Articles | Volume 11, issue 5
https://doi.org/10.5194/gmd-11-1873-2018
https://doi.org/10.5194/gmd-11-1873-2018
Methods for assessment of models
 | 
15 May 2018
Methods for assessment of models |  | 15 May 2018

The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

Julian Koch, Mehmet Cüneyd Demirel, and Simon Stisen

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Cited articles

Alexandrov, G. A., Ames, D., Bellocchi, G., Bruen, M., Crout, N., Erechtchoukova, M., Hildebrandt, A., Hoffman, F., Jackisch, C., Khaiter, P., Mannina, G., Matsunaga, T., Purucker, S. T., Rivington, M., and Samaniego, L.: Technical assessment and evaluation of environmental models and software: Letter to the Editor, Environ. Model. Softw., 26, 328–336, https://doi.org/10.1016/j.envsoft.2010.08.004, 2011. 
Brown, B. G., Gotway, J. H., Bullock, R., Gilleland, E., Fowler, T., Ahijevych, D., and Jensen, T.: The Model Evaluation Tools (MET): Community tools for forecast evaluation, in: Preprints, 25th Conf. on International Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, Phoenix, AZ, Amer. Meteor. Soc. A, Vol. 9, 2009. 
Clark, M. P., Kavetski, D., and Fenicia, F.: Pursuing the method of multiple working hypotheses for hydrological modeling, Water Resour. Res., 47, W09301, https://doi.org/10.1029/2010WR009827, 2011. 
Cloke, H. L. and Pappenberger, F.: Evaluating forecasts of extreme events for hydrological applications: An approach for screening unfamiliar performance measures, Meteorol. Appl., 15, 181–197, 2008. 
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Short summary
Our work addresses a key challenge in earth system modelling: how to optimally exploit the information contained in satellite remote sensing observations in the calibration of such models. For this we thoroughly test a number of measures that quantify the fit between an observed and a simulated spatial pattern. We acknowledge the difficulties associated with such a comparison and suggest using measures that regard multiple aspects of spatial information, i.e. magnitude and variability.