Overview

1. Overview Scientific Advisory Committee Meeting 26 September 2011

2. SAC membersand agency colleagues - Welcome!

3. Special Welcome!Dennis LettenmaierNew SAC Member

4. Congratulations!Tim Palmer Elected President, Royal Meteorological Society

5. Congratulations!Jim Hurrell Selected Director, NCAR Earth System Laboratory

6. SAC Meeting Goals Highlight COLA progress since last SAC meeting (April 2010) Get SAC advice on current and future plans for COLA research and broader engagement activities

7. Vision and Mission VISION Global society benefits from basic and applied research and education on climate variability and predictability and the free access to data and research tools MISSION Explore, establish and quantify the predictability and prediction of intra-seasonal to decadal variability in a changing climate

8. … and in a probabilistic framework The laws of probability, so true in general, so fallacious in particular. - Edward Gibbon

9. COLA Uniqueness • Critical mass of excellent climate scientists working together • Experimentation with multiple national climate models • Stable, multi-agency funding and external expert advice • Scientific leadership in national/international I-S-I climate research • Co-sponsorship with GMU of PhD program in Climate Dynamics • Highly-valued, widely-used software: GrADS • High-capacity in-house computing facility • Building global capacity: creating weather & climate research institutions

10. COLA Uniqueness • Critical mass of excellent climate scientists working together • Experimentation with multiple national climate models • Stable, multi-agency funding and external expert advice • Scientific leadership in national/international I-S-I climate research • Co-sponsorship with GMU of PhD program in Climate Dynamics • Highly-valued, widely-used software: GrADS • High-capacity in-house computing facility • Building global capacity: creating weather & climate research institutions

11. Pres., IGES (1993-present) Dir. COLA (1993-2004) Exec. Dir. COLA (1993-2004) Dir. COLA (2005-present) Your most precious possessions are the people you have working there, and what they carry around in their heads, and their ability to work together. - Robert Reich

12. COLA Uniqueness • Critical mass of excellent climate scientists working together • Experimentation with multiple national climate models • Stable, multi-agency funding and external expert advice • Scientific leadership in national/international I-S-I climate research • Co-sponsorship with GMU of PhD program in Climate Dynamics • Highly-valued, widely-used software: GrADS • High-capacity in-house computing facility • Building global capacity: creating weather & climate research institutions

13. Experimentation with the Nation’s Climate Models NCAR CAM4 GFDL AM2 GSFC GEOS5 NCEP GFS2 POP4 MOM4 MOM4 MOM4 CCSM4 CESM1 CFSv2 (CFSv1) GEOS_CM CM2.x Multi-Model Ensemble

14. COLA Uniqueness • Critical mass of excellent climate scientists working together • Experimentation with multiple national climate models • Stable, multi-agency funding and external expert advice • Scientific leadership in national/international I-S-I climate research • Co-sponsorship with GMU of PhD program in Climate Dynamics • Highly-valued, widely-used software: GrADS • High-capacity in-house computing facility • Building global capacity: creating weather & climate research institutions

15. “Omnibus” Funding COLA is a private, non-profit research institute supported by NSF (lead), NOAA and NASA through a single jointly-peer-reviewed *, jointly-funded five-year proposal. 2009-2014 Predictability of the Physical Climate System Funding: ~$3.6 M / yr Principal Investigator: Kinter Co-Investigators: Cash, DelSole, Dirmeyer, Huang, Jin, Klinger, Krishnamurthy, Schneider, Shukla, Straus “Science is a wonderful thing if one does not have to earn one's living at it.” - Albert Einstein 2004-2008 Predictability of Earth’s Climate Funding: ~$3.25M / yr (NSF - 46%; NOAA - 39%; NASA - 15%) Principal Investigator: Shukla Co-Investigators: DelSole, Dirmeyer, Huang, Kinter, Kirtman, Klinger, Krishnamurthy, Misra, Schneider, Schopf, Straus 1999-2003 Predictability and Variability of the Present Climate Funding: ~$2.75M / yr Principal Investigator: J. Shukla Co-PIs: J. Kinter, E. Schneider, P. Schopf, D. Straus Co-investigators: P. Dirmeyer, B. Huang, B. Kirtman 1994-1998 Predictability and Variability of the Present Climate Funding: $2.25M /yr Principal Investigator: J. Shukla Co-PIs: J. Kinter, E. Schneider, D. Straus * Thanks to our peers and the agencies

