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

BER Research Highlights

Evaluating Land-Atmosphere Coupling in Earth System Model Simulations
Published: November 09, 2017
Posted: January 22, 2018

ARM observations were used to evaluate the land-atmosphere coupling in an Earth system model; the model’s overly strong coupling may contribute to the warm and dry bias in its simulations over the Southern Great Plains region.

The Science
The land surface and the lower atmosphere interact with each other through exchanges of water, energy, and momentum.  These interactions, known as land-atmosphere coupling, can influence regional surface temperature, evaporation, and precipitation and therefore need to be captured correctly in weather and Earth system models.  DOE-funded researchers used observations from the Atmospheric Radiation Measurement (ARM) facility to investigate land-atmosphere coupling strength over the U.S. Southern Great Plains (SGP) region, with a particular focus on the role of soil moisture. These field observations were then used to evaluate simulations of land-atmosphere coupling in an Earth system model. 

The Impact
This research confirms that in the Earth system model, the soil moisture exerts an outsized influence on the model’s weather and climate projections in the Southern Great Plains.  The overly strong impact of soil moisture may be a contributing factor to a large regional warm/dry bias in the model in this region that is typical of current Earth system models. The unrealistically strong land-atmosphere coupling in both the free-running and controlled climate simulation points to the model’s land-atmosphere coupling mechanisms--rather than its simulation of soil moisture or surface atmospheric variables--as the chief source of the problem. Future work will focus on analyzing these model coupling mechanisms in more detail.

Several independent measurements of warm-season soil moisture and surface atmospheric variables recorded at the ARM Southern Great Plains (SGP) research facility were used to estimate land-atmosphere coupling strength. The observations revealed substantial variation in coupling strength, as estimated from three soil moisture measurements at a single site, as well as across six other sites having varied soil and land cover types. The observational estimates then served as references for evaluating SGP terrestrial coupling strength in the Community Atmospheric Model version 5.1 (CAM 5.1) coupled to the Community Land Model version 4 (CLM4).  The model was run in two configurations over the study period: 1) a “free-running” atmospheric simulation with prescribed observations of ocean surface temperatures; and 2) a “controlled” atmospheric simulation having the same ocean boundary condition, but in which model soil moisture and atmospheric state variables were corrected daily from observationally based approximations of these fields. The controlled simulation deviated less from the observed surface climate than its free-running counterpart, but the land-atmosphere coupling in both configurations was much stronger, and displayed less spatial variability, than the SGP observational estimates. These results imply that model physical parameterizations involved in the coupling of CAM5.1/CLM4 land and atmospheric components are likely to be the main sources of the problematical land-atmosphere coupling behaviors.

Contacts (BER PM)
Sally McFarlane
ARM Program Manager

Shaima Nasiri
ASR Program Manager

Ashley Williamson
ASR Program Manager

Renu Joseph
RGCM Program Manager

(PI Contact)
Thomas J. Phillips
Lawrence Livermore National Laboratory

We acknowledge the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for funding the recording of CO2FLX, EBBR, and SWATS soil moisture and the ARMBE and other atmospheric data sets. The work of T. J. P., S. A. K., Y. M., Q. T., and S. X. was funded by the U.S. Department of Energy Office of Science under its ARM, Atmospheric System Research (ASR), and Regional and Global Modeling (RGCM) programs and was performed at the Lawrence Livermore National Laboratory under contract DE-AC52 07NA27344. INW and MST were supported by the U.S. Department of Energy Atmospheric System Research under contract DE-AC02-05CH11231. The work of D. R. C. was funded by the U.S. Department of Energy Office of Science under its ARM Program and was performed at Argonne National Laboratory under contract DE-AC02-06CH11357.

Phillips, T., S. Klein, H. Ma, Q. Tang, S. Xie, I. Williams, J. Santanello, D. Cook, and M. Torn. 2017. "Using ARM Observations to Evaluate Climate Model Simulations of Land-Atmosphere Coupling on the U.S. Southern Great Plains." Journal of Geophysical Research: Atmospheres 122:11524-11548. doi: 10.1002/2017JD027141.


Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Atmospheric System Research
  • Facility: DOE ARM User Facility

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)