Overview of Recent Progress at Oak Ridge National Laboratory toward Next Generation Land Components of Earth System Models
Abstract
We present an overview of the recent results from the Oak Ridge National Laboratory land modeling team toward the Climate Science for a Sustainable Energy Future (CSSEF) project. One of the goals of the CSSEF project is to improve and accelerate the climate model development process leading toward the 6th generation of the Community Earth System Model (CESM3). Here we focus on subgrid scale land hydrology modeling, separation of the above and below ground litter and soil organic matter pools, and parameter sensitivity studies using the Community Land Model (CLM) to improve uncertainty quantification (UQ). On the subgrid land hydrology subproject, the effects of using the available higher resolution land cover and soil texture data sets (15 to 30 arcsecond) to increase the heterogeneity within a typical half degree latitude and longitude land model grid cell were tested by doing model simulations with CLM4 at increasingly higher resolutions near the Niwot Ridge North American Carbon Program (NACP) site. Another central objective of the project is detailed quantification of Earth system model prediction uncertainty. The overall uncertainty quantification approach, from the perspective of land model evaluation and development, is to first characterize uncertainty in model parameter values, then to quantify the components of that prediction uncertainty (e. g. parameter uncertainty, structural uncertainty, and model forcings). As a first step toward these goals, at another NACP site, University of Michigan Biological Station, parameters within CLM were systematically varied to characterize uncertainty in model parameter values.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2011
- Bibcode:
- 2011AGUFM.B31D0353B
- Keywords:
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- 0428 BIOGEOSCIENCES / Carbon cycling;
- 1622 GLOBAL CHANGE / Earth system modeling;
- 1847 HYDROLOGY / Modeling;
- 3275 MATHEMATICAL GEOPHYSICS / Uncertainty quantification