16. “Omnibus” Funding COLA is viewed as a major interagency National center of excellence: • Box 5-1 Major Interagency Programs • U.S. Climate Change Science Program (CCSP) • U.S. Weather Research Program (USWRP) • National Space Weather Program (NSWP) • Center for Ocean-Land-Atmosphere Studies (COLA) 2006

17. COLA Uniqueness • Critical mass of excellent climate scientists working together • Experimentation with multiple national climate models • Stable, multi-agency funding and externalexpert advice • Scientific leadership in national/international I-S-I climate research • Co-sponsorship with GMU of PhD program in Climate Dynamics • Highly-valued, widely-used software: GrADS • High-capacity in-house computing facility • Building global capacity: creating weather & climate research institutions

18. COLA Scientific Advisory Committee THANK YOU!

19. COLA Scientific Advisory Committee

20. Advice from SAC 2010 • COLA should maintain its role as “honest broker” • COLA management should provide emphasis on, and coordination and prioritization of core activities • COLA should focus on its niche (I-S-I) and avoid mission creep, e.g. overemphasis on Decadal, Athena projects • COLA should coordinate closely with NCAR, NCEP • COLA should maintain its independence in transition to GMU

21. COLA Involvement with NCEP, NCAR: NMME and CFSv3 • NMME – National Multi-Model Ensemble • Real-time seasonal forecast ensembles with CCSM3beinggiven to NCEP (in collaboration with U. Miami) • Proposal to CPO FY12 AO: real-time seasonal forecast ensembles with CCSM4 • collaboration with ESRL, GFDL, GMAO, U. Miami, NCAR, IRI, Princeton, and NCEP • Heavy leveraging of COLA I-S-I project and results • Design of next generation operational I-S-I prediction model • COLA and CTB spearheading groundbreaking R2O activity • Involving research scientists from outside NCEP and including private sector input • Very successful workshop on 25-26 August 2011

22. Experimentation with National Models Real-time NMME as of August 2011: NCAR CAM4 GFDL AM2 GSFC GEOS5 NCEP GFS2 POP4 MOM4 MOM4 MOM4 CCSM4 CESM1 CFSv2 (CFSv1) GEOS_CM CM2.x Multi-Model Ensemble

23. COLA Involvement with NCEP, NCAR: NMME and CFSv3 • NMME – National Multi-Model Ensemble • Real-time seasonal forecast ensembles with CCSM3 being given to NCEP (in collaboration with U. Miami) • Proposal to CPO FY12 AO: real-time seasonal forecast ensembles with CCSM4 • collaboration with ESRL, GFDL, GMAO, U. Miami, NCAR, IRI, Princeton, and NCEP • Heavy leveraging of COLA I-S-I project and results • Design of next generation operational I-S-I prediction model • COLA and CTB spearheading groundbreaking R2O activity • Involving research scientists from outside NCEP and including private sector input • Very successful workshop on 25-26 August 2011

24. COLA Uniqueness • Critical mass of excellent climate scientists working together • Experimentation with multiple national climate models • Stable, multi-agency funding and external expert advice • Scientific leadership in national/international I-S-I climate research • Co-sponsorship with GMU of PhD program in Climate Dynamics • Highly-valued, widely-used software: GrADS • High-capacity in-house computing facility • Building global capacity: creating weather & climate research institutions

