End‐user satisfaction with Hurricane Dorian information in Atlantic Canada

Abstract

Both Environment and Climate Change Canada (ECCC) and the National Oceanic and Atmospheric Administration have focused significant time and resources towards improving their forecast products. However, weather prediction remains an imperfect science, and as such, it is not unusual for meteorologists to prioritize accuracy over consistency or vice versa. There is considerable debate within the literature about whether (and how) inaccuracies and/or inconsistencies in forecasting will affect end-user trust in future warnings.Hurricane Dorian presented the opportunity to explore the intersection between these concepts as its messaging was at times both inaccurate (e.g., then-President Donald J. Trump indicated the storm would directly affect the state of Alabama) and inconsistent (i.e., both the storm's forecasted intensity and track changed over time). Two research projects were undertaken in Atlantic Canada: the first utilized semi-structured interviews to examine the ways that ECCC meteorologists (n = 6) perceived the needs of their end-users during the storm. There was considerable concern that changes in the storm's forecasted track and intensity would negatively influence public response. The second project utilized a large sample questionnaire (n = 1218) to examine ways that end-users searched for, shared, and responded to storm-related information. Despite changes in the storm's track and intensity as it approached Atlantic Canada, as well as the international news coverage of Sharpiegate, respondents overwhelmingly agreed that the storm was well forecasted and its impacts were well predicted. The implications for this (seemingly) contradictory response are explored in the context of probabilistic forecast potential.

Reconceptualizing Virtual Operations Support Teams (VOSTs) as an experiential learning tool for emergency management education

“…This body of research has demonstrated that social media can provide numerous functions before, during, and after disasters, including: Rapid dissemination of information, such as life safety information (e.g., weather warnings, evacuation routes, recommended protective actions), on‐the‐ground impacts (e.g., videos, pictures, or textual descriptions of damage), and community needs (e.g., Hyvärinen & Saltikoff, 2010; Palen et al, 2010; Ripberger et al, 2014; St. Denis et al, 2020; Stokes & Senkbeil, 2017; Vieweg et al, 2010). Providing a platform for information seeking, information sharing, and decision support (e.g., Armstrong et al, 2021; Austin et al, 2012; Lee & Jin, 2019; Liu et al, 2016; Silver & Behlendorf, 2023; Silver & Matthews, 2017). Providing a platform for milling and sense‐making (e.g., Eiser et al, 2012; Heverin & Zach, 2012; Liu et al, 2016; Sutton et al, 2011, 2014).…”

“…Providing a platform for information seeking, information sharing, and decision support (e.g., Armstrong et al, 2021; Austin et al, 2012; Lee & Jin, 2019; Liu et al, 2016; Silver & Behlendorf, 2023; Silver & Matthews, 2017).…”

Understanding your audience: The influence of social media user‐type on informational behaviors and hazard adjustments during Hurricane Dorian

“…Although the storm was well forecasted and its impacts in the region were generally well predicted, it was not without its challenges. Both the Canadian Hurricane Centre (Canada) and the National Hurricane Center (United States) predicted the storm would come ashore either as a high-end Category 1 storm or a low-end Category 2 storm (Silver et al, 2022). Given the relative rarity of Category 1 and 2 storms in the region, there was a great deal of speculation about the storm's intensity, with some sources even drawing comparisons to Hurricane Juan, a Category 2 storm that had devastated the region almost 20 years earlier (Toronto Star, 2019).…”

“…The questionnaires were disseminated to residents of Atlantic Canada (Nova Scotia, New Brunswick, Prince Edward Island, and Newfoundland) using the online survey platform Qualtrics between late September and late October 2019. Silver et al (2022) provide results regarding the perceptions of storm-related information, including issues pertaining to misinformation and credibility. In this paper, we explore respondents' self-reported information seeking and sharing behaviors, as well as whether and how Twitter influenced their decisions to prepare for and respond to the storm.…”