Machine learning emulation of spatial deposition from a multi-physics ensemble of weather and atmospheric transport models

HIGHLIGHTS

  • who: Nipun Gunawardena et al. from the Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA have published the paper: Machine Learning Emulation of Spatial Deposition from a Multi-Physics Ensemble of Weather and Atmospheric Transport Models, in the Journal: Atmosphere 2021, 12, 953. of 24/04/2018
  • what: For the work , the authors use a specific version of FLEXPART designed to work directly with WRF output (FLEXPART-WRF version 3.3). The authors focus specifically on uncertainty due to meteorological modeling. Much of the prior emulation work focused on the . . .

     

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