25. Panels and Working Groups COLA

26. COLA Leadership – Current Examples Editors: Adv. Atmospheric Science (Huang) Climate Dynamics(Schneider) J. Climate(DelSole) IPCC AR5 (DelSole, Lu, contributing authors) Climate change assessement; also contributions from others (e.g. ZOD and FOD reviewers) International Advisory Panel for Weather and Climate, India (Shukla, chair; Palmer, Uccellini, members) Advise Indian government on weather forecasting and climate prediction (research and operations) NRC BASC Panel on Advancing Climate Modeling (Kinter, member) Advise US government on climate modeling strategy for 10-20 year horizon UCAR Community Advisory Committee for NCEP (Kinter, co-chair) Advise NCEP on strategic direction for 5-10 year horizon US CLIVAR PPAI Panel (Stan, member) Set agenda for Predictability, Predictions and Applications Interface World Climate Modeling Summit(Shukla, chair; Kinter, member) Very successful meeting in May 2008  multiple BAMS articles in 2010

27. COLA Uniqueness • Critical mass of excellent climate scientists working together • Experimentation with multiple national climate models • Stable, multi-agency funding and external expert advice • Scientific leadership in national/international I-S-I climate research • Co-sponsorship with GMU of PhD program in Climate Dynamics • Highly-valued, widely-used software: GrADS • High-capacity in-house computing facility • Building global capacity: creating weather & climate research institutions

28. Education COLAand George Mason University (GMU) established (2003) a new Ph.D. Program in Climate Dynamics in the School of Computational Sciences (SCS). Became Climate Dynamics Department in College of Sciences in 2006. Now part of Department of Atmospheric, Oceanic and Earth Sciences. • Current Graduate Students • K. Arsenault (Shukla/Dirmeyer/Houser) • A. Badger (Jin) • G. Bucher (Boybeyi) • H. Chen (Schneider) • I. Colfescu (Schneider) • X. Feng (Lu) • A. Garuba (Klinger) • A. Hazra (Klinger) • Y. Jang (Straus) • L. Jia(DelSole) • L. Krishnamurthy (Krishnamurthy) • E. Lajoie (DelSole) • J. Li (Huang) • J. Nattala (Kinter) • E. Palipane (Lu) • M. Scafonas (Lu) • B. Singh (Krishnamurthy) • A. Srivastava (Shukla) • E. Stofferahn (Boybeyi) • E. Swenson (Straus) • L. Xu(Shukla) • X. Yan (DelSole) • Climate Dynamics Faculty • Faculty (0.5 FTE): Boybeyi, Chiu, DelSole, Huang,Jin, Kinter, Klinger, Lu, Schneider, Schopf, Shukla (Director, CLIM), Stan, Straus(chair, AOES) • Adjunct:Dirmeyer (selected for 2012 appointment), Doty, Krishnamurthy • Bold = 2011 graduate

29. 2002-2010 GMU-CD Ph.D.s DeepthiRole of the Indian and Pacific Oceans in Indian Summer Monsoon Variability Achuthavarier(post-doctoral associate, COLA) Whit Anderson Oceanic Sill - Overflow Systems: Investigation and Simulation with the Poseidon OGCM (post-doctoral associate, NOAA GFDL) Susan Bates The Role of the Annual Cycle in the Coupled Ocean-Atmosphere Variability in the Tropical Atlantic Ocean (research scientist, NCAR) Robert Burgman ENSO Decadal Variability in a Tropically-Forced Hybrid Coupled Model (faculty member, Florida International University) Carlos CruzGlobal Ocean Circulation Variability Induced by Southern Ocean Winds (research scientist, NASA Goddard) Meizhu Fan Low Frequency North Atlantic SST Variability: Weather Noise Forcing and Coupled Response (research scientist: NOAA NESDIS) Xia FengNew Methods For Estimating Seasonal Potential Climate Predictability (post-doctoral associate, GMU) Laura Feudale Extreme Events in Europe & N. America During 1950-2003: An Observational & Modeling Study (research scientist, ARPA/OSMER) Daeho Jin The Impact of ENSO on the Extratropics (post-doctoral associate, University of Maryland) Julia ManganelloThe Influence of SST Anomalies on Low-Frequency Variability of the North Atlantic Oscillation (research scientist, COLA) BalaNarapusetty Impact Of Tropical Instability Waves In The Eastern Equatorial Pacific (post-doctoral associate, COLA) Xiaohua Pan Impact of Mean Climate on ENSO Simulation and Prediction (post-doctoral associate, UMBC/GEST) Kathy Pegion Potential Predictability of Tropical Intraseasonal Variability in the NCEP CFS (research scientist, CIRES, University of Colorado) Mary Ellen Verona Observational Analysis and Numerical Simulation of 1997-1998 El Niño (deceased) Yuri Vikhliaev Decadal Extra-Tropical Pacific Variability (post-doctoral associate, NASA Goddard) TugrulYilmazImproving Land Data Assimilation Performance With A Water Budget Constraint (research scientist, USDA)

