final_program_abstracts[1]

11 IMSC Session Program
Towards systematic calibration of comprehensive climate
models
Thursday - Poster Session 1
Omar Bellprat, Daniel Lüthi, Sven Kotlarski and Christoph Schär
Institute of Atmospheric and Climate Science, ETH Zürich, Switzerland
The calibration of climate models is a subject of constant debate and strongly
diverging opinions. There is no clear consensus whether the models should reproduce
most accurately past and present sets of observations or rather be exlusively based
upon physical laws. When should a model or a parameter set be rejected? Do the
available observations actually allow for rejection in the sense of the ability to make a
prediction? Which are the relevant characteristics of the model that should constrain
the parameter sets and which are the important statistical measures? Even though
these questions are fundamental, the efforts of model calibration in climate science
are often concealed. In particular physicallybased global and regional climate models,
which also are subject to some degree of calibration, show a lack of transparency of
their optimization.
From the calibration of intermediate complexity climate models, which is a far more
openly discussed topic, we have improved our understanding of the parameter
uncertainty and the structural errors of the climate models. In addition it provided
some estimates on how much of the model projection uncertainty can be constrained
by reducing the parameter uncertainty and led to the application of many efficient
statistical frameworks for model calibration. Unfortunately most these methods are
still inappropriate for costly high resolution climate models, but still relevant
information on parameter interrelations and model uncertainty can be inferred.
Here we present preliminary results of an ongoing project on the systematic
calibration of the regional climate model COSMOCLM. The COSMOCLM is a
nonhydrostatic limited area climate model originally developed by the German
Weather Service. An optimal performance framework on the variables of interest,
available and useful reference datasets, statistical measures of skill and spatial and
temporal averaging is discussed. We show the effects of training period length on the
measures, implications for the consideration of interannual variability and relate the
measures to estimates of the internal variability of the model for the years 1990 –
2000.
Furthermore a perturbed physics ensemble is shown for about 50 poorly confined
parameters in the convection, turbulence, radiation, microphysics, dynamical and
surface flux scheme for the year 1990. Parameters of the soil model are not tested,
since long simulations are required to assess the model sensitivity to these parameters.
The results of the model sensitivity and its pattern correlation are related to the
calibration of the model.
Abstracts 268