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| DPRI Kyoto and Cabot Institute |
Over the last
two days a group from the Cabot Institute has been holding a workshop with
colleagues from Kyoto University’s Disaster Prevention Research Institute (or
DPRI) on the topic of probabilistic hazard analysis. On the face of it Japan and the UK are very
similar: highly urbanised and complex island societies with high population
densities and therefore the potential for serious disruption if natural hazards
occur. Mind you, the earthquake, tsunami
and volcano hazards do put Japan in a different league when it comes to
potential impacts. In both countries,
robust hazard analysis, planning and decision making is therefore essential to
protecting society. Both countries have
a lot to learn from each other, and our recent paper on lessons for the UK from
the Fukushima disaster is a case in point.
Cabot members
Wendy Larner, Colin Taylor, Susanna Jenkins, Jeremy Phillips, Katsu Goda,
Philippa Bayley and myself (Paul Bates) spent two days working with around 30
Japanese colleagues, with Skype presentations from the UK delivered by WillyAspinall, Jonty Rougier and Tamsin Edwards.
A full programme of the meeting is on our website,
and includes pdfs of the presentations for download. We learned a huge amount about hazard
research in Japan and have hopefully begun a large number of research
collaborations that will be important for Bristol University for many
years. Our profound thanks go to our
Japanese hosts Prof. Eiichi Nakahita and Prof. Hirokazu Tatano, and to the
Director of DPRI, Prof. Nakashima. The
photos here give a flavour of the wonderful time we had.
Possibly the
most important theme to emerge from the workshop was that whilst probabilistic
analysis of hazards (where we give the chance of an event occurring rather than
a definite yes/no prediction) is now commonplace in science, there is still a
major issue in educating decision makers, governments and the public in how to
use such forecasts to take decisions.
Indeed the Daily Mail in the UK has recently been giving the Met Office
a hard time for wanting (very sensibly) to move to a probabilistic forecast of
rainfall. This shouldn’t be such a big problem, but the fact that it is tells
us an awful lot. Intrinsically people
deal with probability information all the time: betting and insurance, for example,
are both examples of probabilistic contracts that are well understood by the
public. So why do we resist being told about other risks in a similar way. My gut feeling is that it is to do with the
question of responsibility. A probabilistic forecast of risk forces the
decision maker (be they Ministers, civil servants or the public) to deal with
uncertainty in predictions, whilst insistence on a deterministic forecast puts
the responsibility for this onto the scientists who can then be blamed if things
go wrong.