Quantitative Verification and Calibration of Volcanic Ash Ensemble Forecasts Using Satellite Data

In this paper, we address the problem of verifying and calibrating ensemble‐based probabilistic volcanic ash forecasts. The ensemble members are constructed from dispersion model simulations with different meteorological fields obtained from an ensemble meteorological forecast model and different values of ash source parameters such as ash column height and vertical mass distribution. The Brier score is employed to verify the probabilistic forecasts relative to binary‐valued ash detection fields and fully quantitative satellite‐retrieved ash mass load fields. A new ensemble forecast calibration methodology, which treats the meteorological and source term variations on equal footing, is also developed. This enables the creation of an ensemble subset yielding higher Brier skill scores than the uncalibrated ensemble during a calibration time window of about 6 hr after the start of an eruption. It is shown that this can be used to improve probabilistic forecasts up to 24 hr after the start of the eruption using the Indonesian 13 February 2014 Kelut and 6 November 2015 Rinjani eruptions as case studies. Key Points The use of ensembles of meteorological fields is shown quantitatively to improve volcanic ash forecasts The use of observations to calibrate the ensemble forecasts is shown quantitatively to further improve volcanic ash forecasts Calibrating ash source term parameters in addition to meteorological ensemble members is shown to further improve forecast skill