Research : uncertainty
Sources of uncertainty in regional climate predictions
Decision makers in a wide variety of organisations are increasingly seeking quantitative climate forecasts. An important issue for these decision makers, and for organisations that fund climate research, is: what is the scope for narrowing the uncertainty through future monitoring, research and development activities?
Using IPCC model data we have quantified the relative importance of different sources of uncertainty in climate projections of surface air temperature, precipitation and ozone to help answer this question. Additionally, we have built an interactive website to allow users to explore the results.
We have also explored the key question of 'when' will climate impacts be felt. This allows planning of adaptation strategies.
Relevant papers:
• Hawkins & Sutton, 2012, 'Time of emergence of climate signals', Geophys. Res. Lett., 39, L01702
• Joshi, Hawkins, Sutton, Lowe & Frame, 2011, 'Projections of when temperature change will exceed 2C above pre-industrial levels', Nature Climate Change, 1, 407
• Hawkins & Sutton, 2011, 'The potential to narrow uncertainty in projections of regional precipitation change', Climate Dynamics, 37, 407
• Charlton-Perez et al., 2010, 'The potential to narrow uncertainty in projections of stratospheric ozone over the 21st century', Atmospheric Chemistry and Physics, 10, p9473
• Hawkins & Sutton, 2009, 'The potential to narrow uncertainty in regional climate predictions', BAMS, 90, p1095 (open access).
End-to-end quantification of uncertainty in impacts predictions (EQUIP)
The EQUIP
project will advance the quantification of uncertainty in the
prediction of climate and of climate impacts with a view to supporting
decision making among users. It will develop new methodologies for
assessing the information content of climate-model projections, for
combining climate models and data-driven models to support decisions,
and for evaluating the quality of climate and impacts predictions. The
project will also conduct integrated assessments of the cascade of
uncertainty from climate to impacts: not just feeding climate
ensembles through impact models, but analysing sources of uncertainty
and using the resulting information to find better ways of quantifying
uncertainty in predictions of climate impacts for decision makers.
