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@ARTICLE{Franke:903143,
      author       = {Franke, Philipp and Lange, Anne Caroline and Elbern,
                      Hendrik},
      title        = {{P}article filter based volcanic ash emission inversion
                      applied to a hypothetical sub-{P}linian {E}yjafjallajökull
                      eruption using the chemical component of the {E}nsemble for
                      {S}tochastic {I}ntegration of {A}tmospheric {S}imulations
                      ({ESIAS}-chem) version 1.0},
      journal      = {Geoscientific model development discussions},
      issn         = {1991-9611},
      address      = {Katlenburg-Lindau},
      publisher    = {Copernicus},
      reportid     = {FZJ-2021-04867},
      year         = {2021},
      abstract     = {Abstract. A particle filter based inversion system to
                      derive time- and altitude-resolved volcanic ash emission
                      fluxes along with its uncertainty is presented. For the
                      underlying observation information only vertically
                      integrated ash load data as provided by retrievals from
                      nadir looking imagers mounted on geostationary satellites is
                      assimilated. We aim to estimate the temporally varying
                      emission profile with error margins, along with evidence of
                      its dependencies on wind driven transport patterns within
                      variable observation intervals. Thus, a variety of
                      observation types, although not directly related to volcanic
                      ash, can be utilized to constrain the probabilistic volcanic
                      ash estimate. The system validation addresses the special
                      challenge of ash cloud height analyses in case of
                      observations restricted to bulk column mass loading
                      information, mimicking the typical case of geostationary
                      satellite data. The underlying method rests on a
                      linear-combination of height-time emission finite elements
                      of arbitrary resolution, each of which is assigned to a
                      model run subject to ensemble-based space-time data
                      assimilation. Employing a modular concept, this setup builds
                      the Ensemble for Stochastic Integration of Atmospheric
                      Simulations (ESIAS-chem) that comprises a particle smoother
                      in combination with a discrete-grid ensemble extension of
                      the Nelder-Mead minimization method. The ensemble version of
                      the EURopean Air pollution Dispersion – Inverse Model
                      (EURAD-IM) is integrated into ESIAS-chem but can be replaced
                      by other models. The performance of ESIAS-chem is tested by
                      identical twin experiments. The application of the inversion
                      system to two notional sub-Plinian eruptions of the
                      Eyjafjallajökull with strong ash emission changes with time
                      and injection heights demonstrate the ability of ESIAS-chem
                      to retrieve the volcanic ash emission fluxes from the
                      assimilation of column mass loading data only. However, the
                      analysed emission profiles strongly differ in their levels
                      of accuracy depending of the strength of wind shear
                      conditions. Under strong wind shear conditions at the
                      volcano the temporal and vertical varying volcanic emissions
                      are analyzed up to an error of only 10 $\%$ for the
                      estimated emission fluxes. For weak wind shear conditions,
                      however, analysis errors are larger and ESIAS-chem is less
                      able to determine the ash emission flux variations. This
                      situation, however, can be remedied by extending the
                      assimilation window. In the performed test cases, the
                      ensemble predicts the location of high volcanic ash column
                      mass loading in the atmosphere with a very high probability
                      of > 95 $\%.$ Additionally, the ensemble is able to provide
                      a vertically resolved probability map of high volcanic ash
                      concentrations to a high accuracy for both, high and weak
                      wind shear conditions.},
      cin          = {IEK-8},
      ddc          = {910},
      cid          = {I:(DE-Juel1)IEK-8-20101013},
      pnm          = {2111 - Air Quality (POF4-211)},
      pid          = {G:(DE-HGF)POF4-2111},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.5194/gmd-2021-30},
      url          = {https://juser.fz-juelich.de/record/903143},
}