Lenard Röder: Sequential Monte Carlo Filters for Atmospheric Field Experiments

  • Date: May 18, 2022
  • Speaker: Lenard Röder
Atmospheric field experiments create unique datasets and cannot be repeated to increase data coverage or precision. However, many observables are closely connected through chemical reactions. Can this dependence be used to decrease uncertainty of poorly measured variables with the help of high precision measurements? Yes – the sequential monte carlo filter combines prior knowledge of a variable through system dynamics with actual measurements in a Bayesian way.
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