30. Xu Badger Swenson JiaArsenaultGarubaHazraColfescu NarapusettyLaJoieCruzLiFeng Krishna- NattalaChen murthy Current students and recent graduates not pictured: Bucher, Jang, Palipane, Scafonas, Singh, Srivastava, Stofferahn, Yan, and Yilmaz

31. CLIM 101: Global Warming - Weather, Climate and Society The signs of global climate change can be seen all over the Earth. Some regions are already experiencing dramatic changes and more changes are expected in the future. The costs to society and ecosystems may be huge. Information about climate change is immensely valuable, and a public educated about the scientific basis for these changes is essential. This course provides a survey of the scientific and societal issues associated with weather and climate variability and change. It will enable students to critically examine arguments being discussed by policy makers, corporations, and the public at large. The current debate on climate change will be discussed from a scientific point of view, with a focus on those aspects that have the largest potential impact on global society. CLIM 101 is open to all undergraduate students and fulfills the General Education Natural Science (non-laboratory) requirement. Instructors: Jim Kinter and JagadishShukla Offered since 2008. 47 students enrolled in 2011

32. COLA Uniqueness • Critical mass of excellent climate scientists working together • Experimentation with multiple national climate models • Stable, multi-agency funding and external expert advice • Scientific leadership in national/international I-S-I climate research • Co-sponsorship with GMU of PhD program in Climate Dynamics • Highly-valued, widely-used software: GrADS • High-capacity in-house computing facility • Building global capacity: creating weather & climate research institutions

33. GrADS • GrADS is an essential tool for COLA research and data management (at COLA and at NCAR) and essential to the COLA "brand". • GrADS has over 75,000 users worldwide • We know of no other university-based, PI-driven geoscience software in use by more than just a few people. • COLA’s long-term, stable, multi-agency funding enables GrADSto be both nimbly responsive to user needs and dedicated to long-term design and planning. • GrADS figures are frequently found in weather and climate journals • GrADS is used to generate images on many weather and climate web pages hosted by NOAA, NASA, Universities, and a variety of International Agencies (http://iges.org/grads/gotw.html) • Funded at a minimal level by COLA Omnibus and intermittent external grants (NASA & NOAA)

34. GrADS is Used Worldwide 77,500 downloads February 2010 - Present

35. Data Management at COLA • New, more cost-effective design • Isolate and curate frequently used static data (shared) • Good metadata, logical organization • Automated catalogue • Scientists make data management decisions • Design builds on collaboration with NCAR-CISL • Promote best practices among data curators, users

36. Selected Past COLA Achievements • Established scientific basis for dynamical S-I prediction • Established critical role of land surface in climate predictability • Established feasibility of reanalysis • Organized DSP project (in connection with PROVOST) • Advanced the multi-model ensemble • Helped quantify limits of climate predictability associated with L-A and O-A interactions • Initiated development of framework for climate predictability and prediction • Showed that model fidelity determines model predictability

