1. http://www.cmmap.orghttp://www.cmmap.org/ LaRC

2. This Presentation What is CMMAP? –Science & Motivation –History –Organization –Future plans The Grad Student Colloquium The CMMAP Team Meeting Expectations

3. CMMAP Is a “Science and Technology Center” (an “STC”) supported by the National Science Foundation (NSF) Involves more than 120 people from 30 institutions around the world! Is just starting its second year of a (likely) 10-year lifetime Is inventing a radically new way to predict weather and climate!

4. The Airplane Speech Numerical models of weather & climate Clouds are really important Connecticut is bigger than CSU Computers are way too slow Public opinion polling Shower curtains CMMAP

5. Cloud Processes Radiation Cloud-scale motions Cloud-scale motions Turbulence Precipitation These processes interact strongly on the cloud scale, and also with larger scales.

6. “...The modeling of clouds is one of the weakest links in the general circulation modeling efforts.” --Charney et al., National Academy Report, 1979 Deficiencies in the representation of cloud processes in climate models drive much of the uncertainty surrounding predictions of climate change. This was true 30 years ago, it’s true now, and unless we adopt a new approach it will still be true 30 years from now.

7. The problem is multiple scales. Cloud-scale processses Relatively well understood Global scale Bad news: Requires a very powerful computer.

8. Multiple Scales Cloud-scale processes Relatively well understood Global scale Meso-scale statistics Poorly understood

9. Cloud Parameterizations Current global models include the effects of cloud processes on unresolved scales through “parameterizations,” which are statistical theories, analogous to thermodynamics.

10. At very high resolution, a realistic model should grow individual clouds. A model that uses cloud parameterizations can’t do this. Therefore, global models have to be reformulated when run at high resolution. At very high resolution, a realistic model should grow individual clouds. A model that uses cloud parameterizations can’t do this. Therefore, global models have to be reformulated when run at high resolution.

11. Super-Parameterization: A Multiscale Modeling Framework This idea was proposed and first tested by Wojciech Grabowski.

12. Brief History of CMMAP

13. This Took A Long Time to Gestate November 2000: Dave asks Marat to embed his cloud model into the Community Atmospheric Model Summer 2001: Results look good … Dave considers proposing an STC October 2002: 60 leading cloud modelers from around the world come to CSU in a snowstorm and agree to propose an STC

14. CMMAP Prehistory Continued March 2003: STC proposals are invited by NSF May 2003: Pre-proposal planning in Hawaii. Dave promises to return to Kauai if we get funded June 2003: About 250 preproposals submitted to NSF October 2003: NSF invites a full proposal from 37 proto-Centers

15. CMMAP Prehistory Feb 2004: Full proposal submitted by CSU 30 seconds before the deadline! June 2004: NSF announces it will “Site Visit” 12 applicants October 2004: Site visit at CSU January 2005: NSF rejects 6 of the 12 site-visited Centers (not us!) May 2005: “Limbo” Team Meeting

17. CMMAP Timeline July 2006: CMMAP Award approved! August 2006: Kickoff team meeting at CSU Feb 2007: Second Team Meeting in Kauai Aug 2007: This meeting Feb 2008: Team meets at UCLA?

18. CMMAP Organization

19. We learn. We teach. We “transfer” what we have learned to the larger culture. CMMAP Components Required by NSF, but also a very good idea!

20. Component Shares of Budget Total is $4M/year, likely for 10 years

21. CMMAP Participants

22. Objectives, Working Groups, and Themes Organizing all this and reporting progress to NSF is a lot of work There are a lot of defined “objectives” required for reporting Too many for the Team Meetings “Working Groups” for objectives have been replaced by larger “Themes”

23. “Research Themes” Future tools (the new models) Low cloud feedback processes Shallow -> Deep Convection & Turbulence The Madden-Julian Oscillation

25. Future Tools Multiscale Modeling Framework (MMF) Quasi three-dimensional multiscale model (Q3D MMF) Global cloud resolving model (GCRM)

26. Families of Models

27. Quasi-3D MMF Full-blown CRM with big “holes” Real 3D physics at intersections

28. Quasi-3D MMF

29. Low-Cloud Feedbacks Theme

30. Shallow-Deep & Turbulence Theme

31. Unresolved Processes in MMF

32. The Madden-Julian Oscillation (MJO) Dominant pattern of variability of weather in the deep tropics “Wave” of clouds and rain passing about every 40-50 days Possibly related to El Nino onset Most global models don’t have MJO It wasn’t in the CAM, but when the cloud- resolving shower curtain was embedded, voila! MJO appeared! Why? How does the MJO work?

33. Simulated MJO is Realistic!

34. CMMAP Grad Student Colloquium Annual event for all CMMAP grad students (5 universities?) Opportunity to broaden grad education beyond research with your advisor & department Opportunity to collaborate across CMMAP institutions Ideal outcome: collaborations among future scientists that wouldn’t have happened otherwise!

35. Schedule

36. CMMAP Team Meeting

37. Aspirations CMMAP graduates will emerge having played a central role in the invention of a new way to predict weather & climate … will have strong collaborative relationships with young scientists at other leading universities … will be prepared professionally beyond their research areas –Teaching, Ethics, Writing, Funding, Policy, Diversity