Changes to the climate and consequences for real world systems are typically investigated from either of two perspectives, these are commonly referred to as: ‘top-down’ or ‘bottom-up’ approaches.
The process of assessing climate change and its impacts involves the simulation of a range of different socio-economic and physical processes. Some of these processes are well known, others not. Hence for each modelling step researchers need to consider what is known, what is not known, and how can we attempt to represent any uncertainties that arise from gaps in knowledge. If the process of generating estimates of future climate change is seen as a chain of processes, the top-down and bottom-up approach defines where in this chain analysis begins.
Top-down approaches give information on the range of simulated plausible impacts.
Top-down analysis emphasises understanding the plausible impacts by attempting to represent different sources of uncertainty as it moves through the chain of processes, typically:
This type is the most common approach to investigating climate change impacts, and sometimes referred to as a ‘first generation’ type of impact and adaptation study.
Bottom-up approaches base their analysis on an understanding of existing pressures and demands on a system; – vulnerabilities to climate change are considered in context with non-climate factors.
The bottom-up approach starts with an attempt to identify the nature of climate risks that a system is exposed to under current climate. Often analysis considers other aspects that influence system performance, so that climate risks are not assessed in isolation of other demands on the system. With an understanding of what kind of changes to the climate, or under what circumstances the system becomes more vulnerable to climate changes, users can look to output from climate models to assess if there is high confidence in such conditions occurring and subsequently modify behaviour or conditions to alleviate pressures should such climate change eventuate.
The bottom-up style of analysis represents a second generation type of analysis, reflecting emergent needs by the adaptation and vulnerability community to move away from ‘predict-then-act’ frameworks. For these disciplines, outputs from top-down methods may offer limited value when attempting to improve adaptive capacity or resilience to climate change; providing insights mainly into a likely range of impacts rather than on system sensitivities and typically ignores non-climate influences.
In most cases, the intended application will dictate the approach most appropriate. If the research is investigating system responses under a changing environment, climate model based information provides useful aid in testing the system outside the observed climate boundaries in an exploratory manner. However, for applications that are strongly grounded in real-life situations and influenced by factors beyond the climate, a bottom-up approach is perhaps better suited, providing understanding about how a system may be sensitive to climate variability in combination with other existing pressures.
If viewing the impact study as a type of risk assessment , aspects of both perspectives are present where work involves continuous monitoring of its effectiveness with built-in opportunity to reflect on lessons learnt in a dynamic and iterative way.
Page updated 24th December 2020