Ensemble Prediction of the Dispersion of Volcanic Ash from the 13 February 2014 Eruption of Kelut, Indonesia
A meteorological ensemble prediction system that represents uncertainties in both initial conditions and model formulations is coupled with a modified version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. This coupled dispersion ensemble prediction system (DEPS) is...
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Veröffentlicht in: | Journal of applied meteorology and climatology 2016-01, Vol.55 (1), p.61-78 |
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Sprache: | eng |
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Zusammenfassung: | A meteorological ensemble prediction system that represents uncertainties in both initial conditions and model formulations is coupled with a modified version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. This coupled dispersion ensemble prediction system (DEPS) is used to generate a 24-member ensemble forecast of the dispersion of the volcanic ash cloud produced by the 13 February 2014 eruption of Kelut, Indonesia. Uncertainties in the volcanic ash source are not represented. For predictions up to 12 h from the start of the eruption, forecasts from the deterministic control member and from the DEPS both show very good qualitative agreement with satellite observations. By 18–24 h the DEPS forecast shows better qualitative agreement with observations than does the deterministic forecast. Although composited fields such as the ensemble mean and probability present information concisely, experiments here show that it is very important to also consider results from individual member forecasts in order to identify features that may be underrepresented. For example, an area of relatively high ash concentration that was forecast by most of the members was not particularly evident in the composited fields because the location of this feature was highly variable between member forecasts. To fully understand a DEPS forecast, it is necessary to consider both atmospheric column load and concentration fields, individual member forecasts, and a range of thresholds in computing and interpreting probabilities. |
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ISSN: | 1558-8424 1558-8432 |
DOI: | 10.1175/jamc-d-15-0079.1 |