Objective calibration of regional climate models: Application over Europe and North America

Friday, 19 December 2014
Omar Bellprat1,2, Ramon De Elia3, Anne Frigon3, Sven Kotlarski2, Daniel Lüthi2, René Laprise4 and Christoph Schär2, (1)Institut Català de Ciències del Clima, Barcelona, Spain, (2)ETH Zurich, Atmospheric and Climate Science, Zurich, Switzerland, (3)Ouranos, Montreal, QC, Canada, (4)University of Quebec at Montreal UQAM, Montreal, QC, Canada
An important source of model uncertainty in climate models arises from unconfined model parameters in physical parameterizations. These parameters are commonly estimated on the basis of manual adjustments (expert tuning), which carries the risk of over-tuning the parameters for a specific climate region or time period. This issue is particularly germane in the case of regional climate models (RCM), which are often developed and used in one or a few geographical regions only. Here we address the role of objective parameter calibration in this context. Using a previously developed objective calibration methodology, we calibrate an RCM over two regions (Europe and North America) and investigate the transferability of the results. A total of eight different model parameters are calibrated, using a metamodel to account for parameter interactions. We demonstrate that the calibration is effective in reducing model biases in both domains. For Europe, this concerns in particular a pronounced reduction of the summer warm bias and the associated overestimation of interannual temperature variability, that has persisted previous expert tuning efforts and that is common in many global and regional climate models. The key process responsible behind this improvement is an increased hydrological conductivity. Over North America, there is also some reduction of the summer warm bias, but in addition the calibration achieves a pronounced reduction of winter biases in interannual temperature variability. We also find that the calibrated parameter values are almost identical for both domains, i.e. the parameter calibration is transferable between the two regions. This is a promising result and indicates that models may be more universal than previously considered.