale terms, data is required for the
following areas: climatic influencing factors (temperature, rain, wind); non-climatic
influences (population, prices, pests, policies); internal functions of the
system and their climatic and other sensitivities; and the interactions (physical,
biological and social) with other systems and resultant integrated behaviours
(Basher 1999). Data requirements will vary by degree of complexity and scale
dependent upon the particular topic.
Data is the integral component to almost every aspect of climate change science.
Most of the data used for climate change assessment were, and still are, largely
collected for alternate purposes, for example, weather prediction. Thus the
spatial and temporal scale of the data may be inefficient for assessment purposes.
A list of data and information
sources is available from the Institute
for Technology Assessment and Systems Analysis