Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.240
IF 5-year value: 5.768
IF 5-year
CiteScore value: 8.9
SNIP value: 1.713
IPP value: 5.53
SJR value: 3.18
Scimago H <br class='widget-line-break'>index value: 71
Scimago H
h5-index value: 51
Volume 7, issue 2
Geosci. Model Dev., 7, 621–629, 2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 7, 621–629, 2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model experiment description paper 16 Apr 2014

Model experiment description paper | 16 Apr 2014

Design of a regional climate modelling projection ensemble experiment – NARCliM

J. P. Evans1, F. Ji2, C. Lee2, P. Smith3, D. Argüeso1, and L. Fita1 J. P. Evans et al.
  • 1ARC Centre of Excellence for Climate System Science and the Climate Change Research Centre, University of New South Wales, Sydney, Australia
  • 2Office of Environment and Heritage, New South Wales Government, Sydney, Australia
  • 3Macquarie University, Sydney, Australia

Abstract. Including the impacts of climate change in decision making and planning processes is a challenge facing many regional governments including the New South Wales (NSW) and Australian Capital Territory (ACT) governments in Australia. NARCliM (NSW/ACT Regional Climate Modelling project) is a regional climate modelling project that aims to provide a comprehensive and consistent set of climate projections that can be used by all relevant government departments when considering climate change. To maximise end user engagement and ensure outputs are relevant to the planning process, a series of stakeholder workshops were run to define key aspects of the model experiment including spatial resolution, time slices, and output variables. As with all such experiments, practical considerations limit the number of ensemble members that can be simulated such that choices must be made concerning which global climate models (GCMs) to downscale from, and which regional climate models (RCMs) to downscale with. Here a methodology for making these choices is proposed that aims to sample the uncertainty in both GCM and RCM ensembles, as well as spanning the range of future climate projections present in the GCM ensemble. The RCM selection process uses performance evaluation metrics to eliminate poor performing models from consideration, followed by explicit consideration of model independence in order to retain as much information as possible in a small model subset. In addition to these two steps the GCM selection process also considers the future change in temperature and precipitation projected by each GCM. The final GCM selection is based on a subjective consideration of the GCM independence and future change. The created ensemble provides a more robust view of future regional climate changes. Future research is required to determine objective criteria that could replace the subjective aspects of the selection process.

Publications Copernicus