Title: If You Build It, They Will Come!
1530230 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 David.Schultz_at_fmi.fi http//www.cimms
.ou.edu/schultz
2Who 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
3Education and Experience
- (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
4Education and Experience
- (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) 1996present Cooperative Institute for
Mesoscale Meteorological Studies (CIMMS),
University of Oklahoma, and NOAA National Severe
Storms Laboratory (NSSL), Norman, Oklahoma
5- 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
6Research Interests
- Observationalist and diagnostician, model user,
some theory - Over 60 publications
- Cyclone/frontal structure and evolution
- Winter-weather processes
- Precipitation banding
- Snow density
- Radar observations
- Thundersnow
- Severe convective storms
- Elevated convection
- Convective morphology
- Other
- Mammatus
- Drizzle
- History of meteorology
- Does it rain more on the weekends?
7Why am I here?
- Develop strong interaction between research
(University and FMI), forecast operations (FMI),
and the private sector (Vaisala). - Summer Course on Mesoscale Meteorology and
Predictability - Mentor students/forecasters on their MS/PhD
research and publications - Helsinki Testbed
- Use Testbed data in research and operations
- 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
8Course Overview Lectures
- 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
9Course Overview Lectures
- 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
10A big KIITOKSIA to all the lecturers!
11Project Requirements
- Purpose
- Expose you to obtaining and using the Testbed
data - Get you to use the Testbed data in ways you
wouldnt otherwise be doing for research - 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
- Can work alone or in small groups (13 people)
- 510-page written report due at your seminar
12Course Overview Projects
- Tuesday afternoon initial discussion of ideas
and organize into groups by theme - Wednesday afternoon, Thursday afternoon, and
Friday morning work within groups to discuss the
plan for the project, begin initial phase of
research - Friday afternoon group presentations and
comments on class projects - 10-minute presentations with 58 powerpoint
slides - Peer-review of project design and initial
findings - Comments and advice from others
- Feb. 17? work on research
- Sometime in late March or early April seminars
to present results, submit written reports (no
later than 13 April)
13Beware of the room schedule!
14Questions to Consider During Each Presentation
- 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?
15Expectations of Students
- 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.
- 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
16(No Transcript)
17The Helsinki Testbed If You Build It, They Will
Come
An Outsiders Perspective
18Definition 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 RD 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.
19Definition 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 RD 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.
20Definition 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 RD 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.
21Testbed Concept as a Process
22Testbeds (regional or topical)
Final Network
Candidate Sensors
- surface met
- GPS receivers
- profilers
- gap-filling radars
- buoys
- etc.
Outcome Improved services through NWP nowcasting
Temporary Oversampling Objective testing and
demonstration
Fill gaps through targeted sensor
development, e.g., buoy profilers, precipitation
radars, etc.
Testbed results objectively inform decisions on
changing the design of long-term regional
observing networks
23The Helsinki Testbed Benefits Research,
Operations, Business, Public Sector, and End Users
- Research
- Improved ability to observe the atmosphere
- Improved parameterizations
- Better data to improve numerical weather
prediction models - Operations
- More data where it is needed -gt better forecasts
- Development of short-term forecasting system
(LAPS) - Business
- Allows developing an end-to-end observation -gt
forecasting package for customers - Public Sector
- Improved road maintenance
- More observations of air quality
- End Users
- Sailors and other outdoor enthusiasts love the
availability of the data
24The Testbed is a unique collaboration between the
public and private sector.
- 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)
25The Testbed is a unique collaboration between the
public and private sector.
- Other examples of mesoscale observing networks.
- 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).
26Definition 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 RD 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.
27The Helsinki Testbed Solving Societys Relevant
Problems
- 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.
28New culture change initiative Prof. Eve
Gruntfest Univ. of Colorado at Colorado
Springs www.rap.ucar.edu/was_is
29Eves role applied geographer
- Social scientist in world of engineers physical
scientists - Career started in Boulder with Big Thompson Flood
- Focus Flash floods warning systems
30The Big Thompson Flood in Colorado July 31, 1976
- 140 lives lost - 35 miles northwest of Boulder
- Studied the behaviors that night
- Who lived?
- Who died?
- Led to detection response systems
- You cant outrun the flood in your CAR, climb to
safety
31Nearly 30 years later
- Signs
- FLASH FLOODS are recognized as different from
slow rise floods - Real- time detection,
- some response
- More federal agencies do flood warning
- Vulnerability increases
32 Eves dream Social Science is MORE
integrated in METEOROLOGY WASIS
33The Helsinki Testbed is not only a model for
business, but also a model for the economic value
of observing systems.
- 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?
34Definition 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 RD 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.
35Definition 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 RD 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.
36A 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.
Dabberdt et al. (2005) Multifunctional
mesoscale observing networks.
37Themes-1
- 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. -(
38Themes-2
- 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)