Example of the Complex Ways that Uncertain Hydrometeorological Information Can Interact with User Decision Making
Flood managers often make high-stakes decisions based on complicated and usually incomplete data and information amidst not only much uncertainty but also constant change. The interaction between hydrometeorological uncertainty and flood management decision making was explored in a study by Morss et al. (2005). Like many groups of users, flood managers are not a homogeneous group; rather, the group includes decision makers from a variety of disciplines who operate under the priorities and values of their respective constituencies and communities. Their decisions must often be made quickly, using whatever information is available at the time, and the options available to them frequently must be taken in untidy, discrete chunks and not continuously along an elegant distribution of probabilities. And in many cases, flood management decisions are, in essence, already made for them, determined well in advance by land-use patterns, existing infrastructure, and rigid operating rules.
In such an environment, these resource constraints—in addition to technical capacity, familiar and comfortable routines, and even personal relationships with trusted advisers—triumph over scientific information, especially when different sources of hydrometeorological information and guidance conflict. Flood managers thus often retreat to simple analyses and actions that, while perhaps not fully incorporating the best science and uncertainty information available, are nonetheless logical and defensible. Based on their findings and the experience of others, Morss et al. (2005) recommend that to provide usable scientific information, scientists must invest time and effort to develop long-term relationships with flood managers, providing a two-way street for ongoing interaction and feedback. For information to be used, scientists must also make hydrometeorological information directly applicable and practical for a flood manager’s situation and environment. Such an approach should eventually lead to the familiarity with, trust in, and credibility of scientists that flood management practitioners seek when making critical decisions and thereby allow them to better incorporate hydrometeorological information into those decisions. As noted earlier, for some users a key component of this information is detailed forecast and historical information for user-based verification.
that may constitute an input into such processes are then discussed in the subsequent section. The formal analyses of the statistical decision analysis approach may be internalized in many businesses (e.g., for decisions on maintenance, inventory and supply chain management, infrastructure and strategic planning, and insurance). The opportunity for the use of probabilistic forecasts by different users may vary dramatically, and different types of efforts (e.g., modification of an existing decision-support system, or a detailed analysis of factors that determine decisions and the “safe” introduction of probabilistic information into that process) may need to be stimulated by the Enterprise to make forecasts useful to these groups.
This section reviews some established results from the psychology of risk and uncertainty; that is, what is known about the way in which people deal with risk and uncertainty and how they understand and utilize uncertainty information? It begins by describing several psychological dimensions relevant to the communication of uncertainty information on which potential users of weather and climate forecasts are known to differ. Most of these differences derive from the fact that people process uncertainty information with the help of two systems, an experiential/emotional system and an analytic system. These two processing systems operate for everyone, but the degree of sophistication of the analytic processing system and the attention paid to it by the decision maker strongly differ as a function of education and training, and by the current rules of practice in an organization. This section discusses the implications that this and other individual differences might have for the design of forecast uncertainty products. Section 2.2.2 describes three complications in the communication of uncertainty information that lie at the root of possible user misinterpretations or rejections of probabilistic forecasts and point the way to user needs.
The psychological heterogeneity of users makes it impossible for any single forecast product to satisfy the needs and constraints of all users. Factors that influence the way in which users perceive uncertainty and make decisions include the operation of different information-processing systems, how information about possible events and their likelihood is obtained, the different emotional impact of gains versus losses, and the degree of numeracy and personality of a particular user.
Research from cognitive, social, and clinical psychology suggests that people process information in two distinct ways when making judgments or arriving at decisions (Epstein,