37. Highlights of Today’s Presentations • ISI prediction – predictability rebound • Develops as a result of coupling of climate system components, e.g., L-A, O-A • Consistent with “predictability in the midst of chaos” • Seamless prediction • Applying NWP technology for climate prediction: higher resolution is necessary but not sufficient for improving climate model fidelity • Weather predictability ≈ error growth || Climate predictability ≈ signal/noise • Decadal predictability and prediction • Rigorous scientific basis for decadal predictability. Evidence for multi-decadal modes of variability; however, we don’t know how to initialize those modes • Decadal predictions with CFSv2 (CMIP5) • Detected predictability due to changing GHG forcing and ENSO; nothing in between • Hypothesis-based experimentation • To provide feedback to model development, need experiments to test hypotheses

38. Predictability from L-A Coupling • Top: CCSM4 (1850) correlation between initial ½ day soil moisture perturbations and 1-day T2m anomalies. • Bottom: GSWP2 seasonal index of coupling between soil moisture and evaporation. • Red shading links high land IC impacts on atmosphere (top) to strong land-atmosphere coupling (bottom).

39. Impact of Land and Ocean on Precipitation Prediction GLACE-2: COLA AGCM 10-member ensemble hindcasts for 1986-1995 signal/total ratio 80% for land (green), specified SST (blue), and both (purple) dots indicate 95% significance

40. Ensemble Mean IC Improves Signal-to-noise Ratio Ensemble initialization from multiple ocean initial states may be the key to predicting the tropical Atlantic 6 ODA Products: ORA-S3 (ECMWF) NEMO-Var (ECMWF) GODAS (NCEP) CFS-R (NCEP) SODA (UMCP) ECDA (GFDL) Initializing 1 Model: CFSv2

41. Obs Decadal NINO3.4 SSTA Hindcasts (CMIP5)with CFSv2 (NEMO-Var ocean ICs) Model (ens 4)

42. Scientific Basis for Decadal Prediction Autocorrelation squared 5% significance Time Lag (years) Most Predictable Component Most predictable component of annual average SST in CMIP3 control simulations, projected onto 300-year control simulations of individual models  some models show skillful prediction to ~10-year lead-time DelSole, Tippett and Shukla (2011)

43. The Athena Project, 2009-2011:Revolutionizing Climate Modeling • Exploring hypothesis that high spatial resolution and process-resolving models can dramatically improve simulation of climate

44. Basis for Seamless Prediction • WCRP, 2005:  The world climate research programmestrategic framework2005-2015. WMO/TD-No. 1291. • Palmer, T. N.and co-authors, 2008: Toward seamlessprediction: Calibration of climate change projections using seasonal forecasts. Bull. Amer. Meteor. Soc., 89, 459–470. • Dole, R., 2008: Linking weather and climate. Synoptic-Dynamic Meteorology and Weather Analysis and Forecasting. Meteor. Monogr., 55, Amer. Meteor. Soc., 297-348. • Hurrell, J., and co-authors, 2009: A unifiedmodeling approach to climate system prediction. Bull. Amer. Meteor. Soc., 90, 1819-1832. • Brunet, G., and co-authors, 2010: Collaboration of the weather and climate communitiesto advance subseasonal-to-seasonal prediction. Bull. Amer. Meteor. Soc., 91, 1397-1406. • Hazeleger, W., and co-authors, 2010: EC-Earth: A seamlessEarth-system predictionapproach in action. Bull. Amer. Meteor. Soc., 91, 1357-1364. • Shukla, J., and co-authors, 2010: Toward a new generation of world climate research and computing facilities. Bull. Amer. Meteor. Soc., 91, 1407–1412. • Shapiroand co-authors 2010: An Earth-system predictioninitiativefor the twenty-first century. Bull. Amer. Meteor. Soc., 91, 1377-1388.

