Published in

American Meteorological Society, Journal of Climate, 8(31), p. 2995-3008, 2018

DOI: 10.1175/jcli-d-16-0177.1

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Evaluating Global Land Surface Models in CMIP5: Analysis of Ecosystem Water- and Light-Use Efficiencies and Rainfall Partitioning

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

AbstractWater and carbon fluxes simulated by 12 Earth system models (ESMs) that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) over several recent decades were evaluated using three functional constraints that are derived from both model simulations, or four global datasets, and 736 site-year measurements. Three functional constraints are ecosystem water-use efficiency (WUE), light-use efficiency (LUE), and the partitioning of precipitation P into evapotranspiration (ET) and runoff based on the Budyko framework. Although values of these three constraints varied significantly with time scale and should be quite conservative if being averaged over multiple decades, the results showed that both WUE and LUE simulated by the ensemble mean of 12 ESMs were generally lower than the site measurements. Simulations by the ESMs were generally consistent with the broad pattern of energy-controlled ET under wet conditions and soil water-controlled ET under dry conditions, as described by the Budyko framework. However, the value of the parameter in the Budyko framework ω, obtained from fitting the Budyko curve to the ensemble model simulation (1.74), was larger than the best-fit value of ω to the observed data (1.28). Globally, the ensemble mean of multiple models, although performing better than any individual model simulations, still underestimated the observed WUE and LUE, and overestimated the ratio of ET to P, as a result of overestimation in ET and underestimation in gross primary production (GPP). The results suggest that future model development should focus on improving the algorithms of the partitioning of precipitation into ecosystem ET and runoff, and the coupling of water and carbon cycles for different land-use types.