Abstract:Abstract. In this study we explore the applications and limitations of Sequential Monte Carlo filters (SMC) to atmospheric chemistry field experiments. The proposed algorithm is simple, fast, versatile and returns a complete probability distribution. It combines information from measurements with known system dynamics to decrease the uncertainty of measured variables. The method shows high potential to increase data coverage, precision and even possibilities to infer unmeasured variables. We extend the origina… Show more
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