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@Article{PaugamWoAtFrScKa:2015:Pa2,
               author = "Paugam, R. and Wooster, Martin and Atherton, Jonathan and Freitas, 
                         Saulo Ribeiro de and Schultz, M. G. and Kaiser, J. W.",
          affiliation = "{King’s College London} and {King’s College London} and {King’s 
                         College London} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Institute for Energy and Climate 
                         Research-Troposphere} and {Max Planck Institute for Chemistry}",
                title = "Development and optimization of a wildfire plume rise model based 
                         on remote sensing data inputs - Part 2",
              journal = "Atmospheric Chemistry and Physics Discussion",
                 year = "2015",
               volume = "15",
               number = "6",
                pages = "9815--9895",
             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, in-cluding 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\◦ 5 horizontal and 500m 
                         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 10 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).",
                  doi = "10.5194/acpd-15-9815-2015",
                  url = "http://dx.doi.org/10.5194/acpd-15-9815-2015",
                 issn = "1680-7367",
                label = "lattes: 9873289111461387 4 PaugamWoAtFrScKa:2015:Pa2",
             language = "en",
        urlaccessdate = "29 nov. 2020"
}


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