1. The Unknown And The Unexpected: Climate Change And The Pacific Northwest Mark R. Abbott College of Oceanic and Atmospheric Sciences Oregon State University

2. Overview Global scale climate Modeling and climate Climate and the Northwest New ways to approach the unknowable

3. Historical Records of CO2

4. CO2 And Temperature

5. 20,000 years ago2200? ( + 5 meters) Past And Future Rise In Sea Level

6. Timeline Of Climate Model Development Figure courtesy W. Washington, NCAR

7. Impacts Of Spatial Resolution On The Types Of Terrain That Are Included In Models Figure courtesy S. Hostetler, USGS/OSU

8. What Was Predicted For Last Winter?

9. What Actually Happened?

10. An Impact Of Climate Change?

11. Climate Change Impacts Depend On Variability Variability may have more human impact than mean state Examples European heat wave Niger drought Figure courtesy A. Mix, OSU

12. The Five “Currencies” Of The Earth System Energy Water Carbon Money Information Next-generation Earth system models must account for all of these currencies

13. Innovation In Earth System Models The “Old” Way Increased temporal and spatial resolution Data assimilation and near real-time observatories and sensor networks Increasing coupling of components and increasing richness of models Impact on HPC requirements has been a focus on increased capacities for computation as well as on post-production analyses Can the community obtain the HPC resources it needs in a rapidly-changing market?

14. New Demands On Climate Models Not just increased resolution and more physics Risk assessments and scenarios Impacts of climate change on human migration patterns Rare but high impact scenarios Feedbacks between climate and socioeconomic processes Past as a poor predictor of the future Need to create diverse and resilient knowledge networks to develop and test scenarios Adaptive management rather than rigid protocols

15. System Architectures The Intel and AMD Approach General purpose systems for a wide array of applications 6 month technology cycle Science community started rolling their own clusters because of lower costs CPU MPI

16. Increasingly Complex Architectures Intel and AMD stalled at 3 GHz because of packaging issues (i.e., heat dissipation) Now going multi-core at lower frequency Increasingly complex programming model Low efficiencies because fundamental models require lots of shared memory (and hence message passing) Focus on communications infrastructure Hard to take generalized commodity systems and support innovation New architectures (CPU/GPU) now entering the fray Core 1 Core 2 Core 3 Core 4 Core 1 Core 2 Core 3 Core 4 MPI OpenMP

17. Is This Innovation? Community models Good for production runs and post-production analyses Good for education Not so good for adding new components and new physics and biogeochemistry Supercomputer centers Good for production runs of very large models Not especially efficient for exploration of new models and new approaches New architectures make it increasingly difficult to code We need more than a big data center with VT 100 terminals

18. Shifting The Context For IT Transforming our workflows Real-time, continuous, adaptive Shifting the balance of data and knowledge Collaborative, networked, interdisciplinary Not just bigger and faster A collection of adaptable, dynamic services Increased customization in a commodity world HPC-enabled components live everywhere, not just data centers End-to-end, user experience is critical Not just in the office or lab

19. A New Approach? Overcoming language and cultural barriers to enable collaboration Merging data streams and sensors Developing and testing models Seeking out underlying and emergent rules to make projections and predictions This looks more like a network gaming metaphor New capabilities include Preservation, provenance, collaboration, accountability, and reputation

20. Shifting The Community From data delivery to knowledge services The Wikipedia model for smart mobs Networks of potential resources Innovation will come from the fringes More “democracy” in the system What used to be expensive and complex is now available to everyone Need for standard, open frameworks Simple and extensible Not driven solely by science requirements But still require enormous amount of work

21. Convergences New IT capabilities will bring more integration among diverse communities, data sets, and models New demands for climate models and climate services will require these capabilities Need a resilient approach to the complexities and uncertainties of the future

22. © 2007 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

23. Microsoft Research Faculty Summit 2007