Generation of Spatial Profiles and Mapping of Volcanic Ash Distribution

Defining spatial distribution of airborne volcanic ash in the neighbourhood an erupting volcano is a synoptic scale problem, severely impacting lives and livelihoods. Robust algorithms are needed to model such complex phenomenon from sparse field data. This study investigated optimal modelling dispersion using Empirical Bayesian Kriging (EBK): geostatistical, probabilistic algorithm. Both distance temperature values samples 2010 Icelandic eruption were spatially correlated semivariograms generate prediction error surfaces. Results showed that block averages 90% accurate as validated against NCEP NWP The work supports utility EBK datasets where autocorrelation not significant. Furthermore, results could help risk maps delineate safety zones for aircrafts.