Probability, Uncertainty and Risk in the Natural Environment

自然灾害给社会和全球经济带来严重问题。英国最近的例子包括2009年和2010年的寒冬，以及格里姆火山和埃亚菲亚德拉火山的爆发，导致航空旅行中断。再往远一点看，2011年上半年，澳大利亚（洪水）、新西兰（地震）、日本（地震和海啸）和美国（飓风）都发生了重大灾害。如果科学家能够提供准确的信息来帮助管理这些事件，那就太好了。然而，这是不现实的，原因有几个：数据通常不完整（例如，并非在所有需要的地点都能得到），而且测量有误差;预测是使用计算机模型作出的，充其量只能近似现实;我们对某些现象的理解因缺乏经验而受到限制（例如，历史上的海啸记录相对有限）。因此，自然灾害科学家必须承认他们所提供的信息的不确定性，并必须将这种不确定性有效地传达给科学用户。然而，这两项任务都不容易。此外，科学家并不总是了解用户想要什么和需要什么;用户自己也常常对不确定性感到不安。尽管存在这些问题，但现代统计方法可用于使用概率论处理复杂系统中的不确定性。与此同时，社会科学研究人员对了解人们如何应对和理解不确定性感兴趣。通过将这两个发展结合在一起，并与来自几个危险领域的科学家沿着与各种用户联系，我们的目标是（a）展示一个通用的框架，用于处理跨危险的不确定性;（B）开发改进的工具，用于交流不确定的信息。这里考虑的通用框架有三个核心组成部分。第一个是对不确定性的处理，这些不确定性来自我们不完善的模型和对任何复杂系统的不完善理解。第二种是将来自各种来源的信息结合起来，这些信息都被认为是相关的：这在事件管理情况下尤其重要，因为决策者必须根据可能明显相互矛盾的多方面证据迅速采取行动。第三个是对被认为“不可量化”或太难处理的不确定性的处理：保险行业的一个例子涉及预留多少钱来支付已知可能发生但没有历史损失数据的事件的成本。可用（例如拉帕尔马的Cumbre Vieja火山崩溃引起的大西洋海啸）。五个案例研究将被用来说明该框架：（1）英国的洪水风险管理;（2）英国的地震灾害（与核电工业有关）和意大利的研究;（3）海啸灾害和风险评估，包括制定改进实时预警系统的方法;（4）解读未来几天的天气预报（重点是风速和寒冷天气）;（5）火山灰散布，也包括实时预警系统。一个最后的，关键的，拟议的研究组成部分涉及的通信和使用的不确定性信息来自前三个组成部分。我们将与工业伙伴合作，展示如何将对灾害本身不确定性的更好理解转化为风险评估（重点关注灾害的后果，例如经济损失或对基础设施的破坏）。我们还将开展研究，以更好地了解人们如何看待和使用风险信息。研究结果将用于为开发向专业和非专业用户传达自然灾害风险信息的新方法提供信息;并且（与PURE Network合作）制作自然灾害风险沟通手册。

Natural hazards pose serious problems to society and to the global economy. Recent examples in the UK include the cold winters of 2009 and 2010 and the eruptions of the Grimsvotn and Eyjafjallajökull volcanoes with the consequent disruption to air travel. Moving further afield, the first half of 2011 saw major disasters in Australia (flood), New Zealand (earthquake), Japan (earthquake and tsunami) and the US (hurricanes).It would be nice if scientists could provide precise information to help with the management of such events. This is unrealistic, however, for several reasons: data are usually incomplete (e.g. not available at all required locations) and measured with error; predictions are made using computer models that can at best approximate reality; and our understanding of some phenomena is limited by lack of experience (for example, the historical tsunami record is relatively limited). Therefore, natural hazard scientists must acknowledge the uncertainty in the information they provide, and must communicate this uncertainty effectively to users of the science. However, neither of these tasks is easy. Moreover, scientists do not always understand what users want and need; and users themselves often are uncomfortable with uncertainty. Despite these problems, modern statistical methods are available for handling uncertainty in complex systems using probability theory. In parallel, social science researchers are interested in understanding how people react to and understand uncertainty. By bringing these two developments together, and linking with scientists from several hazard areas along with a variety of users, we aim (a) to demonstrate a generic framework for handling uncertainty across hazards; and (b) to develop improved tools for communicating uncertain information. The generic framework considered here has three core components. The first is the treatment of uncertainties arising from our imperfect models and imperfect understanding of any complex system. The second is the combination of information from various sources that are all judged to be relevant: this is particularly important in event management situations where decision-makers must take rapid action based on multiple strands of evidence that might be apparently contradictory. The third is the treatment of uncertainties that are deemed to be "unquantifiable" or too hard to handle:an example from the insurance industry involves how much money to set aside to cover the cost of an event that is known to be possible but for which no historical loss data are available (such as an Atlantic tsunami caused by the collapse of the Cumbre Vieja volcano in La Palma). Five case studies will be used to illustrate the framework: (1) flood risk management in the UK; (2) earthquake hazard in the UK (relevant to the nuclear power industry) and in Italy; (3) tsunami hazard and risk assessment, including the development of methods to improve real-time warning systems; (4) the interpretation of days-ahead weather forecasts (focusing on wind speeds and cold weather); (5) volcanic ash dispersal, again including real-time warning systems. A final, and critical, component of the proposed research relates to the communication and use of the uncertainty information derived from the three previous components. Working with industrial partners, we will demonstrate how an improved understanding of uncertainty in the hazard itself can be translated through into risk assessments (which focus on the consequence of the hazard, for example the economic loss or damage to infrastructure). We will also carry out research to understand better how people perceive and use risk information. The results will be used to inform the development of novel methods for communicating natural hazard risk information to specialist and non-specialist users; and also (in collaboration with the PURE Network) to produce a handbook of risk communication for natural hazards.