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Daphne S. LaDue
and
Ariel E. Cohen

Abstract

Professional meteorologists gain a great deal of knowledge through formal education, but two factors require ongoing learning throughout a career: professionals must apply their learning to the specific subdiscipline they practice, and the knowledge and technology they rely on becomes outdated over time. It is thus inherent in professional practice that much of the learning is more or less self-directed. While these principles apply to any aspect of meteorology, this paper applies concepts to weather and climate forecasting, for which a range of resources, from many to few, for learning exist. No matter what the subdiscipline, the responsibility for identifying and pursuing opportunities for professional, lifelong learning falls to the members of the subdiscipline. Thus, it is critical that meteorologists periodically assess their ongoing learning needs and develop the ability to reflectively practice. The construct of self-directed learning and how it has been implemented in similar professions provide visions for how individual meteorologists can pursue—and how the profession can facilitate—the ongoing, self-directed learning efforts of meteorologists.

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Rachael N. Cross
and
Daphne S. LaDue

Abstract

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-Southeast (SE) research program to tackle these unique challenges and integrate them with social science research to increase the survivability of southeastern U.S. weather. As part of 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 emergency managers (EMs) and weather providers. We conducted in-depth, critical incident background interviews with 35 emergency management personnel across 14 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 to explain the nature of trust in the EM–National Weather Service (NWS) relationship. No- or short-notice events, null events, gaps in information, and differences in perspectives when compared with weather forecasters have led emergency managers to modify their procedures in ways that position them to adapt quickly to unexpected changes in the forecast. 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.

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Daphne S. LaDue
,
Pamela L. Heinselman
, and
Jennifer F. Newman

Advancements in radar technology since the deployment of the Weather Surveillance Radar-1988 Doppler (WSR-88D) network have prompted consideration of radar replacement technologies. In order for the outcomes of advanced radar research and development to be the most beneficial to users, an understanding of user needs must be established early in the process and considered throughout. As an important early step in addressing this need, this study explored the strengths and limitations of current radar systems for nine participants from two key stakeholder groups: NOAA's NWS and broadcast meteorologists. Critical incident interviews revealed the role of each stakeholder group and attained stories that exemplified radar strengths and limitations in their respective roles.

NWS forecasters emphasized using radar as an essential tool to assess the current weather situation and communicate hazards to key stakeholder groups. TV broadcasters emphasized adding meaning and value to NWS information and using radar to effectively communicate weather information to viewers. The stories told by our participants vividly illustrated the advancing nature of weather detection with radar, and why there are still issues with weather radar and radar-derived information. Analysis of the stories, which ranged from accounts of severe weather to winter weather, revealed four underlying radar needs: 1) clean, accurate data without intervention, 2) higher spatial-and temporal-resolution data than that provided by the WSR-88D, 3) consistent and low-altitude information, and 4) more accurate information on precipitation type, size, intensity, and distribution.

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Pamela L. Heinselman
,
Daphne S. LaDue
, and
Heather Lazrus

Abstract

Rapid-scan weather radars, such as the S-band phased array radar at the National Weather Radar Testbed in Norman, Oklahoma, improve precision in the depiction of severe storm processes. To explore potential impacts of such data on forecaster warning decision making, 12 National Weather Service forecasters participated in a preliminary study with two control conditions: 1) when radar scan time was similar to volume coverage pattern 12 (4.5 min) and 2) when radar scan time was faster (43 s). Under these control conditions, forecasters were paired and worked a tropical tornadic supercell case. Their decision processes were observed and audio was recorded, interactions with data displays were video recorded, and the products were archived. A debriefing was conducted with each of the six teams independently and jointly, to ascertain the forecaster decision-making process. Analysis of these data revealed that teams examining the same data sometimes came to different conclusions about whether and when to warn. Six factors contributing toward these differences were identified: 1) experience, 2) conceptual models, 3) confidence, 4) tolerance of possibly missing a tornado occurrence, 5) perceived threats, and 6) software issues. The three 43-s teams issued six warnings: three verified, two did not verify, and one event was missed. Warning lead times were the following: tornado, 18.6 and 11.5 min, and severe, 6 min. The three tornado warnings issued by the three 4.5-min teams verified, though warning lead times were shorter: 4.6 and 0 min (two teams). In this case, use of rapid-scan data showed the potential to extend warning lead time and improve forecasters’ confidence, compared to standard operations.

