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NCAR’s Societal Impacts Program: WIST-Related Research Efforts. Julie Demuth NCAR Societal Impacts Program 3 rd National Surface Transportation Weather Symposium Vienna, VA July 18, 2007. Outline. Socio-economic roles in WIST NCAR’s Societal Impacts Program (SIP)
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NCAR’s Societal Impacts Program: WIST-Related Research Efforts Julie Demuth NCAR Societal Impacts Program 3rd National Surface Transportation Weather Symposium Vienna, VA July 18, 2007
Outline • Socio-economic roles in WIST • NCAR’s Societal Impacts Program (SIP) • SIP’s research activities relevant to the transportation community • OUSSSA • ISSA-T • Other related efforts
Socio-economic roles in WIST goals • Identify the priorities, challenges, and opportunities for research and development that will contribute to saving lives, reducing injuries, and improving efficiency in the Nation’s surface transportation infrastructure. • Investigate opportunities to document and substantiate the socioeconomic impacts of improved surface transportation weather products and services. • Identify the potential and emerging information dissemination technologies available to get the “right message” to surface transportation weather stakeholders. • Establish partnerships with the stakeholder community to ensure that customers and stakeholders understand how to effectively use surface transportation weather products and services in their decision-making processes. • Identify the needs for new products and services driven by current operations or concepts for future surface transportation systems. Are there existing capabilities or emerging research and development that can be leveraged and/or transitioned into operations to meet these needs? How can probabilistic forecasts be used to meet these needs? • Articulate a clear observation strategy for surface transportation weather that defines the types of data that are needed and the optimal mix of observing platforms required to meet those needs. • Define the needs for advanced computing capacity required for surface transportation weather modeling and for the assimilation of data from multiple data sources.
Societal Impacts Program (SIP) • Jeff Lazo, Director • Objective • Improve the societal gains from weather forecasting by infusing social science and economic research, methods, and capabilities into the planning, execution, and analysis of weather information, applications, and research directions. • Achieved through combination of research, outreach and education, WAS*IS program, capacity building / community support
Overall U.S. Sector Sensitivity Assessment (OUSSSA) • Goal: Evaluate the sensitivity of U.S. economic sectors to weather variability • Economic impacts of weather • Motivation: Wide use of back-of-the-envelope economic sensitivity estimates (e.g., Dutton 2002) • Methodology • Sensitivity = variation in economic productivity caused by weather variability • Technology and economic inputs (capital, labor, energy) held constant • Estimate sensitivity using data for 11 sectors, 48 states, 24 years = 12,672 observations
OUSSSA -- Sector sensitivity (Billions $2000)
Individual Sector Sensitivity Assessment – Transportation (ISSA-T) • Goal: Assess transportation sector’s use and value of weather forecasts and weather information • Motivation: • Develop baseline knowledge and valid and reliable socio-economic methods for use and value • Improve provision of weather information and support public investment in weather observing and forecasting systems • 5 subsectors: air, rail, water, truck, pipeline
ISSA-T • Methodology: expert elicitation from researchers, private sector employees, government officials • Phase 1 (now through Fall 2007): Input through semi-structured interviews to refine project scope, assess methodological approach, hone survey instrument for next phase • Phase 2 (tentative): Input through online structured survey from a broader population of experts
ISSA-T • Interview questions • Expert’s demographics, general sector assessment • Weather impacts • How weather affects costs, demand • Annual variability of weather effects • Economic impacts • Use and value of weather forecast information • Look at weather information currently used, available but not currently used, not available • Usefulness, upper and lower bounds of costs, upper and lower bounds of value of weather information • We need your input! • Feedback, contacts to interview or survey, references, etc.
Other related efforts • Communication of Forecast Uncertainty (CoFU) • To assess public’s understanding, use, and preferences about forecast uncertainty information • Warning Decisions in Extreme Weather Events • Explore decision processes of 4 “user groups” in obtaining, interpreting, and responding to extreme weather event warnings • Case study of the December 20-21, 2006, blizzard along the Colorado Front Range • People’s information sources and driving decisions actual behaviors! • Warning Project • People’s information sources and driving decisions related flash flood and tornado scenarios stated behaviors
WIST goals revisted • Identify the priorities, challenges, and opportunities for research and development that will contribute to saving lives, reducing injuries, and improving efficiency in the Nation’s surface transportation infrastructure. • Investigate opportunities to document and substantiate the socioeconomic impacts of improved surface transportation weather products and services. • Identify the potential and emerging information dissemination technologies available to get the “right message” to surface transportation weather stakeholders. • Establish partnerships with the stakeholder community to ensure that customers and stakeholders understand how to effectively use surface transportation weather products and services in their decision-making processes. • Identify the needs for new products and services driven by current operations or concepts for future surface transportation systems. Are there existing capabilities or emerging research and development that can be leveraged and/or transitioned into operations to meet these needs? How can probabilistic forecasts be used to meet these needs?
Thank you! • Contact • Jeff Lazo, SIP Director (lazo@ucar.edu) • Julie Demuth (jdemuth@ucar.edu) • www.sip.ucar.edu