Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling ...
<!--!introduction!--> Probabilistic forecasting of volcanic ash dispersion typically involves simulating an ensemble of realistic event scenarios to estimate the probability of a particular hazard threshold being exceeded. While the ensemble size, the sampling procedure used, and the desired t...
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| Format: | Conference Object |
| Language: | unknown |
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GFZ German Research Centre for Geosciences
2023
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| Online Access: | https://dx.doi.org/10.57757/iugg23-1575 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5018031 |
| Summary: | <!--!introduction!--> Probabilistic forecasting of volcanic ash dispersion typically involves simulating an ensemble of realistic event scenarios to estimate the probability of a particular hazard threshold being exceeded. While the ensemble size, the sampling procedure used, and the desired threshold all influence the uncertainty in the probability estimate, current practice does not usually quantify and communicate this uncertainty. We present the application of standard statistical methods to estimate the variance in probabilistic ensembles and communicate confidence intervals, using the example of volcanic ash transport from a representative explosive eruption in Iceland. For stochastic (random) sampling of the wind data, we show how the variance of an exceedance probability depends on the threshold of interest and the ensemble size, and illustrate how we can use the relative variance to compare the uncertainty between estimates of probabilities of different magnitudes. Further, we demonstrate how ... : The 28th IUGG General Assembly (IUGG2023) (Berlin 2023) ... |
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