4.7 Article

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

期刊

JOURNAL OF CLIMATE
卷 31, 期 8, 页码 2995-3008

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-16-0177.1

关键词

Ecological models; Hydrologic models; Land surface model; Model comparison; Model evaluation; performance

资金

  1. National Key R&D Program of China [2017YFA0603603]
  2. Australian Research Council Discovery Early Career Researcher Award Project [DE120103022]
  3. Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme [GA01101]
  4. European Union's Horizon 2020 research and innovation programme [641816]
  5. RCN [229771]
  6. Australian Research Council [DE120103022] Funding Source: Australian Research Council

向作者/读者索取更多资源

Water 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 , obtained from fitting the Budyko curve to the ensemble model simulation (1.74), was larger than the best-fit value of 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.

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