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@ARTICLE{Paugam:189272,
author = {Paugam, R. and Wooster, M. and Atherton, J. and Freitas, S.
R. and Schultz, Martin and Kaiser, J. W.},
title = {{D}evelopment and optimization of a wildfire plume rise
model based on remote sensing data inputs – {P}art 2},
journal = {Atmospheric chemistry and physics / Discussions},
volume = {15},
number = {6},
issn = {1680-7375},
address = {Katlenburg-Lindau},
publisher = {EGU},
reportid = {FZJ-2015-02450},
pages = {9815 - 9895},
year = {2015},
abstract = {Biomass burning is one of a relatively few natural
processes that can inject globally significant quantities of
gases and aerosols into the atmosphere at altitudes well
above the planetary boundary layer, in some cases at heights
in excess of 10 km. The "injection height" of biomass
burning emissions is therefore an important parameter to
understand when considering the characteristics of the smoke
plumes emanating from landscape scale fires, and in
particular when attempting to model their atmospheric
transport. Here we further extend the formulations used
within a popular 1D plume rise model, widely used for the
estimation of landscape scale fire smoke plume injection
height, and develop and optimise the model both so that it
can run with an increased set of remotely sensed
observations. The model is well suited for application in
atmospheric Chemistry Transport Models (CTMs) aimed at
understanding smoke plume downstream impacts, and whilst a
number of wildfire emission inventories are available for
use in such CTMs, few include information on plume injection
height. Since CTM resolutions are typically too spatially
coarse to capture the vertical transport induced by the heat
released from landscape scale fires, approaches to estimate
the emissions injection height are typically based on
parametrizations. Our extensions of the existing 1D plume
rise model takes into account the impact of atmospheric
stability and latent heat on the plume up-draft, driving it
with new information on active fire area and fire radiative
power (FRP) retrieved from MODIS satellite Earth Observation
(EO) data, alongside ECMWF atmospheric profile information.
We extend the model by adding an equation for mass
conservation and a new entrainment scheme, and optimise the
values of the newly added parameters based on comparison to
injection heights derived from smoke plume height retrievals
made using the MISR EO sensor. Our parameter optimisation
procedure is based on a twofold approach using sequentially
a Simulating Annealing algorithm and a Markov chain Monte
Carlo uncertainty test, and to try to ensure the appropriate
convergence on suitable parameter values we use a training
dataset consisting of only fires where a number of specific
quality criteria are met, including local ambient wind shear
limits derived from the ECMWF and MISR data, and "steady
state" plumes and fires showing only relatively small
changes between consecutive MODIS observations. Using our
optimised plume rise model (PRMv2) with information from all
MODIS-detected active fires detected in 2003 over North
America, with outputs gridded to a 0.1° horizontal and 500
m vertical resolution mesh, we are able to derive wildfire
injection height distributions whose maxima extend to the
type of higher altitudes seen in actual observation-based
wildfire plume datasets than are those derived either via
the original plume model or any other parametrization tested
herein. We also find our model to be the only one tested
that more correctly simulates the very high plume (6 to 8 km
a.s.l.), created by a large fire in Alberta (Canada) on the
17 August 2003, though even our approach does not reach the
stratosphere as the real plume is expected to have done. Our
results lead us to believe that our PRMv2 approach to
modelling the injection height of wildfire plumes is a
strong candidate for inclusion into CTMs aiming to represent
this process, but we note that significant advances in the
spatio-temporal resolutions of the data required to feed the
model will also very likely bring key improvements in our
ability to more accurately represent such phenomena, and
that there remain challenges to the detailed validation of
such simulations due to the relative sparseness of plume
height observations and their currently rather limited
temporal coverage which are not necessarily well matched to
when fires are most active (MISR being confined to morning
observations for example).},
cin = {IEK-8},
ddc = {550},
cid = {I:(DE-Juel1)IEK-8-20101013},
pnm = {243 - Tropospheric trace substances and their
transformation processes (POF3-243)},
pid = {G:(DE-HGF)POF3-243},
typ = {PUB:(DE-HGF)16},
doi = {10.5194/acpd-15-9815-2015},
url = {https://juser.fz-juelich.de/record/189272},
}