A143-0006
Assessment of WRF-Fire’s modeling skill on large wildfires under variable grid spacing and input conditions

Monday, 14 December 2020
Poster
Francis Turney1, Pablo E Saide2, Pedro Angel Jimenez3 and Domingo Munoz-Esparza3, (1)University of California Los Angeles, Los Angeles, CA, United States, (2)University of California Los Angeles, Institute of the Environment and Sustainability (IoES), Los Angeles, CA, United States, (3)National Center for Atmospheric Research, Research Applications Laboratory, Boulder, CO, United States
Abstract:
WRF-fire, a coupled atmospheric-fire-spread model, has been shown to possess skill in simulating large wildfires in the Western U.S. Here, using the July 2018 California Carr Fire and August 2019 Washington State Williams Flats Fire as case studies, we examine model skill under a variety of configurations that may allow for either faster computational time or improved comparison with reality such as grid spacing, terrain smoothing, meteorological forcing, lake resolution, and fuel moisture inputs. We ran the model as a base simulation on a 1km mesoscale domain and ~100m LES domain with 9s lake/land use data and ~10m fire grid spacing. We demonstrate the potential to asses WRF-Fire’s outputs against burned area, Fire Radiative Power, and fire counts retrieved by satellite or plane from GOES, VIIRS, and NIROPS.
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