Refsgaard, J. C.16; Madsen, H.8; Andréassian, V.17; Arnbjerg-Nielsen, Karsten1; Davidson, T. A.10; Drews, Martin3; Hamilton, D. P.11; Jeppesen, E.10; Kjellström, E.12; Olesen, J. E.10; Sonnenborg, T. O.16; Trolle, Didde13; Willems, P.14; Christensen, J. H.15
1 Department of Environmental Engineering, Technical University of Denmark2 Urban Water Engineering, Department of Environmental Engineering, Technical University of Denmark3 Department of Management Engineering, Technical University of Denmark4 Systems Analysis, Department of Management Engineering, Technical University of Denmark5 DTU Climate Centre, Systems Analysis, Department of Management Engineering, Technical University of Denmark6 Energy Systems Analysis, Systems Analysis, Department of Management Engineering, Technical University of Denmark7 Geological Survey of Denmark and Greenland8 DHI Denmark9 Irstea10 Aarhus University11 University of Waikato12 Swedish Meteorological and Hydrological Institute13 unknown14 Katholieke Universiteit15 Danish Meteorological Institute16 Geological Survey of Denmark and Greenland17 Irstea
Models used for climate change impact projections are typically not tested for simulation beyond current climate conditions. Since we have no data truly reflecting future conditions, a key challenge in this respect is to rigorously test models using proxies of future conditions. This paper presents a validation framework and guiding principles applicable across earth science disciplines for testing the capability of models to project future climate change and its impacts. Model test schemes comprising split-sample tests, differential split-sample tests and proxy site tests are discussed in relation to their application for projections by use of single models, ensemble modelling and space-time-substitution and in relation to use of different data from historical time series, paleo data and controlled experiments. We recommend that differential-split sample tests should be performed with best available proxy data in order to build further confidence in model projections.
Climatic Change, 2014, Vol 122, Issue 2-2, p. 271-282