Transcript If You Build It, They Will Come!

530230
Mesoscale Atmospheric
Network:
The Helsinki Testbed
David Schultz
Division of Atmospheric Sciences, Department of Physical Sciences, University of Helsinki,
and Finnish Meteorological Institute
Dynamicum 4A01d
Mobile: 050 919 5453
[email protected]
http://www.cimms.ou.edu/~schultz
Who am I, and
what am I doing here?
The “Science” of Phrenology
Having the bumps on my head interpreted
The Museum of Questionable Medical Devices,
St. Paul, Minnesota
Education and Experience
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(1) Born (1965) and raised in Pennsylvania
(2) B.S. 1987, Massachusetts Institute of Technology
(3) M.S. 1990, University of Washington
(4) Ph.D. 1996, University of Albany
Education and Experience
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(1) Born (1965) and raised in Pennsylvania
(2) B.S. 1987, Massachusetts Institute of Technology
(3) M.S. 1990, University of Washington
(4) Ph.D. 1996, University of Albany
(5) 1996–present: Cooperative Institute for Mesoscale
Meteorological Studies (CIMMS), University of Oklahoma,
and NOAA National Severe Storms Laboratory (NSSL),
Norman, Oklahoma
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Adjunct Faculty Member, Univ. of Oklahoma, School of Meteorology
Lecturer at summer schools in France and Romania
Editor, Monthly Weather Review (co-Chief Editor 2008!!)
Co-led the Intermountain Precipitation Experiment
Forecaster for National Weather Service, 2002 Winter Olympic
Games, Salt Lake City
NSSL is co-located with the NOAA/Storm Prediction Center, the best
severe-weather forecasters in the U.S.
Developed web-training materials on winter weather for U.S. National
Weather Service
Research Interests
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Observationalist and diagnostician, model user, some theory
Over 60 publications
Cyclone/frontal structure and evolution
Winter-weather processes
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Precipitation banding
Snow density
Radar observations
Thundersnow
Severe convective storms
– Elevated convection
– Convective morphology
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Other
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Mammatus
Drizzle
History of meteorology
Does it rain more on the weekends?
Why am I here?
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Develop strong interaction between research (University and FMI),
forecast operations (FMI), and the private sector (Vaisala).
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Summer Course on Mesoscale Meteorology and Predictability
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Mentor students/forecasters on their MS/PhD research and
publications
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Helsinki Testbed
– Use Testbed data in research and operations
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Research on mesoscale weather (fronts, sea breeze, convection)
Use dual-polarimetric radar for winter-weather processes
Data assimilation and high-resolution modeling
Value of Testbed data to forecasting
– Teach class on Testbed
Course Overview: Lectures
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Helsinki Testbed: Overview and its
importance
Other mesoscale observing networks
Instrumentation
Quality control
Data assimilation and numerical weather
prediction
Research methodologies for mesoscale data
How to obtain Testbed data
Applications of Testbed data: Road weather,
air quality, climate, hazardous weather
Good scientific communication skills
Course Overview: Lectures
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Helsinki Testbed: Overview and its
importance
Other mesoscale observing networks
Instrumentation
Quality control
Data assimilation and numerical weather
prediction
Research methodologies for mesoscale data
How to obtain Testbed data
Applications of Testbed data: road weather,
air quality, climate, hazardous weather
Good scientific communication skills
A big KIITOKSIA
to all the lecturers!
Project Requirements
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Purpose:
– Expose you to obtaining and using the Testbed data
– Get you to use the Testbed data in ways you wouldn’t
otherwise be doing for research
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About 40 hours of work outside of class time
Must use Helsinki Testbed data
Project can be part of your thesis research
– Use Testbed data other than dataset of your primary interest,
or
– Some aspect tangential to primary thesis research
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Can work alone or in small groups (1–3 people)
5–10-page written report due at your seminar
Course Overview: Projects
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Tuesday afternoon: initial discussion of ideas and organize into
groups by theme
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Wednesday afternoon, Thursday afternoon, and Friday morning:
work within groups to discuss the plan for the project, begin initial
phase of research
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Friday afternoon: group presentations and comments on class
projects
– 10-minute presentations with 5–8 powerpoint slides
– Peer-review of project design and initial findings
– Comments and advice from others
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Feb. 17–?: work on research
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Sometime in late March or early April: seminars to present results,
submit written reports (no later than 13 April)
Beware of the
room schedule!
Questions to Consider During Each
Presentation
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What limitations do these systems have?
Is designing/siting/instrumentation optimal?
Optimal for what?
