U.S. Department of Energy Office of Biological and Environmental Research

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Uncertainty Quantification Framework Applied to Community Land Model Reveals Uncertainty in Model Hydrology
Published: June 27, 2012
Posted: November 01, 2012

Many aspects of land hydrology in climate models are uncertain and important for correctly simulating climate and cloud changes. A new, more precise system of estimating land model uncertainties has been designed and implemented in the Community Land Model (CLM4) by U.S. Department of Energy scientists at Pacific Northwest National Laboratory and Oak Ridge National Laboratory. They analyzed the sensitivity of simulated surface heat and energy fluxes to selected hydrologic parameters in CLM4 by applying a new method of uncertainty quantification (UQ) to 13 Ameriflux tower sites that span a wide range of climate conditions and provide measurements of surface water, energy, and carbon fluxes. UQ is used to select the most influential CLM parameters for increased focus and research. The results suggest that the CLM4 simulated latent/sensible heat fluxes show the largest sensitivity to parameters associated with subsurface runoff. This work is the first UQ study on the CLM4 and has demonstrated that uncertainties in hydrologic parameters could have significant impacts on the simulated water and energy fluxes and land surface states, which will in turn affect atmospheric processes and the carbon cycle.

Reference: Hou, Z., M. Huang, L. R. Leung, G. Lin, and D. M. Ricciuto. 2012. “Sensitivity of Surface Flux Simulations to Hydrologic Parameters Based on an Uncertainty Quantification Framework Applied to the Community Land Model,” Journal of Geophysical Research Atmospheres, DOI: 10.1029/2012JD017521. (Reference link)

Contact: Dorothy Koch, SC-23.1, (301) 903-0105
Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Terrestrial Ecosystem Science
  • Research Area: Carbon Cycle, Nutrient Cycling

Division: SC-23.1 Climate and Environmental Sciences Division, BER

 

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