Forecasters are responsible for predicting the weather and communicating risk with stakeholders and members of the public. This study investigates the statements that forecasters use to communicate probability information in hurricane forecasts and the impact these statements may have on how members of the public evaluate forecast reliability. We use messages on Twitter to descriptively analyze probability statements in forecasts leading up to Hurricanes Harvey, Irma, Maria, and Florence from forecasters in three different groups: the National Hurricane Center, local Weather Forecast Offices, and in the television broadcast community. We then use data from a representative survey of United States adults to assess how members of the public wish to receive probability information and the impact of information format on assessments of forecast reliability. Results from the descriptive analysis indicate forecasters overwhelmingly use words and phrases in place of numbers to communicate probability information. In addition, the words and phrases forecasters use are generally vague in nature -- they seldom include rank adjectives (e.g., “low” or “high”) to qualify blanket expressions of uncertainty (e.g., “there is a chance of flooding”). Results from the survey show members of the public generally prefer both words/phrases and numbers when receiving forecast information. They also show information format affects public judgments of forecast reliability; on average, people believe forecasts are more reliable when they include numeric probability information.

When a tornado lofts debris to the height of the radar beam, a signature known as the tornadic debris signature (TDS) can sometimes be observed on radar. The TDS is a useful signature for operational forecasters as it can confirm the presence of a tornado and provide information about the amount of damage occurring. Since real-time estimates of tornadic intensity do not have a high degree of accuracy, past studies have hypothesized that the TDS could also be an indicator of the strength of a tornado. However, few studies have related the tornadic wind field to TDS characteristics due to the difficulty of obtaining accurate, three-dimensional wind data in tornadoes from radar data. With this in mind, the goals of this study are twofold: 1) to investigate the relationships between polarimetric characteristics of TDSs and the three-dimensional tornadic winds, and 2) to define relationships between polarimetric radar variables and debris characteristics. Simulations are performed using a dual-polarization radar simulator called SimRadar; Large-Eddy Simulations (LESs) of tornadoes; and a single-volume, T-matrix based emulator. Results show that increases (decreases) in horizontal and vertical wind speeds are related to decreases (increases) in correlation coefficient and increases (decreases) in TDS area and height for all simulated debris types. However, the range of correlation coefficient values varies with debris type, indicating that TDSs comprised of similar debris types can appear remarkably different on radar compared to a TDS with diverse scatterers. Such findings confirm past, observational hypotheses and can aid operational forecasters in tornado detection and potentially the categorization of damage severity using radar data.

Weather forecasting is not an exact science and, in regions near the southern end of the Appalachian Mountains, the vastly different types of topography and frequency of rapidly forming storms can result in high uncertainty in severe weather forecasts. NOAA created its VORTEX-SE research program to tackle these unique challenges and integrate them with social science research to increase the survivability of Southeast U.S. weather. As part of the VORTEX-SE, this study focused on the severe weather preparation and decision making of emergency management, and in particular, how uncertainty in severe weather forecasts impacted the relationship between EMs and weather providers. We conducted in-depth, critical incident background interviews with thirty-five emergency management personnel across fourteen counties. An inductive, data-driven analysis approach revealed several factors contributing to an added layer of practical uncertainty beyond the meteorological forecast uncertainty that impacted and helped explain the nature of trust in the EM-NWS relationship. No- or short-notice events, null events, gaps in information, and differences in perspectives compared to weather forecasters have led emergency managers to modify their procedures in ways that position them to adapt to unexpected changes in the forecast quickly. The need to do so creates a complex, nuanced trust between these groups. This paper explains how EMs developed a nuanced trust of forecast information, how that trust is a recognition of the inherent uncertainty in severe weather forecasts, and how to strengthen the NWS-EM relationship.