The Uncoordinated Giant: Why U.S. Weather Research and Prediction are Not Achieving their Potential

2. The Uncoordinated Giant: Why U.S. Weather Research and Prediction are Not Achieving their Potential Cliff Mass Atmospheric Sciences University of Washington The U.S. Weather Prediction Enterprise is very big but uncoordinated.

3. April Bulletin of the AMS

4. The U.S. Weather Prediction Enterprise Has Accomplished a Great Deal During the Past Decades

5. Dramatic Improvements in Numerical Weather Prediction

6. Large Advances in Weather Observation Technology

8. Camano Island Weather Radar

9. Substantial Improvements in Weather Sensors

10. The Development of a Vigorous Private Sector

11. Aggressive Use of the Internet and other New Dissemination Approaches.

12. Substantial Advances in Understanding of Weather Systems and Basic Processes.

13. But Even With These Advances We Have Accomplished Far Less Than Our Potential and in a Number of Areas the U.S. Have Lost World Leadership This talk will suggest that our progress has been undermined by the inability of the major sectors of the weather prediction community to work together effectively.

14. Warning Signs • The skill of the GFS, the main U.S. global weather prediction model, lags that of others (e.g., ECMWF).

15. 500 mb Height--24h

16. The U.S. Weather Research Program—whose goal was to coordinate and support the nation’s weather research--is essentially dead, ended by a lack of funding, vision, and interest.

17. Warning Signs • Major deficiencies exist in key forecast model parameterizations (e.g., planetary boundary layer, microphysics) and there is minimal community coordination and joint research to deal with them. • Disturbingly, the intellectual resources needed to deal with such major problems are declining. (How many PBL researchers are in our department now versus 30 years ago?)

21. Warning Signs Although weather prediction is essentially probabilistic, the community has held to a deterministic paradigm, failing to provide our users with critical probabilistic information.

22. A new forecast preparation/dissemination approach (IFPS) was developed by the NWSthat is completely deterministic and which burdens forecasters with producing single renditions of reality every six hours for seven days.

23. Exact Forecasts Out Several Days at Every Location!

24. Starving Probabilistic Prediction • U.S. efforts to create short-term, mesoscale ensembles have been underfunded and inadequate. • Virtually no post-processing of ensembles to produce reliable probabilistic forecasts (pdfs)

25. The Communication Deficit • There has been virtually no research on how to best communicate weather information. • Current icons are inconsistent and often irrational. • Icons and other approaches are used with little understanding of how people interpret them.

26. Iconology And what does probability of precipitation really mean? A large proportion of the population doesn’t really know.

27. Short-Term Forecasting: Our Greatest Failing • With improving radar, mesonets, short-term NWP, and physical understanding, meteorologists know a great deal of what is happening now and during the next few hours….that is not communicated. • Example: radar and MM5 indicate a profound rain-shadow that will persist for the remainder of the day. NWS and media provide forecast of “scattered showers” • There has never been as much discrepancy between what meteorologists know and what information the public gets.

28. Example 2: Puget Sound Rain Shadow Camano Island Radar 1-h Precip. Total

29. High Resolution MM5 Does Very Well With Rainshadows

30. NWS Forecasts Miss It Completely

31. WAZ006>008-062330- EVERETT AND VICINITY-SEATTLE METROPOLITAN AREA-TACOMA AREA-INCLUDING THE CITIES OF...EVERETT... EDMONDS... LYNNWOOD...MARYSVILLE...ARLINGTON...SEATTLE...BELLEVUE...FEDERAL WAY... KENT...RENTON…TACOMA ...LAKEWOOD... PUYALLUP...SUMNER 330 AM PST SUN NOV 6 2005 .TODAY...SHOWERS LIKELY. HIGHS IN THE UPPER 40S. SOUTHWEST WIND 10 TO 20 MPH. TEMPERATURE / PRECIPITATION EDMONDS 49 40 47 / 60 60 60 EVERETT 48 40 45 / 60 60 60 SEATTLE 48 41 46 / 60 60 60 BELLEVUE 49 41 48 / 60 60 60 PUYALLUP 49 40 47 / 60 60 60 TACOMA 48 39 46 / 60 60 60

