CAT Demonstration Project

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CAT Demonstration Project#

AI2ES/OU, NSF NCAR, UW: Andrea Schumacher, Julie Demuth, DJ Gagne, Jorge Celis, Amy McGovern, Sara Curran, Sameer Shah, Masha Vernik, Ann Bostrom

Collaborating Across Threads Demonstration Project: Integrating multidisciplinary data to investigate changes in driving behaviors before and during a southern California atmospheric river flooding event

The motivation for this project is to investigate whether people change their driving behaviors as an atmospheric river (AR) flooding event is threatening and occurring and, if so, 1. who changes their driving behaviors, 2. how driving behaviors change, and 3. when those changes occur. This case study focuses on an AR event that occurred in Southern California from 29-31 March 2024, and integrates data from multiple disciplines such as longitudinal panel survey data*, American Community Survey (ACS), weather, and mobility data to examine changes in driving behavior surrounding this event through various disciplinary lenses. This project also seeks to address questions related to the process of integrating data from different disciplines, including: How do different datasets, individually and together, answer these questions? Where are there similarities and differences? How can we have a focused examination on population disparities? What types of data are needed to meaningfully explore these groups? What can we learn in doing so?

Datasets#

  • Longitudinal panel survey data collected during an atmospheric river flooding event in Southern CA from 29-31 March 2024

    • Included questions related to information use, risk perception, behavioral responses, and covariates

    • Web-only survey data collected by YouGov

    • Surveys collected over 3 24-hour waves on 27, 29, and 31 March 2024 American Community Survey (ACS)

  • Mobility data for southern CA (TBD - working with vendor to acquire)

  • Traffic data for southern CA (TBD - working with vendor to acquire)

Team Bios#

See biosketches for team members here.

We would like to acknowledge our collaborators from NCAR (Rebecca Morss and Robert Prestley) and Stanford (Gabrielle Wong-Parodi and Natalie Herbert) for their roles in collecting and analyzing the longitudinal panel data used in this study.

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