530230 Mesoscale Atmospheric Network: The Helsinki Testbed David Schultz

1. 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 David.Schultz@fmi.fi http://www.cimms.ou.edu/~schultz

2. 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

3. Education 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

4. Education 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) 1996–present: 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

6. Research 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?

7. Why 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

8. Course 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

9. Course 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

10. A big KIITOKSIAto all the lecturers!

11. Project Requirements • 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 • 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 (1–3 people) • 5–10-page written report due at your seminar

12. Course 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 5–8 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)

13. Beware of the room schedule!

14. Questions 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?

15. Expectations 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

17. The Helsinki Testbed: If You Build It, They Will Come An Outsider’s Perspective

18. 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.”

19. 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.”

20. 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.”

21. Marty Ralph NOAA/ETL-PACJET Testbed Concept as a Process

22. Testbeds (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

23. The 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 -> better forecasts • Development of short-term forecasting system (LAPS) • Business • Allows developing an end-to-end observation -> 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

24. The 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)

25. The 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).

26. 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.”

27. The Helsinki Testbed: Solving Society’s 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.

28. New culture change initiative: Prof. Eve Gruntfest Univ. of Colorado at Colorado Springs www.rap.ucar.edu/was_is

29. Eve’s role – applied geographer • Social scientist in world of engineers & physical scientists • Career started in Boulder with Big Thompson Flood • Focus: Flash floods & warning systems

30. The 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 can’t outrun the flood in your CAR, climb to safety

31. Nearly 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. Eve’s dream: Social Science is MORE integrated in METEOROLOGY WAS*IS

33. The 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?

34. 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.”

35. 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.”

36. 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. Dabberdt et al. (2005): “Multifunctional mesoscale observing networks.”

37. Themes-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. :-(

38. Themes-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)