What remaining research questions need to be
addressed?
What commercial and forecasting applications could
be developed?
How would you direct new resources to the Testbed
or research program in the future?
Expectations of Students
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This is not a passive course.
Learn the joys of participating!!!!!!
– Others may have the same questions as you.
– You will learn more and be more engaged.
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Class participation will be a factor in your grade
Ask questions of presenters (even during their talks!)
Interact with them during breaks
Consider the presenters as experts on:
– the types of data and applications of Testbed data
– project ideas you need for your class project or thesis research
The Helsinki Testbed:
If You Build It, They Will Come
An Outsider’s Perspective
Definition of a testbed
A testbed is a working relationship in a quasi-operational
framework among measurement specialists, forecasters,
researchers, the private sector, and government agencies
aimed at solving operational and practical regional _____
problems with a strong connection to the end users.
Outcomes from a testbed are more effective observing
systems, better use of data in forecasts, improved services,
products, and economic/public safety benefits. Testbeds
accelerate the translation of R&D findings into better
operations, services, and decision making. A successful
testbed requires physical assets as well as substantial
commitments and partnership.
Dabberdt et al. (2005): “Multifunctional mesoscale observing networks.”
Definition of a testbed
A testbed is a working relationship in a quasi-operational
framework among measurement specialists, forecasters,
researchers, the private sector, and government agencies
aimed at solving operational and practical regional _____
problems with a strong connection to the end users.
Outcomes from a testbed are more effective observing
systems, better use of data in forecasts, improved services,
products, and economic/public safety benefits. Testbeds
accelerate the translation of R&D findings into better
operations, services, and decision making. A successful
testbed requires physical assets as well as substantial
commitments and partnership.
Dabberdt et al. (2005): “Multifunctional mesoscale observing networks.”
Definition of a testbed
A testbed is a working relationship in a quasi-operational
framework among measurement specialists, forecasters,
researchers, the private sector, and government agencies
aimed at solving operational and practical regional _____
problems with a strong connection to the end users.
Outcomes from a testbed are more effective observing
systems, better use of data in forecasts, improved services,
products, and economic/public safety benefits. Testbeds
accelerate the translation of R&D findings into better
operations, services, and decision making. A successful
testbed requires physical assets as well as substantial
commitments and partnership.
Dabberdt et al. (2005): “Multifunctional mesoscale observing networks.”
Testbed Concept as a Process
Marty Ralph
NOAA/ETL-PACJET
Testbeds
Candidate
Sensors
Final Network
(regional or topical)
•surface met
•GPS receivers
•profilers
Outcome
•gap-filling radars
Improved
services
through NWP
& nowcasting
•buoys
•etc.
Fill gaps through
targeted sensor
development,
e.g., buoy profilers,
precipitation radars,
etc.
Temporary
Oversampling
Objective testing and
demonstration
Testbed results objectively
inform decisions on
changing the design of longterm regional observing
networks
The Helsinki Testbed:
Benefits Research, Operations,
Business, Public Sector, and End Users
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Research
– Improved ability to observe the atmosphere
– Improved parameterizations
– Better data to improve numerical weather prediction models
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Operations
– More data where it is needed -> better forecasts
– Development of short-term forecasting system (LAPS)
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Business
– Allows developing an end-to-end observation -> forecasting package for customers
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Public Sector
– Improved road maintenance
– More observations of air quality
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End Users
– Sailors and other outdoor enthusiasts love the availability of the data
The Testbed is a unique collaboration
between the public and private sector.
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WeatherBug
8,000 weather stations
across USA. Most of
these stations are
operated by schools and
governed by a local
television station.
http://en.wikipedia.org/wiki/WeatherBug
AWS Convergence Technologies, Inc., the National Weather Service
and the Department of Homeland Security: Weatherbug stations could
be used by Homeland Security to assess weather conditions in the
event of a disaster (2004)
The Testbed is a unique collaboration
between the public and private sector.
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Other examples of mesoscale observing networks.
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Oklahoma (and Texas) mesonets (mesonet.org)
Iowa and Minnesota mesonets
Mesowest
Weatherbug
Hydrometeorology Testbed, research-operational collaboration
But these are mostly surface observing networks.
The Helsinki Testbed has the added benefit of more 3D
observing systems (e.g., profilers, masts).
Definition of a testbed
A testbed is a working relationship in a quasi-operational
framework among measurement specialists, forecasters,
researchers, the private sector, and government agencies
aimed at solving operational and practical regional _____
problems with a strong connection to the end users.
