3:30 PM - 4:45 PM
[MIS26-P03] Bayesian Estimation of Volcanic Ash Plume Height by Weather Radar Network
Keywords:Volcanic Ash Plume Height, Weather Radar Network, Bayesian Estimation
The authors analyzed a case of the eruption at Mt. Ontake, and concluded that JMA radar echo height showed an over-estimated value compared to the ash plume height deduced from a photo taken at Mt. Aino. Since the data observed by Tokyo radar had a bias because of an anomalous propagation, the composite radar echo height was over-estimated.
To estimate volcanic ash plume height more accurately, the authors introduce a Bayesian estimation method. The procedure to estimate a volcanic ash plume height is as follows: 1. assume that a probability density function (PDF) of each radar echo height follows a normal distribution; 2. multiply the prior probability by the PDFs; 3. normalize the composite PDF. Moreover, Bayesian updating can make the prior probability better. Using the Bayesian method, we can eliminate effects of anomalous propagations. The disadvantage of this method is that, in the case of fewer radar coverage, we can't get accurate estimation. In such a case, the prior probability become more important.
In this presentation, preliminary results of the method will be shown.