A framework for benchmarking land models

Luo, Y.Q.; Randerson, J.T.; Abramowitz, G.; Bacour, C.; Blyth, E. ORCID: https://orcid.org/0000-0002-5052-238X; Carvalhais, N.; Ciais, P.; Dalmonech, D.; Fisher, J.B.; Fisher, R.; Friedlingstein, P.; Hibbard, K.; Hoffman, F.; Huntzinger, D.; Jones, C.D.; Koven, C.; Lawrence, D.; Li, D.J.; Mahecha, M.; Niu, S.L.; Norby, R.; Piao, S.L.; Qi, X.; Peylin, P.; Prentice, I.C.; Riley, W.; Reichstein, M.; Schwalm, C.; Wang, Y.P.; Xia, J.Y.; Zaehle, S.; Zhou, X.H.. 2012 A framework for benchmarking land models. Biogeosciences, 9 (10). 3857-3874. https://doi.org/10.5194/bg-9-3857-2012

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Abstract/Summary

Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models to improve their prediction performance skills.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.5194/bg-9-3857-2012
Programmes:	CEH Topics & Objectives 2009 - 2012 > Water > WA Topic 3 - Science for Water Management > WA - 3.3 - Better represent hydrological and biogeochemical processes in Earth System Models
UKCEH and CEH Sections/Science Areas:	Reynard
ISSN:	1726-4170
Additional Information. Not used in RCUK Gateway to Research.:	This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Additional Keywords:	benchmarking
NORA Subject Terms:	Meteorology and Climatology
Date made live:	19 Oct 2012 10:42 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/19977

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