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Assumptions and limitations

All methods of providing climate change projections incorporate a range of assumptions. The results represent the effects of earth system processes understood sufficiently well to be included in the climate models used to produce the projections.

Here we summarise a few key assumptions and limitations. The first two points provide general context informing how climate change projections should be interpreted. The third and fourth points provide two specific examples of a number of more detailed methodological assumptions, on which more information is provided in Chapter 3 of the UKCP09 probabilistic climate projections report.

1 - The UKCP09 projections represent known uncertainties in earth system processes included in the climate models used to produce them

The modelling and statistical framework developed by the Met Office Hadley Centre to produce UKCP09 includes consideration of the drivers of uncertainty known to be important, and sufficiently well understood to be included in the climate models used to make the projections. These include physical atmospheric processes and carbon cycle feedbacks. There are other possible forcing processes and feedbacks that are not included either because their importance is thought to be small relative to those process and feedbacks included in UKCP09, or because they are currently too poorly understood to be included in a credible way (such as the feedback between climate change and the methane cycle). The effects of known but poorly understood processes imply a component of uncertainty which is currently unquantifiable, and is therefore not included in the UKCP09 data.

2 - Future climate projections cannot represent the effects of errors common to all current climate models

Structural error (the difference between the real world and model projections) is incorporated into the UKCP09 projections by comparing the HadCM3 projections with those from twelve other climate models. Including this structural uncertainty prevents the projections from being too heavily biased by the way in which one model is structured. Using multiple climate models overcomes this issue to a certain extent. However, this strategy does not account for the effects of systematic biases common to all current climate models. Such common biases are a further source of unquantifiable uncertainty, alongside the effects of poorly understood processes not yet included in climate models.

These qualitative uncertainties are inevitable, and effectively arise from the limits of current knowledge. Understanding that they exist provide valuable context for appropriate use of the projections, emphasising the importance of testing the sensitivity of user decisions to plausible variations in the probabilistic data.

3 - That models that simulate recent climate and historical trends well are more accurate at simulating future climate

UKCP09 assumes that climate models that more accurately reproduce observed (past) climate are more skilful in their projection of future climate. In practice, this means that different variants of the Met Office Hadley Centre model are assigned different weights according to how well the model simulates a set of observations of recent average climate, and of past climate change during the 20th century.

4 - That local effects of carbon cycle feedbacks are not accounted for

Feedbacks at the global scale are considered through changes in global temperature, which include changes that would occur as a result of carbon cycle processes. However, the UKCP09 projections do not consider any potential influences of carbon cycle feedbacks in modifying regional patterns of climate change as the global temperature changes. For the UK, any such effects are likely to be modest compared to other effects included in the projections, based on evidence from current earth system model simulations. This is in contrast to some world regions, for example Brazil, where some simulations suggest potential for future die back of the Amazon rainforest, leading to considerable effects on the local climate.