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Daphne S. LaDue
,
David Roueche
,
Frank Lombardo
, and
Lara Mayeux

Abstract

When a tornado strikes a permanent or mobile/manufactured home, occupants are at risk of injury and death from blunt force trauma caused by debris-loaded winds and failure of the structure. Mechanisms for these failures have been studied for the past few decades and identified common weaknesses in the structural load path. Also under study in recent decades, much has been learned about how people receive and understand warnings and determine how, when, and if they will shelter in advance. Recent research, for example, shows most people do not shelter until close to impact, after seeing, hearing, or feeling the approaching tornado. To advance beyond these innovations, a new, multi-disciplinary approach was fielded in nine Southeast U.S. tornadoes between 2019 and 2022. For each tornado, 1) wind engineering assessments documented near-surface wind fields, 2) structural engineering assessments documented the primary wind load path for each structure, and 3) social science interviews captured the survivor’s narrative and asked several follow-up questions to assure key items of interest were addressed in each interview. When possible, the team was multi-disciplinary during the interview, enabling survivors to ask questions and better understand their experiences. Most survivors became aware of the approaching tornado with at least a few minutes lead time and most were able to reach a place of refuge. Most survivors recalled sensory experiences during the tornado and about half could describe direction or temporal sequences of damage. A case study of the Cookeville, Tennessee, Tornado of 3 March 2020 illustrates the power of the integrated data assessment.

Open access
Jack R. Friedman
,
Daphne S. LaDue
,
Elizabeth H. Hurst
,
Michelle E. Saunders
, and
Alex N. Marmo

Abstract

This paper provides an introduction to a new tool that is designed to provide operationally useful vulnerability information to National Weather Service (NWS) Weather Forecasting Offices (WFOs). The Brief Vulnerability Overview Tool (BVOT) is a shapefile containing local known, spatially specific, and weather-hazard-related vulnerabilities in a format that is easily integrated into the existing forecasting, warning, and decision support responsibilities and tasks of NWS WFO meteorologists. The methods for gathering vulnerability data and then building a BVOT for a WFO leverage and strengthen the relationships that NWS WFOs already have with their local emergency managers (EMs) and core partners to work together to identify operationally useful, local vulnerability knowledge. The BVOT is populated with discrete, known vulnerabilities to provide NWS meteorologists spatial situational awareness of those people, places, and things of greatest concern to their core partners. Crucially, the BVOT is a subsample of all potential vulnerabilities; its primary purpose is to make meteorologists aware of those weather-hazard-specific vulnerabilities that, as we posed to them, “keep them awake at night.” Here, we describe the development of the BVOT as a social science–informed operational tool; how the BVOT methods have evolved and how it can be integrated into the culture of the NWS as a tool for building and maintaining relationships with partners; and how the BVOT is designed to be used and its impact on operational decision-making as observed in NOAA’s Hazardous Weather Testbed.

Open access
Christopher D. Karstens
,
James Correia Jr.
,
Daphne S. LaDue
,
Jonathan Wolfe
,
Tiffany C. Meyer
,
David R. Harrison
,
John L. Cintineo
,
Kristin M. Calhoun
,
Travis M. Smith
,
Alan E. Gerard
, and
Lans P. Rothfusz

Abstract

Providing advance warning for impending severe convective weather events (i.e., tornadoes, hail, wind) fundamentally requires an ability to predict and/or detect these hazards and subsequently communicate their potential threat in real time. The National Weather Service (NWS) provides advance warning for severe convective weather through the issuance of tornado and severe thunderstorm warnings, a system that has remained relatively unchanged for approximately the past 65 years. Forecasting a Continuum of Environmental Threats (FACETs) proposes a reinvention of this system, transitioning from a deterministic product-centric paradigm to one based on probabilistic hazard information (PHI) for hazardous weather events. Four years of iterative development and rapid prototyping in the National Oceanic and Atmospheric Administration (NOAA) Hazardous Weather Testbed (HWT) with NWS forecasters and partners has yielded insights into this new paradigm by discovering efficient ways to generate, inform, and utilize a continuous flow of information through the development of a human–machine mix. Forecasters conditionally used automated object-based guidance within four levels of automation to issue deterministic products containing PHI. Forecasters accomplished this task in a timely manner while focusing on communication and conveying forecast confidence, elements considered necessary by emergency managers. Observed annual increases in the usage of first-guess probabilistic guidance by forecasters were related to improvements made to the prototyped software, guidance, and techniques. However, increasing usage of automation requires improvements in guidance, data integration, and data visualization to garner trust more effectively. Additional opportunities exist to address limitations in procedures for motion derivation and geospatial mapping of subjective probability.

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