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New Method to Improve Use of Aerosol Data in Climate Models
Published: April 25, 2013
Posted: July 18, 2013

Investigation of aerosol-related issues such as aerosol-cloud interactions and evaluation of model-simulated aerosol indirect effects against observations often require a multiscale aerosol dataset. However, despite great advances in aerosol measurements (such as those conducted by the U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) program), measurements alone often cannot satisfy all the requirements. In recent DOE-funded work carried out jointly by researchers at the Jet Propulsion Laboratory, University of California at Los Angeles, and Brookhaven National Laboratory, a three-dimensional (3D) variational data assimilation (3DVAR) system for aerosols was developed for WRF/Chem. This WRF/Chem-based 3DVAR system simultaneously provides not only mass concentrations but also number concentrations of multiple species in multiple size bins, representing one of the most comprehensive and sophisticated aerosol data assimilation schemes. This system also incorporates novel formulations to reduce the computational cost incurred by a large number of analysis variables, which is crucial for aerosol data assimilation in generating multiyear aerosol reanalysis. The multiscale data generated by the system offer 3D aerosol fields that can be utilized for both driving and initializing atmospheric models and evaluating related model performance. This research is underway.

Reference: Li, Z., Z. Zang, Q. B. Li, Y. Chao, D. Chen, Z. Ye, Y. Liu, and K. N. Liou. 2013. “A Three-Dimensional Variational Data Assimilation System for Multiple Aerosol Species with WRF/Chem and an Application to PM2.5 Prediction,” Atmospheric Chemistry and Physics 13, 4265–78. DOI: 10.5194/acp-13-1-2013. (Reference link)

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

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

Division: SC-33.1 Earth and Environmental Sciences Division, BER

 

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