final_program_abstracts[1]

11 IMSC Session Program
Quantifying uncertainty in climate forecasts from
climateprediction.net
Thursday - Parallel Session 2
Dan Rowlands 1 , Dave Frame 2 , Tolu Aina 3 , Nicolai Meinshausen 4 and Myles
Allen 1
1 AOPP, Oxford University, UK
2 Smith School, Oxford University, UK
3 OeRC, Oxford University, UK
4 Department of Statistics, Oxford University, UK
Perturbed physics ensembles have been run to explore the uncertainty in climate
forecasts by systematically varying physics parameters in a single base model. Here
we discuss some results from the transient HadCM3L ensemble run as part of the
climateprediction.net project.
In particular we detail the approach taken in evaluating the level of model-data
discrepancy in each ensemble member, based on methods used in Detection &
Attribution studies. In particular we advocate comparing model output and
observations only at a level where the residual is indistinguishable from our best
estimate of natural variability – this avoids ignoring the irreducible error or the need
for a subjective “discrepancy” term.
Further, we consider the question of what observations are relevant for making a
particular climate forecast: should the set that we use depend on the question that we
are asking, or does it make sense to have a broad set over which we evaluate the
model performance? Can the inclusion of transient and climatological information
together help us rule out particular future climates?
We finally discuss how one may incorporate all of this information together into a
single probabilistic forecast, and advocate objective approaches based on testable
information rather then subjective, often untestable, prior assumptions on climate
model parameters.
Abstracts 245