Overview Office of Naval Research 24 May 2012

ONR Briefing – 24 May 2012 COLA Overview Vision and Mission MISSION Basic and applied research and educating the next generation to explore, establish and quantify the predictability and prediction of intra-seasonal to decadal variability in a probabilistic framework and in the context of a changing climate VISION Global society benefits from improved understanding of climate variability and predictability and free and open access to data and research tools Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 2

ONR Briefing – 24 May 2012 COLA Overview Scientific Advisory Committee The SAC reviews and advises on scientific activities at COLA. Current members selected in consultation with the Federal agencies: J. HurrellNCAR2010 – ; chair 2011 – D. LettenmaierU Washington2011 – T. PalmerECMWF2010 – S. SchubertNASA Goddard2002 – L. UccelliniNOAA NCEP2007 – B. WangU Hawaii2005 – Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 3

ONR Briefing – 24 May 2012 COLA Overview Scientific Advisory Committee Former members of the COLA SAC: D. AndersonECMWF L. BengtssonMPI G. BranstatorNCAR D. BurridgeECMWF ; A. BusalacchiU Maryland R. DickinsonU Texas ; chair D. HartmannU Washington ; chair A. LeetmaaGFDL R. MechosoUCLA K. MiyakodaIMGA (Italy) G. NorthTexas A&M Julia PaegleU Utah J. SlingoU Reading (UK) K. TrenberthNCAR ; chair J. M. WallaceU Washington ; chair Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 4

ONR Briefing – 24 May 2012 COLA Overview Uniqueness Critical mass of excellent climate scientists working together Desire, capability to experiment with multiple national models Stable, multi-agency funding and external expert advice Scientific leadership in national/international 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 & advancing research institutions Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 5

ONR Briefing – 24 May 2012 COLA Overview Advantages of COLA Uniqueness New Ideas and Accomplishments Recent Advances COLA in the Nation’s Service Educating the Next Generation of Earth System Modelers Critical Mass Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 6

ONR Briefing – 24 May 2012 COLA Overview Accomplishments over 20 Years COLA is an environment for research that enables scientists to test new ideas and pose a “credible threat” to old ones Established scientific basis for dynamical S-I prediction Established critical role of land surface in climate predictability Established feasibility of reanalysis Advanced the multi-model ensemble Helped quantify limits of climate predictability –Land-atmosphere interactions –Ocean-atmosphere interactions Developed framework for climate predictability and prediction Showed that model fidelity determines model predictability Developed and contributed GrADS to the climate research and prediction community Organized multi-institutional, multi-model modeling projects Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 7

ONR Briefing – 24 May 2012 COLA Overview Recent Advances Established a scientific rationale for regional multi-year prediction Discovered a new mechanism of overlooked land-driven predictability associated with spring-summer growing season transition Determined that ocean analysis is critical to ENSO prediction accuracy and that multi-analysis ensembles are a viable method to overcome uncertainty in ocean states Established a scientific basis for decadal prediction Developed a method that extracts predictability at all time scales Quantified how and why the extratropical response to ENSO changes as the global climate warms Developed a simple conceptual model of interannual variations of Indian monsoon rainfall: linear combination of boundary-forced seasonal a statistical average of intra-seasonal variations Also – see Science Highlights Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 8

ONR Briefing – 24 May 2012 COLA Overview Leading Predictable Component: Internal Multidecadal Pattern (IMP) Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 9

ONR Briefing – 24 May 2012 COLA Overview IMP and the Global Warming Trend Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 10

ONR Briefing – 24 May 2012 COLA Overview Mean Precipitation Change in Europe’s Growing Season: 21 st C minus 20 th C Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 11 “Time-slice” runs of the ECMWF IFS with observed SST for the 20 th century and CMIP3 projections of SST for the 21 st century at two different model resolutions. T159 (128-km) T1279 (16-km)

