Probabilistic Hazard Assessment (PHA) provides an appropriate methodology for assessing space weather hazard and its impact on technology. PHA is widely used in the geosciences to determine the probability of exceedance of critical thresholds, caused by one or more hazard sources. PHA has proved useful where there are limited historical data to estimate the likelihood of specific impacts. PHA has also driven the development of empirical and physical models, or ensembles of models, to replace measured data. Here we aim to highlight the PHA method to the space weather community and provide an example of it could be used. In terms of space weather impact, the critical hazard thresholds might include the Geomagnetically Induced Current in a specific high voltage power transformer neutral, or the local pipe-to-soil potential in a particular metal pipe.
We illustrate PHA in the space weather context by applying it to a twelve-year dataset of Earth-directed solar Coronal Mass Ejections (CME), which we relate to the probability that the global three-hourly geomagnetic activity index K p exceeds specific thresholds. We call this a ‘Probabilistic Geomagnetic Hazard Assessment’, or PGHA. This provides a simple but concrete example of the method. We find that the cumulative probability of K p > 6-, > 7-, > 8- and K p = 9o is 0.359, 0.227, 0.090, 0.011, respectively, following observation of an Earth-directed CME, summed over all CME launch speeds and solar source locations. This represents an order of magnitude increase in the a priori probability of exceeding these thresholds, according to the historical K p distribution. For the lower Kp thresholds, the results are distorted somewhat by our exclusion of coronal hole high speed stream effects. The PGHA also reveals useful (for operational forecasters) probabilistic associations between solar source location and subsequent maximum Kp .