32. Increasing Tensions Among the Weather Enterprise • Tensions have developed among the community, particularly at the interface between the private and governmental sectors. • The private sector feels that the NWS is invading their territory with Internet and wireless delivery, and is providing “custom forecasts” to potential clients. • A group of private sector companies convinced Senator Rick Santorum to introduce legislation that would limit the NWS to warnings and collecting observations/NWP Penn. Senator Santorum (a.k.a., the Senator from Accuweather)

35. And Other Tensions • NCAR and NCEP over the development of a new national mesoscale model (WRF)

36. Inefficient and Poorly Organized Research Structure in NOAA • The government research laboratories that are tasked to supply new scientific and technical advances for the NWS are OUTSIDE of the organization, under NOAA’s Office of Atmospheric and Oceanographic Research • Without direct management by the “user” agency and with research tasks balkanized over many labs, the research agenda has been inefficient, developing technologies that are unneeded or redundant, and not dealing with acute problems.

37. Lack of Critical Mass: Too Many Weather Prediction Models • NWS NCEP: Eta, GFS, Regional Spectral, WRF-NMM • Navy: COAMPS, NOGAPS, NORAPS • NCAR: MM5, WRF-ARW • Oklahoma: ARPS • Colorado: RAMS • MESO Inc: MASS model • …and several more!

38. Too Many Models • Some competition is good, and we don’t want to put all our eggs in one basket, but we have clearly divided the community between too many modeling systems for our own good. • The NWS and universities have generally used different models. Eta has been the main mesoscale model for the NWS, MM5 (and now WRF) for the academic community. A real problem for the transfer of research results to operations.

39. The WRF Model Saga Same Pronunciation • The WRF (Weather Research and Forecasting) model was conceived as a way to bring the academic and operational communities together under one model infrastructure for mesoscale prediction. • Plug compatible physics would be easy to switch and test. • Completely new model with better, numerics, clean code and easily parallelized.

40. The Reality • The NWS and NCAR went in separate directions with different dynamic cores. • NWS: NMM core • NCAR/Universities: ARW core • The plug compatible physics that would allow various cores to use the same physics has not panned out. • The infrastructure…the software framework that it all works in has proven difficult to modify and understand. • Decision making has been limited to NCAR and a few Federal agencies. • NWS and NCAR going separate ways on data assimilation

41. These Issues Have Developed at the Same Time as the U.S. Meteorological Community Has Experienced Great Structural Changes

42. Structural Changes • The private sector has grown rapidly and stands as an equal to the government and academic sectors. • The National Weather Service is now a much smaller piece of the pie. • The boundaries between the sectors have become more diffuse.

43. The Boundaries Are Fading • All sectors now do NWP • All sectors disseminate information to the public • (even the universities through their web pages and involvement with the media—e.g., Penn. State produced weather page in the NY Times) • All sectors are involved in data collection. • Such overlap is really a very healthy development, promoting creativity and cross-fertilization, assuming it does not lead to conflict and tensions.

44. Still a Giant • We (the U.S.) still have many things going for us: • The world’s largest meteorological academic community. • The largest and most successful private sector community. • The largest governmental research community. • Demonstrated great creativity. • But we have not effectively combined our resources…both intellectual and financial…to make the rapid progress of which we are capable. • Often overseas competitors take our technologies and beat us to operational implementation (e.g., 4DVAR)

45. A Number of Groups Have Realized We Have a Problem

46. Pielke and Carbone 2002 • The goals of the weather prediction enterprise “are unlikely to be reached if the community proceeds in a balkanized fashion that has characterized it in the past.” • “No organization or entity has embraced the collective measure of responsibility for improving forecast processes.”

47. National Research Council: 1998 Report on the Future of the Atmospheric Sciences “Today, there is reason for considerable concern about planning for atmospheric research. No one sets the priorities; no one fashions the agenda…. Thus, BASC believe that a national research environment requires a strong disciplinary planning mechanism. ... all partners in the atmospheric enterprise –in government, in universities, and in a variety of commercial undertakings– must join together as an effective team focused on the future.”

48. NRC FairWeather Report (2003) • Suggests that the various components of the Weather Enterprise needs to work together more effectively. • Provides some potential approaches (e.g., AMS set up a neutral arbiter)

49. Weather Coalition: Private Sector/University “Lobbying Group” for the Enterprise

50. New AMS Commission on the Weather Enterprise