Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
doi:10.5194/gmd-2016-285
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Methods for assessment of models
21 Dec 2016
Review status
This discussion paper is under review for the journal Geoscientific Model Development (GMD).
Skill and independence weighting for multi-model assessments
Benjamin Sanderson1, Michael Wehner2, and Reto Knutti3,1 1National Center for Atmospheric Research, Boulder CO, USA
2Lawrence Berkeley National Laboratory, CA, USA
3ETH Zurich, Switzerland
Abstract. We present a weighting strategy for use with the CMIP5 multi-model archive in the 4th National Climate Assessment which considers both skill in the climatological performance of models over North America as well as the inter-dependency of models arising from common parameterizations or tuning practices. The method exploits information relating to the climatological mean state of a number of projection-relevant variables as well as metrics representing long term statistics of weather extremes. The weights, once computed can be used to simply compute weighted means and significance information from an ensemble containing multiple initial condition members from co-dependent models of varying skill. Two parameters in the algorithm determine the degree to which model climatological skill and model uniqueness are rewarded; these parameters are explored and final values are defended with respect to the Assessment. The influence of model weighting on projected temperature and precipitation changes is found to be moderate, partly due to a compensating effect between model skill and uniqueness. However, more aggressive skill weighting and weighting by targeted metrics is found to have a more significant effect on inferred ensemble confidence in future patterns of change for a given projection.

Citation: Sanderson, B., Wehner, M., and Knutti, R.: Skill and independence weighting for multi-model assessments, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-285, in review, 2016.
Benjamin Sanderson et al.
Benjamin Sanderson et al.
Benjamin Sanderson et al.

Viewed

Total article views: 164 (including HTML, PDF, and XML)

HTML PDF XML Total Supplement BibTeX EndNote
115 44 5 164 6 3 4

Views and downloads (calculated since 21 Dec 2016)

Cumulative views and downloads (calculated since 21 Dec 2016)

Viewed (geographical distribution)

Total article views: 164 (including HTML, PDF, and XML)

Thereof 162 with geography defined and 2 with unknown origin.

Country # Views %
  • 1

Saved

Discussed

Latest update: 26 Feb 2017
Publications Copernicus
Download
Short summary
How should climate model simulations be combined to produce an overall assessment which reflects both their performance and their interdependencies. This paper presents a strategy for weighting climate model output such that models which are replicated or models which perform poorly in a chosen set of metrics are appropriately downweighted. We perform sensitivity tests to show how the method results depend on variables and parameter values.
How should climate model simulations be combined to produce an overall assessment which reflects...
Share