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

BER Research Highlights


Improving Atmospheric Chemistry in Climate Models
Published: February 07, 2013
Posted: April 18, 2013

Climate model simulations include the influences of atmospheric chemistry and aerosols, yet there are uncertainties in how models formulate and parameterize chemistry, aerosols, and their influence on Earth’s radiation, clouds, and other climate features. The latest phase of the international Climate Model Intercomparison Project (CMIP) included a parallel effort in which model groups compared the treatment and effect of chemistry and aerosols in climate models (Atmospheric Chemistry and Climate Model Intercomparison Project; ACCMIP). An international group of scientists, including U.S. Department of Energy researchers at Pacific Northwest and Lawrence Livermore National Laboratories, participated. The project consisted of a series of single time-slice experiments targeting long-term changes in atmospheric composition between 1850 and 2100. The focus was to document composition changes and the associated radiative forcing during this period. The team studied 16 ACCMIP models in a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes, and interaction with radiation and clouds. While the groups specified anthropogenic and biomass burning emissions for all time slices in the ACCMIP protocol, they found that natural emissions are responsible for a significant range across models, especially in the case of ozone precursors. Model-to-model comparisons of changes in temperature, specific humidity, and zonal wind between 1850 and 2000 and between 2000 and 2100 were mostly consistent; however, simulated meteorology for some outlier models was different enough to significantly affect their atmospheric chemistry simulations. Isolation and comparison of the chemistry and aerosol effects on climate, as performed in this exercise, will be an important element of understanding overall climate change within the CMIP experiments.

Reference: Lamarque, J.-F., D. T. Shindell, B. Josse, P. J. Young, I. Cionni, V. Eyring, D. Bergmann, P. Cameron-Smith, W. J. Collins, R. Doherty, S. Dalsoren, G. Faluvegi, G. Folberth, S. J. Ghan, L. W. Horowitz, Y. H. Lee, I. A. MacKenzie, T. Nagashima, V. Naik, D. Plummer, M. Righi, S. T. Rumbold, M. Schulz, R. B. Skeie, D. S. Stevenson, S. Strode, K. Sudo, S. Szopa, A. Voulgarakis, and G. Zeng. 2013. “The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): Overview and Description of Models, Simulations, and Climate Diagnostics” Geoscientific Model Development 6, 179–206. DOI: 10.5194/gmd-6-179-2013. (Reference link)

Contact: Renu Joseph, SC-23.1, (301) 903-9237, Dorothy Koch, SC-23.1, (301) 903-0105
Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Atmospheric System Research

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)