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2024 D4 Hack Week: Disasters, Demography, Disparities, and Decisions

Applications for the 2024 D4 Hack Week are CLOSED. Please check back here for updates regarding the Hack Week Teams and Agenda.

Workshop Overview

The University of Washington invites you to apply to participate in a 5-day collaborative workshop from September 9-13, 2024, to advance research products and methods for improving observations, assessments, and forecasts across appropriate temporal and spatial scales to accomplish three goals:

Investigate the human behavior and societal adaptive responses to, and impacts of, severe weather and climate-related events, particularly flooding associated with atmospheric rivers, hurricanes, and severe storms, but also including other extreme events such as heat or fire.

Address the research gaps linking mitigation to adaptation and resilience in relation to severe weather. This will involve exploring co-benefits for human well-being from climate adaptation strategies that will further contribute to resilience to extreme weather events and climate mitigation.

Explore pathways to better understand the dynamics of decisions and population disparities in responses to and impacts of past extreme climate / weather events.

The workshop will create improved data products and methods (data integration, data assimilation, analytic tools, new approaches to analyses) that integrate social and weather and/or climate data across space and time, through interdisciplinary collaborations. Data products should inform decision models that can guide decision making to address the needs of individuals, households, neighborhoods, and communities, with projections of impacts on the scales of minutes to hours, days, weeks, or years. Data and their analyses should be capable of informing impact analysis and risk reduction planning.

The workshop will focus on the data and analytic challenges of linking climate- and weather-related impacts and mitigation efforts to human behavior, health, and well-being by:

  1. facilitating all participants’ access to data sources and tools in a secure computing environment, when required, and provide open source tools and resources otherwise;
  2. exploring and innovating new approaches, including the use of machine learning (ML), to assimilate, curate, and analyze the relevant multiplicity of data required to assess and predict impacts of extreme weather events across contexts and scales.
  3. incorporating vital, mediating societal, institutional, organizational, and relational factors into understandings of the environment. The workshop organizers assume that societal and natural landscape factors are crucial mechanisms in managing mitigation and adaptation, but until now these factors have been incompletely incorporated into models that link climate change or weather to human and societal well-being;
  4. catalyzing research that more completely models weather- and climate-human linkages and accelerates knowledge and provision of tools for policymakers, emergency managers, businesses, and the public.

Prior to the workshop, participants will be expected to participate in activities related to preparing for the workshop, which may include a short presentation before or during the workshop on the participant’s workshop-related expertise, or topical research or methodological focus.  Participants may also be asked to contribute to the post-workshop development of products, such as research papers, grant proposals, websites, and shared integrated tools and data.

Workshop Logistics

Accessible Accordion

Successful applicants will be supported for a 5-day workshop (September 9-13, 2024) at the eScience Institute at the University of Washington’s Seattle Campus. Applications can be made by individuals or teams (with support for in-person attendance for up to 3 team members).  While the number of attendees will be limited, we will also facilitate virtual participation to the extent possible.

Attendees will be expected to have experience working directly with related data integration challenges, and to be prepared to advance one or more research products in the workshop. Applicants should have expertise in

  1. climate and/or extreme weather data or modeling, which may include AI/ML, or modeling compound or cascading hazards and their interactions with built or social systems, and
  2. demographic and/or social and behavioral data or modeling, which may include AI/ML, risk communication and decision making under uncertainty, or other social system dynamics.

Individual members of teams applying should have expertise in at least one relevant area. We especially welcome submissions from applicants who cut across multiple themes and skill areas.

The information you will be asked to provide in the survey is listed below. Where short statements are requested, the form allows 300 words max.

    • Your expertise in any of these fields (short statement):
      • Climate and/or Extreme Weather Data or Modeling
      • Demographic and/or Social and Behavioral Data or Modeling
      • Decision Modeling or Decision-Support Systems
      • Data Science, AI/ML Modeling or Tools
      • Other Relevant Expertise
    • Your interest and willingness to collaborate, with examples of collaborative experience (short statement)
    • Your interest and willingness to address diversity, equity, and inclusion in understanding climate impacts, adaptation, and mitigation (short statement)
    • Your general interests in better understanding the dynamics of decisions and population disparities in responses to and impacts of past extreme climate/weather events (short statement)
    • A bio-sketch or resume that highlights relevant research and interests (for each team member if applying as a team)
    • Describe the research question that you wish most to answer. The research question must require data integration approaches and/or modeling approaches (short statement)
    • A brief description of one or more of the following to be co-developed or used during the workshop. Note: these do not have to be their own/original to you. (short statement):
      • Data product (s) – full description of measures, temporal and spatial resolution, potential linkages, and data size and coverage.
      • Models and measures
      • Data science tools for linkages
      • AI/ML tools
      • Data visualization tools
    • A detailed description of the kind of additional data or modeling approach you or your team are seeking to integrate via collaboration with another team during the workshop and why these data are crucial for advancing research on the question of most interest to you (short answer).
    • Please describe a product that you would like to come out of this workshop. This could be a proposed data assimilation/visualization tool, research paper, and/or research grant proposal idea by your team, augmented or newly formed at the workshop (short statement)
    • How might analyses that you propose to conduct during the workshop contribute to the three goals for the workshop?
    • Do any of the data you plan to use have secure / confidentiality measures we would need to consider for you to participate in the workshop?
    • If you were to attend the workshop, what would be a successful outcome for you or your team from the workshop?  (short statement)
    • If you were to attend the workshop, what would be a specific challenge addressed during the workshop that would be most exciting and productive for you and your team? (short statement)
    • If you were to attend the workshop, would you attend in person? This does not affect your chances of selection but helps with workshop planning and logistics.

Workshop Support

This workshop is supported by a partnership between the University of Washington (UW)’s Center for Studies in Demography and Ecology (CSDE), the National Science Foundation AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES), and the University of Washington eScience Institute

Funding for the workshop derives from a grant from NOAA to AI2ES (Award NA23OAR40505031) and a center grant to CSDE from the Eunice Kennedy Shriver National Institutes of Child Health and Human Development via the P2C HD042828 mechanism.

In his role as a John C. Garcia Term Professor, Dr. Shah recognizes the generous financial support made possible by Carole Garcia.

Support for the workshop organization is also provided through the Weyerhaeuser Endowed Professorship in Environmental Policy at the University of Washington Evans School of Public Policy & Governance.