Transcript Document

Collaborative Adaptive Sensing of the
Atmosphere: End User and Social
Integration
2009 American 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
Background
New technology is the
solution!
Background
But, what was the
problem??
snow
tornado
Flexible architecture
0

Rapid, “smart” scans
– balance competing user needs for data
– adapt to changing weather
– RHIs, PPIs, dual Doppler, sector scans
40
80
120
160
RANGE (km)
200
240
Current paradigm: large, Long range radars
3.05 km
•
wind
10,000 ft
Goal:
To provide users the information they
need when they need it .
3.05 km
•
5.4 km
Low level, overlapping coverage
4 km
•
10,000 ft
2 km
Dense networks of X-band radars
1 km
•
3.05 km
CASA addresses a new sensing paradigm
snow
wind
tornado
0
40
80
120
160
RANGE (km)
200
240
CASA’s dense networks of small radars
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.
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)
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 endusers (e.g, individual and organizational level of analysis) and
relate to aforementioned objectives.
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.
End-user Integration Model
End-User Integration
Research Group
Public Sector (NWS,
FEMA, emergency
managers, etc.)
Private Sector
(Insurance, Media,
Transportation, etc.)
Science/Technology
Development: NETRAD
General Public
Research Methodology
Public Sector (NWS,
FEMA, emergency
managers, etc.)
Quick
Response
Integrating Data and
Information from the
Puerto Rico and Oklahoma
Testbeds
G.I.S.
Private Sector
(Insurance, Media,
Transportation,
etc.)
Experiments
General Public
G.I.S.
End-User Integration
Research Group
Surveys
Ongoing Research Efforts
NOAA Experimental Warning
Program in Hazardous Weather
Test bed
Assessment Error
CASA reduces wind
assessment error by 30 %
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.
Reasons EMs Deploy Spotters
During Warning Phase
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.