FIGURE 2.1 User categories for NWS products and the flow of forecast information and products among them. Line thickness qualitatively illustrates the relative magnitude of flow. SOURCE: Committee on Estimating and Communicating Uncertainty in Weather and Climate Forecasts.

mediaries between NWS and the public. Those include the media, government organizations, and weather services. The psychological factors in interpretation and use of uncertainty information apply mostly to individual end users. However, some intermediaries (such as the media) can exhibit similar understanding of probabilistic information. In addition, forecast products and formats that work for the NWS scientists who develop them may not be understandable to and usable by less specialized information processors.

The decision-support systems and analytic decision methods discussed in Section 2.3 are found to a far greater extent among users who get their information from the intermediaries listed on the right-hand side of Figure 2.1. Whether the decision processes that utilize hydrometeorological forecasts are informal and intuitive or formal and analytic, forecast producers need to be cognizant of how forecast information gets used to decide on how to optimally present its uncertainty.

Weather and climate affect nearly all segments of society, and there is a multitude of weather- and climate-related decisions and decision makers. More specifically, decision processes and their consequences vary on at least the following dimensions:

  • Forecast user: for example, individual, institution, or Enterprise member/intermediary;

  • Sector: for example, travel, tourism, energy, water, agriculture, insurance;

  • Type of decision: for example, emergency response, routine/recurrent operation, or adaptive long-term management plan;

  • Time or space scale: for example, imminent flood management at a location, or prediction of global market prices for commodities in a future season, or long-term corporate or national investments in infrastructure;

  • Problem complexity: for example, single objective with a few known inputs, or multiple objectives with many inputs/outputs and sources of uncertainty;

  • Decision processes: for example, analytic versus intuitive; exhaustive analysis of response options versus semiautomatic decision rules or response triggers, and framing of outcomes as gains or losses; and

  • Consequence of decision: for example, carrying an umbrella unnecessarily; saving lives and property.

In general, users want forecasts to help them make a decision: What clothes do I wear? Do we send out snowplows, and if so, when? Do we purchase additional fuel supplies for the coming months, and if so, how much? Do we order mandatory evacuations?1 The decisions made with hydrometeorological forecasts are so numerous and variable that this report cannot identify and specify the information needs of each individual user or user community. Thus, this section explores user needs for uncertainty information by discussing broad user communities and presenting examples. Guidance to NWS on how to build capacity to identify its users’ needs in greater detail is presented in Section 2.4

Specific User Types and Needs for Uncertainty Information

Although NWS has not established a comprehensive formal method for incorporating uncertainty information into its services and products based on user needs,2 it does have


 As these examples illustrate, many (but not all) user decisions are binary (yes or no), often with some threshold for action. Within this binary decision, however, there can still be a range of alternatives related to type of action (e.g., take a raincoat or an umbrella), timing of action, and other factors.


 As noted in written responses from NWS to the committee and in a presentation by Ed Johnson at the committee’s first meeting.

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