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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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GMD | Articles | Volume 11, issue 5
Geosci. Model Dev., 11, 1873–1886, 2018
https://doi.org/10.5194/gmd-11-1873-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 11, 1873–1886, 2018
https://doi.org/10.5194/gmd-11-1873-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

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 et al.

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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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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.
Our work addresses a key challenge in earth system modelling: how to optimally exploit the...
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