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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},
}