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Collaborative Adaptive Sensing of the Atmosphere: End User and Social Integration 2009 American Meteorological Association Summer Community Meeting.

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  1. Collaborative Adaptive Sensing of the Atmosphere: End User and Social Integration 2009American Meteorological Association Summer Community Meeting Walter Díaz, UPRM; Havidán Rodríguez, UDEL; Bill Donner, UDEL; Jenniffer Santos, UDEL; Brenda Phillips, UMASS; Kevin Kloesel, OU; Joe Trainor, UDEL; Ellen Bass, UVA

  2. Background New technology is the solution!

  3. Background But, what was the problem??

  4. 10,000 ft 3.05 km 4 km 2 km 1 km 5.4 km snow wind tornado earth surface 0 40 120 160 200 80 240 RANGE (km) 10,000 ft 3.05 km snow 3.05 km wind tornado earth surface 0 40 120 160 200 80 240 RANGE (km) CASA’s dense networks of small radars CASA addresses a new sensing paradigm • Dense networks of X-band radars • Low level, overlapping coverage • Flexible architecture • Rapid, “smart” scans • balance competing user needs for data • adapt to changing weather • RHIs, PPIs, dual Doppler, sector scans • Goal: To provide users the information they need when they need it . Current paradigm: large, Long range radars

  5. Background “To be made useful, scientific research must be integrated with the needs of people seeking to address problems or opportunities they face.” Pielke and Pielke, 1997 A multidisciplinary effort integrating engineering and the physical and social sciences is necessary if we are to leverage improved meteorological knowledge and forecasting in order to enhance mitigation and reduce societal vulnerability.

  6. Background What is a disaster? …disasters are about human populations, how their lives and activities are imperiled or changed, how they react to crises, the attitudes they hold, the adjustments they make and how they confront the everyday problems of risk and vulnerability“ Curson (1989)

  7. Objectives of the End User group • Determine how improved forecasting will reduce the exposure and vulnerability of individuals and property to every-day and extreme climatological events and how it contributes to enhancing mitigation, preparedness, and response behavior. • Establish networks with government and non-governmental agencies, industries, and communities to carryout research to determine their knowledge, attitudes, needs, and utilization of weather and forecasting information. • Determine how improved weather observation and forecasting will impact organizational decision making • Generate a demographic and socioeconomic profile of end-users (e.g, individual and organizational level of analysis) and relate to aforementioned objectives.

  8. Why? 1. To improve the science by identifying additional limitations and gaps in current technology and knowledge.2. To develop better products that are more useful to society. Ultimately, users pay for information because it impacts their decision making. What decisions are currently made? To what degree are they a function of current observing technology and products? How will this change? What new or modified products do end users want? How do they want or need them delivered? 3. To improve and demonstrate accountability by improving our ability to collect information on how new technology and products result (hopefully) in improved decision making and behavior.

  9. End-user Integration Model End-User Integration Research Group Public Sector (NWS, FEMA, emergency managers, etc.) Private Sector (Insurance, Media, Transportation, etc.) General Public Science/Technology Development: NETRAD

  10. Research Methodology Private Sector (Insurance, Media, Transportation, etc.) Public Sector (NWS, FEMA, emergency managers, etc.) General Public Quick Response Surveys G.I.S. G.I.S. Experiments Integrating Data and Information from the Puerto Rico and Oklahoma Testbeds End-User Integration Research Group

  11. Ongoing Research Efforts NOAA Experimental Warning Program in Hazardous Weather Test bed Emergency Manager Research - Over 50 in-depth interviews with emergency managers in OK. - Post Event Survey including EMs across the US. Emphasis on test bed events but also includes all jurisdictions surveyed by the Public Response Survey. - Seeks to obtain data on current usage of weather information for EM decision making and how CASA data may change this. Public Response Survey Explore public response and the household decision making process following a severe weather warning or a hazard event Using Computer Assisted Telephone Interviewing (CATI) to carry out interviews with residents of areas affected by tornadoes. Current n=600 across OK, MN, KS, MS, AL and CO. Develop quantitative and predictive models of public response to tornado events and warning. Assessment Error Reasons EMs Deploy Spotters During Warning Phase CASA reduces wind assessment error by 30 %

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