Illustrating Extreme Weather across U.S. School Districts through Data Linking and Visualization

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Title: Illustrating Extreme Weather across U.S. School Districts through Data Linking and Visualization
Language: English
Authors: Nicholas Ortiz, Anne Partika, Paul Burkander, SRI Education
Source: SRI Education, a Division of SRI International. 2025.
Availability: SRI International. 333 Ravenswood Avenue, Menlo Park, CA 94025. Tel: 650-859-2000; e-mail: customer.service@sri.com; Web site: https://www.sri.com/
Peer Reviewed: N
Page Count: 12
Publication Date: 2025
Document Type: Reports - Research
Descriptors: Weather, Natural Disasters, Emergency Programs, Data Use, Synthesis, Geographic Regions, School Districts
Abstract: Extreme weather is increasingly common and severe. Education system leaders need access to integrated data that link national weather and disaster information with data from their own state or district to inform decision-making around disaster preparedness and response. This brief demonstrates one way of integrating education, weather, and population data to estimate how extreme weather affected U.S. school districts over a decade. Through a variety of national maps, descriptive statistics, and vignettes, we use integrated data to illustrate how various types of extreme weather had widespread impacts on school districts. By spatially linking these data, we find that an overwhelming majority of school districts were impacted by extreme weather over 10 years. Moreover, different types of weather affected different areas of the country unequally. School system leaders must plan for the inevitability of disasters and strategically distribute resources. We discuss three key areas where states could use support: (1) integrating data for real-time monitoring and planning, (2) building capacity for data storytelling, and (3) identifying impacts on student outcomes.
Abstractor: As Provided
Entry Date: 2026
Accession Number: ED679872
Database: ERIC
FullText Text:
  Availability: 0
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  Data: Illustrating Extreme Weather across U.S. School Districts through Data Linking and Visualization
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  Data: SRI International. 333 Ravenswood Avenue, Menlo Park, CA 94025. Tel: 650-859-2000; e-mail: customer.service@sri.com; Web site: https://www.sri.com/
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  Data: Extreme weather is increasingly common and severe. Education system leaders need access to integrated data that link national weather and disaster information with data from their own state or district to inform decision-making around disaster preparedness and response. This brief demonstrates one way of integrating education, weather, and population data to estimate how extreme weather affected U.S. school districts over a decade. Through a variety of national maps, descriptive statistics, and vignettes, we use integrated data to illustrate how various types of extreme weather had widespread impacts on school districts. By spatially linking these data, we find that an overwhelming majority of school districts were impacted by extreme weather over 10 years. Moreover, different types of weather affected different areas of the country unequally. School system leaders must plan for the inevitability of disasters and strategically distribute resources. We discuss three key areas where states could use support: (1) integrating data for real-time monitoring and planning, (2) building capacity for data storytelling, and (3) identifying impacts on student outcomes.
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  Data: 2026
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      – Text: English
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        PageCount: 12
    Subjects:
      – SubjectFull: Weather
        Type: general
      – SubjectFull: Natural Disasters
        Type: general
      – SubjectFull: Emergency Programs
        Type: general
      – SubjectFull: Data Use
        Type: general
      – SubjectFull: Synthesis
        Type: general
      – SubjectFull: Geographic Regions
        Type: general
      – SubjectFull: School Districts
        Type: general
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      – TitleFull: Illustrating Extreme Weather across U.S. School Districts through Data Linking and Visualization
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            NameFull: Paul Burkander
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              Y: 2025
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