45. Collaborating Groups • COLA– USA (NSF-funded 1.0 FTE) • CrayInc.– USA (in-kind support) • ECMWF– EU (in-kind support) • JAMSTEC– Japan (in-kind support) • NICS University of Tennessee – USA (NSF-funded 6 months supercomputing) • RIKEN– Japan (in-kind support; data archival support) • University of Tokyo– Japan (in-kind support) Codes • IFS: ECMWF Integrated Forecast System (T159 – T2047) • NICAM: Nonhydrostatic Icosahedral Atmospheric Model (7 km) Supercomputers • Athena: Cray XT4 - 4512 quad-core Opteron nodes (18048) • #30 on Top500 list (November 2009) – dedicated Oct’09 – Mar’10 • Kraken: Cray XT5 - 8256 dual hex-core Opteron nodes (99072) • Total: ~80 million core-hours; 1.2 PB output

46. Mean Precipitation Change inEurope’s Growing Season: 21st C minus 20th C T159 (128-km) T1279 (16-km) “Time-slice” runs of the ECMWF IFS with observed SST for the 20th century and CMIP3 projections of SST for the 21st century at two different model resolutions.

47. Athena Publications • Dirmeyerand 15 co-authors, 2011a: Hydrologic Diurnal Cycle.Climate Dyn., (submitted; accepted). • Dirmeyerand 12 co-authors, 2011b: Land-Atmosphere Feedback in a Warming Climate. J. Hydrometeorology(submitted). • Jung and 12 co-authors, 2011: Experimental Design, Model Climate and Seasonal Forecast Skill. J. Climate (submitted; accepted). • Kinterand 29 co-authors, 2011: Revolutionizing Climate Modeling. Bull. Amer. Met. Soc. (submitted, March 2011). • Manganello and 13 co-authors, 2011: Tropical Cyclones: Toward Weather-Resolving Climate Modeling. J. Climate(submitted; minor revision). • Sato and 12 co-authors, 2011: ISO and Tropical Cyclones. Climate Dyn. (submitted; major revision).

48. COLA Publications > 500 peer-reviewed publications since 1993

49. Today and Tomorrow … • Dirmeyer: Land-Atmosphere Interactions • Straus: I-S-I Prediction and Predictability • Huang: Ocean Prediction and Predictability • Schneider: Decadal Prediction and Predictability • DelSole: Predictability Framework – A Synthesis • Wakefield: COLA Computing • Adams: GrADS • POSTER SESSION • Tomorrow - Future plans

50. COLA SAC Poster Session • Achuthavarier– Impact of horizontal resolution on tropical intraseasonal variability (Project Athena) • Doty– GrADS demo • Lu– Role of ocean dynamical feedback in the climate response to global warming • Manganello,Hodges, Kinter, Cash, Marx, Jung, Achuthavarier, Adams, Altshuler, Huang, Jin, Stan, Towers and Wedi – Tropical cyclone climatology in a 10-km global AGCM: toward weather-resolving climate modeling • Wei– Impact of different land or atmospheric models on climate simulation • Zhu– The tropical Atlantic zonal mode, meridional mode, and their interaction • Arsenault(‘11) – Snow cover fraction data assimilation impacts on modeled energy and moisture budgets • Chen(GRA) – Does SST-forced CAM reproduce the CCSM forced response? • Jang(‘11) – A new look at the influence of tropical waves on the Indian summer monsoon • Jia(‘11) – The limits of detecting forced responses on seasonal and continental scales Robust multi-year predictability on continental scales • Krishnamurthy (Lakshmi, GRA) – Influence of decadal variability of oceans on south Asian monsoon • Lajoie(GRA) – Are some climate models outliers? • Li(‘11) and Huang - SST diurnal variability in the CFS and its influence on low frequency variability • Narapusetty(‘10), Stan, Zhu, Marx, Lu, and Kumar – Role of atmospheric noise in the predictability of PDV