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@INPROCEEDINGS{Liu:884299,
      author       = {Liu, M. and Huang, Y. and Hoffmann, Lars and Huang, C. and
                      Chen, P. and Heng, Y.},
      title        = {{H}igh-{R}esolution {S}ource {E}stimation of {V}olcanic
                      {S}ulfur {D}ioxide {E}missions {U}sing {L}arge-{S}cale
                      {T}ransport {S}imulations},
      volume       = {12139},
      address      = {Cham},
      publisher    = {Springer},
      reportid     = {FZJ-2020-03185},
      series       = {Lecture Notes in Computer Science},
      pages        = {60-73},
      year         = {2020},
      comment      = {Computational Science – ICCS 2020},
      booktitle     = {Computational Science – ICCS 2020},
      abstract     = {High-resolution reconstruction of emission rates from
                      different sources is essential to achieve accurate
                      simulations of atmospheric transport processes. How to
                      achieve real-time forecasts of atmospheric transport is
                      still a great challenge, in particular due to the large
                      computational demands of this problem. Considering a case
                      study of volcanic sulfur dioxide emissions, the codes of the
                      Lagrangian particle dispersion model MPTRAC and an inversion
                      algorithm for emission rate estimation based on sequential
                      importance resampling are deployed on the Tianhe-2
                      supercomputer. The high-throughput based parallel computing
                      strategy shows excellent scalability and computational
                      efficiency. Therefore, the spatial-temporal resolution of
                      the emission reconstruction can be improved by increasing
                      the parallel scale. In our study, the largest parallel scale
                      is up to 1.446 million compute processes, which allows us to
                      obtain emission rates with a resolution of 30 min in time
                      and 100 m in altitude. By applying massive-parallel
                      computing systems such as Tianhe-2, real-time source
                      estimation and forecasts of atmospheric transport are
                      becoming feasible.},
      month         = {Jun},
      date          = {2020-06-03},
      organization  = {International Conference on
                       Computational Science 2020, Amsterdam
                       (The Netherlands), 3 Jun 2020 - 5 Jun
                       2020},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / DFG project 410579391 - Transportwege für
                      Aerosol und Spurengase im Asiatischen Monsun in der oberen
                      Troposphäre und unteren Stratosphäre},
      pid          = {G:(DE-HGF)POF3-511 / G:(GEPRIS)410579391},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      UT           = {WOS:000841756000005},
      doi          = {10.1007/978-3-030-50420-5_5},
      url          = {https://juser.fz-juelich.de/record/884299},
}