Characterizing the diurnal patterns of errors in the prediction of evapotranspiration by several land-surface models: An NACP analysis

Ashley M. Matheny, Gil Bohrer, Paul C. Stoy, Ian T. Baker, Andy T. Black, Ankur R. Desai, Michael C. Dietze, Chris M. Gough, Valeriy Y. Ivanov, Rachhpal S. Jassal, Kimberly A. Novick, Karina V.R. Schäfer, Hans Verbeeck

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46 Scopus citations


Land-surface models use different formulations of stomatal conductance and plant hydraulics, and it is unclear which type of model best matches the observed surface-atmosphere water flux. We use the North American Carbon Program data set of latent heat flux (LE) measurements from 25 sites and predictions from 9 models to evaluate models’ ability to resolve subdaily dynamics of transpiration. Despite overall good forecast at the seasonal scale, the models have difficulty resolving the dynamics of intradaily hysteresis. The majority of models tend to underestimate LE in the prenoon hours and overestimate in the evening. We hypothesize that this is a result of unresolved afternoon stomatal closure due to hydrodynamic stresses. Although no model or stomata parameterization was consistently best or worst in terms of ability to predict LE, errors in model-simulated LE were consistently largest and most variable when soil moisture was moderate and vapor pressure deficit was moderate to limiting. Nearly all models demonstrate a tendency to underestimate the degree of maximum hysteresis which, across all sites studied, is most pronounced during moisture-limited conditions. These diurnal error patterns are consistent with models’ diminished ability to accurately simulate the natural hysteresis of transpiration. We propose that the lack of representation of plant hydrodynamics is, in part, responsible for these error patterns.

Original languageEnglish (US)
Pages (from-to)1458-1473
Number of pages16
JournalJournal of Geophysical Research G: Biogeosciences
Issue number7
StatePublished - Jul 31 2014

All Science Journal Classification (ASJC) codes

  • Soil Science
  • Forestry
  • Water Science and Technology
  • Palaeontology
  • Atmospheric Science
  • Aquatic Science
  • Ecology

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