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Volume 11, issue 1 | Copyright
Geosci. Model Dev., 11, 195-212, 2018
https://doi.org/10.5194/gmd-11-195-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Methods for assessment of models 17 Jan 2018

Methods for assessment of models | 17 Jan 2018

On the predictability of land surface fluxes from meteorological variables

Ned Haughton et al.
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Cited articles
Abramowitz, G.: Calibration, compensating errors and data-based realism in LSMs, Presentation, 2013.
Abramowitz, G., Leuning, R., Clark, M., and Pitman, A. J.: Evaluating the performance of land surface models, 21, 5468–5481, https://doi.org/10.1175/2008JCLI2378.1, 2010.
Batty, M. and Torrens, P. M.: Modeling complexity: the limits to prediction, Cybergeo Eur. J. Geogr., https://doi.org/10.4000/cybergeo.1035, 2001.
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Short summary
Previous studies indicate that fluxes of heat, water, and carbon between the land surface and atmosphere are substantially more predictable than the performance of the current crop of land surface models would indicate. This study uses simple empirical models to estimate the amount of useful information in meteorological forcings that is available for predicting land surface fluxes. These models can be used as benchmarks for land surface models and may help identify areas ripe for improvement.
Previous studies indicate that fluxes of heat, water, and carbon between the land surface and...
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