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Investigation and Separation of Turbulent Fluctuations in Airborne Measurements of Volcanic Ash with Optical Particle Counters
Author(s) -
Jónas Elíasson,
Konradin Weber,
Andreas Vogel Thorgeir Pálsson,
Junichi Yoshitani,
Daisuke Miki
Publication year - 2016
Publication title -
journal of disaster research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.332
H-Index - 18
eISSN - 1883-8030
pISSN - 1881-2473
DOI - 10.20965/jdr.2016.p0072
Subject(s) - volcano , turbulence , environmental science , noise (video) , volcanic ash , autocorrelation , meteorology , atmospheric sciences , anomaly (physics) , statistical physics , physics , statistics , geology , mathematics , computer science , seismology , condensed matter physics , artificial intelligence , image (mathematics)
The science of measuring airborne volcanic ash concentrations supports research in such fields as atmospheric environmental science and the modeling of atmospheric pollution from volcanoes, and is thus very valuable to the aviation industry. These measurements show large scatter directly traceable to turbulent fluctuations responsible for diffusing volcanic dust. Before semistationary components in observations can be compared to each other or to simulation results, they must be separated from fluctuations. In the design of the separation process, however, neither seasonal or diurnal periodicity nor random disturbance with known properties exists to serve as a guideline. It has been suggested that fluctuations could be eliminated through repeated convolutions of a simple 3-point filter enough times. The number of convolutions is chosen from the change in the rate of increase of a special variability parameter. When semistationary concentrations are separated from fluctuations, their statistics are compared to turbulence parameters and the autocorrelation of the series. The method is demonstrated using three measurement series from Sakurajima, Japan measured in 2013. It is concluded that this new method is simple and trustworthy where knowledge and experience of the environmental parameters can be utilized to support the results. They indicate a variability of 40% in the relative fluctuations of the PM10 and around 20% of the PM2.5. The relative fluctuations may be considered completely random, but normally distributed rather than a white noise with an evenly distributed variance spectrum.

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