The full programme book (PDF) - Royal Geographical Society

THEME 4: MODELLING THE EARTH SYSTEM
Modelling the Earth System: Challenges in using Observations for Model Evaluation
Sandy Harrison 1,2
1 Department of Biological Sciences, Faculty of Science, Macquarie University, Australia
2 Centre for Past Climate Change and School of Archaeology, Geography and Environmental Science
(SAGES), University of Reading
The confrontation of palaeo-observations and model experiments has evolved from
essentially qualitative “data-model comparisons” to quantitative “model evaluation”. Both
have a role to play: the first in elucidating the mechanisms of climate change and regional
impacts, the second in testing the reliability of state-of-the-art models.
Data-model comparisons have focused on large-scale regional patterns of climate and/or
environmental changes. Mapped patterns are used to elucidate the mechanisms of
climate change, based on the idea that these patterns provide fingerprints of the response
to specific types of forcing. Map comparisons are facilitated by the use of forward
modeling, which translates simulated climate changes into environmental responses such
as vegetation shifts, changes in fire regimes or changes in peat accumulation rates which
can be more directly compared with observations. The use of forward models raises
issues about the independent validation those models, but perhaps a more serious issue
is how to compare spatial patterns in a mechanistically realistic way – given that features
anchoring these patterns in the real world may not be represented in the model world.
Various clustering or circulation-based techniques are being explored to address this
issue, but the answer is not entirely obvious.
Model evaluation has become a major preoccupation with the inclusion of palaeoclimate
experiments, specifically the Last Glacial Maximum (LGM), mid-Holocene (MH) and last
millennium (LM), in the Coupled Modelling Intercomparison Project (CMIP) as a way of
testing whether models that are used for future projections can simulate known climate
changes. Model evaluation relies on synthesis of quantitative climate reconstructions or of
palaeoenvironmental data that can be directly compared with outputs from earth-system
models (ESMs). There are a large number of quasi-global palaeodata syntheses now
available; whether they are suited to purpose is more debatable. There are issues
associated with the reporting of uncertainty and the use of reported uncertainties in
comparison exercises. To some extent the importance of such issues is a function of the
signal being evaluated. For example, the signal-to-noise ratio in the LGM change in seasurface
temperatures is sufficiently large for methodological uncertainties or inter-sensor
differences to be negligible. This is not true for the MH, where methodological
uncertainties alone are larger than any apparent regional signal in seasonal sea-surface
temperature changes, and differences in the reconstructions obtained from different types
of record are also large and non-systematic.
The growing focus on using transient simulations to understand climate evolution poses
new and particular challenges. Observationalists are well aware of the issues associated
with temporal uncertainty. We have not yet grappled with temporal uncertainty in a