Outcomes from a testbed are more effective observing
systems, better use of data in forecasts, improved services,
products, and economic/public safety benefits. Testbeds
accelerate the translation of R&D findings into better
operations, services, and decision making. A successful
testbed requires physical assets as well as substantial
commitments and partnership.
Dabberdt et al. (2005): “Multifunctional mesoscale observing networks.”
The Helsinki Testbed:
Solving Society’s Relevant Problems
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Saving lives and property is more than just providing the
perfect forecast
Hurricane Katrina
Public access to information
Communication of weather warnings
A few researchers have worked on the margins over the
years, always being considered an “add-on” to hard-core
meteorological and hydrological research
There is a growing awareness that improving the quality of
life requires a collaboration between atmospheric
scientists and other disciplines, particularly those from the
social sciences.
New culture change initiative:
Prof. Eve Gruntfest
Univ. of Colorado at Colorado Springs
www.rap.ucar.edu/was_is
WAS*IS
CULTURE CHANGE
weather & society * integrated studies
www.rap.ucar.edu/was_is/
Eve’s role – applied geographer
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Social scientist in
world of engineers &
physical scientists
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Career started in
Boulder with Big
Thompson Flood
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Focus: Flash floods
& warning systems
The Big Thompson Flood in
Colorado July 31, 1976
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140 lives lost - 35 miles
northwest of Boulder
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Studied the behaviors
that night
– Who lived?
– Who died?
– Led to detection &
response systems
You can’t outrun the flood
in your CAR, climb to
safety
Nearly 30 years later
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Signs
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FLASH FLOODS are
recognized as different
from slow rise floods
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Real- time detection,
some response
• More federal agencies do flood “warning”
• Vulnerability increases
Eve’s dream:
Social Science is MORE integrated in
METEOROLOGY
WAS*IS
The Helsinki Testbed is not only a
model for business, but also a model
for the economic value of observing
systems.
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What is the “optimal” observing network?
Rebecca Morss (National Center for Atmospheric Research, Boulder,
Colorado, USA): Economic value of observing systems
This work has not been done on the mesoscale before.
Is there a group of economists in Finland that could collaborate with us
on this topic?
Definition of a testbed
A testbed is a working relationship in a quasi-operational
framework among measurement specialists, forecasters,
researchers, the private sector, and government agencies
aimed at solving operational and practical regional _____
problems with a strong connection to the end users.
Outcomes from a testbed are more effective observing
systems, better use of data in forecasts, improved services,
products, and economic/public safety benefits. Testbeds
accelerate the translation of R&D findings into better
operations, services, and decision making. A successful
testbed requires physical assets as well as substantial
commitments and partnership.
Dabberdt et al. (2005): “Multifunctional mesoscale observing networks.”
Definition of a testbed
A testbed is a working relationship in a quasi-operational
framework among measurement specialists, forecasters,
researchers, the private sector, and government agencies
aimed at solving operational and practical regional _____
problems with a strong connection to the end users.
Outcomes from a testbed are more effective observing
systems, better use of data in forecasts, improved services,
products, and economic/public safety benefits. Testbeds
accelerate the translation of R&D findings into better
operations, services, and decision making. A successful
testbed requires physical assets as well as substantial
commitments and partnership.
Dabberdt et al. (2005): “Multifunctional mesoscale observing networks.”
A successful testbed should meet the
following criteria:
address the detection, monitoring, and prediction of
regional phenomena;
 engage experts in the phenomena of interest;
 define expected products and outcomes, and establish
criteria for measuring success;
 provide special observing networks needed for pilot
studies and research;
 define the strategies for achieving the expected
outcomes; and
 involve stakeholders in the planning, operation, and
evaluation of the testbeds.
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Dabberdt et al. (2005): “Multifunctional mesoscale observing networks.”
Themes-1
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Users demand higher temporal and spatial observations.
Customers demand even more timely and accurate
forecasts.
Better forecasts result from better data and better forecast
models.
Costs of constructing and maintaining observing systems
are increasing.
No single observing platform can do it all.
The present observational system was not designed from
the beginning as an optimal network.
Neither was the Helsinki Testbed. :-(
Themes-2
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“The predictability of specific weather systems that have
large effects on society or the economy is largely
unknown.” (Dabberdt and Schlatter 1995)
Applications of meteorological data depend are extremely
sensitive to good data and good model forecasts.
Weather forecasts and data “intersect a wide variety of
end products and services.” (Dabberdt et al. 2000)
“The value of these data is diminished to the extent that
they remain inaccessible.” (Dabberdt and Schlatter 1995)