that appear as deterministic values or graphs for the next 7 days, with no change in format. As discussed in Chapter 3, these deterministic digital values for days into the future are not scientifically valid and could be highly inaccurate and misleading. In addition, the system issues forecasts of precipitation type and thunderstorm risk using vague uncertainty terms such as “slight chance,” “chance,” “likely,” and “occasional.” As discussed in Chapter 2 and developed later in this chapter, research has shown that these terms are interpreted by users as communicating a wide range of probabilities.
The NDFD enables a user to select a site-specific forecast and to extract tailored forecasts from the database. The drawback, though, is that these forecasts include no “qualifier” text or statistical ranges that provide the user with uncertainty information to aid decisions. Fundamentally, IFPS and NDFD are also designed from a deterministic framework (other than the “Probability of Precipitation” component) and thus cannot be easily modified to incorporate communication of forecast uncertainty information.
The provision of single-valued forecasts without uncertainty information (such as error bars on a meteograph) not only exposes a significant limitation of the NDFD/IFPS process but is also fundamentally inconsistent with the science (Chapter 1). Moreover, these digital systems may generate machine-derived text forecasts of “partly cloudy” skies for several days in a row—in essence representing a wide range of weather conditions—and therefore do not effectively communicate the complexity or uncertainty of future weather.
With the importance of digital dissemination of forecasts through the Internet, incorporating uncertainty information into NDFD and IFPS would be advantageous to the public, intermediaries, and specialized users. Many methods of communicating uncertainty are available. Choosing the most effective method (or methods) will require research and two-way interactions with users (see Sections 4.4 and 4.5). Possible methods to consider include displaying skill scores or the standard forecast variance for each forecast variable at different times or providing confidence intervals. Another possibility, to improve consistency, is to communicate cloud cover not as scattered or broken but rather in categories (such as high, medium, and low) or as a percentage (as is currently done for probability of precipitation type and probability of thunderstorms in Model Output Statistics [MOS]).
Finding: The public weather forecasts from the IFPS and distributed as the NDFD are one of NWS’s primary forecast products. The system is unable to provide probabilistic forecasts for most fields, and it cannot access probabilistic guidance from the National Centers for Environmental Prediction (NCEP) or other ensemble systems. With the incorporation and communication of uncertainty in most