Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2017-238
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
23 Nov 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).
On the importance of multiple-component evaluation of spatial patterns for optimization of earth system models – A case study using mHM v5.6 at catchment scale
Julian Koch, Mehmet C. Demirel, and Simon Stisen Department of Hydrology, Geological Survey of Denmark and Greenland, Copenhagen, 1350, Denmark
Abstract. The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well tested toolbox of metrics to evaluate temporal model performance. On the contrary, spatial performance evaluation is not corresponding to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex earth system processes. This study makes a contribution towards advancing spatial pattern oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial pattern oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics, because stand-alone metrics tend to fail to provide holistic pattern information to the optimizer. The three SPAEF components are found to be independent which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms this study suggests applying bias insensitive metrics which further allow comparing variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.6), but we see great potential across disciplines related to spatial distributed earth system modelling.

Citation: Koch, J., Demirel, M. C., and Stisen, S.: On the importance of multiple-component evaluation of spatial patterns for optimization of earth system models – A case study using mHM v5.6 at catchment scale, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-238, in review, 2017.
Julian Koch et al.
Julian Koch et al.
Julian Koch et al.

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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 to such a comparison and suggest to use 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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