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

BER Research Highlights


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

 

BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER

Recent Highlights

May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]

May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]

May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]

May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]

Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]

List all highlights (possible long download time)