Global Wildfire Plume-rise Dataset and Parameterizations for Climate
Model Applications
Abstract
The fire plume height (smoke injection height) is an important parameter
for calculating the transport and lifetime of smoke particles, which can
significantly affect regional and global air quality and atmospheric
radiation budget. To develop an observation-based global fire plume-rise
dataset, a modified one-dimensional plume-rise model was used with
observation-based fire size and Maximum Fire Radiative Power (MFRP)
data, which are derived from satellite fire hotspot measurements. The
resulting dataset captured well the observed plume height distribution
derived from the Multi-angle Imaging SpectroRadiometer (MISR)
measurements. The fraction of fire plumes penetrating above the boundary
layer is relatively low at 20% at the time of MISR observation (10:30
am LT) but increases to an average of ~55% in the late
afternoon implying a sampling bias in MISR measurements, which requires
corrections through dynamic modeling or parameterization of fire plume
height as a function of meteorological and fire conditions when the
dataset is applied in climate model simulations. We conducted
sensitivity simulations using the Community Atmospheric Models version 5
(CAM5). Model results show that the incorporation of fire plume rise in
the model tends to significantly increase fire aerosol impacted regions.
We applied the offline plume rise data to develop an online fire plume
height parameterization, allowing for simulating the feedbacks of
climate/weather on fire plume rise in climate models.