ONR Briefing – 24 May 2012 COLA Overview Future Change in Extreme Summer Drought Late 20 th C to Late 21 st C Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 12 4X probability of extreme summer drought in Great Plains, Florida, Yucutan, and parts of Eurasia 10 th Percentile Drought: Number of years out of 47 in a simulation of future climate ( ) for which the June-August mean rainfall was less than the 5 th driest year of 47 in a simulation of current climate ( ). Dirmeyer, P. A., B. A. Cash, J. L. Kinter III, T. Jung, L. Marx, C. Stan, P. Towers, N. Wedi, J. M. Adams, E. L. Altshuler, B. Huang, E. K. Jin, and J. Manganello, 2012: Evidence for enhanced land-atmosphere feedback in a warming climate. J. Hydrometeor., (in press).

ONR Briefing – 24 May 2012 COLA Overview COLA in the Nation’s Service Leadership of national and international initiatives Direct impact on operational prediction Honest broker role among major modeling groups Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 13

ONR Briefing – 24 May 2012 COLA Overview Panels and Working Groups Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 14

ONR Briefing – 24 May 2012 COLA Overview Journal Editors: Adv. Atmospheric Science (Huang) Climate Dynamics (Schneider) J. Climate (DelSole) IPCC AR5 (DelSole, Lu, contributing authors) Climate change assessment; also contributions from others (e.g. ZOD and FOD reviewers) Int’l 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 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 Asia- Pacific Climate Center Scientific Advisory Committee (Wang & Shukla, co-chairs) Advise APCC on improving climate prediction in the Asia-Pacific region World Climate Modeling Summit (Shukla, chair; Kinter, member) Very successful meeting in May 2008  multiple BAMS articles in 2010 COLA Leadership – Current Examples Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 15

ONR Briefing – 24 May 2012 COLA Overview Congratulations, Shukla! Shukla Receives 2012 Padma Shri Award from Government of India Smt. Pratibha Devisingh Patil, President of India Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 16

ONR Briefing – 24 May 2012 COLA Overview Direct Impact on Operational Prediction Real-time seasonal forecast ensembles with CCSM3 (in collaboration with U. Miami) –Forecasts provided to NCEP, IRI (tier-2 forecasts provided to IRI, APCC) Experimentation with CFS and CFSv2 –52 papers published COLA was instrumental in introducing CFS to IITM; acknowledged in published papers: –Pokhrel et al., 2012: ENSO, IOD and IMR in CFS coupled simulations. Climate Dyn. –Chaudhari et al., 2012: Model biases in NCEP CFS in IMR. Int. J. Climatology. GrADS is in use as critical tool for operational climate prediction, including new GIS capability added specifically for CPC requirements NMME – National Multi-Model Ensemble –Proposal to CPO FY12 AO: real-time seasonal forecast ensembles (COLA providing CCSM4; in 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 ISI prediction model –COLA and CTB spearheading groundbreaking R2O activity Involving research scientists from outside NCEP and including private sector input Very successful workshop on August 2011 CFSv2 Evaluation Workshop planned for 30 April – 1 May 2012 at ESSIC Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 17

ONR Briefing – 24 May 2012 COLA Overview COLA and George Mason University (GMU) established a new Ph.D. Program in Climate Dynamics (CLIM) in CLIM is now part of the Department of Atmospheric, Oceanic and Earth Sciences (AOES). Current Graduate Students (18) A. Badger (Dirmeyer) G. Bucher (Boybeyi) H. Chen (Schneider) I. Colfescu (Schneider) X. Feng (Lu) A. Garuba (Klinger) A. Hazra (Klinger) Y. Jin (Stan) L. Krishnamurthy (Krishnamurthy) E. Lajoie (DelSole) J. Nattala (Kinter) E. Palipane (Lu) M. Scafonas (Lu) B. Singh (Krishnamurthy) A. Srivastava (Shukla/Huang) E. Stofferahn (Boybeyi) E. Swenson (Straus) X. Yan (DelSole) Climate Dynamics Faculty Faculty (0.5 FTE): Boybeyi, Chiu, DelSole, Dirmeyer, Huang, Jin, Kinter, Klinger, Lu, Schneider, Schopf, Shukla (Director, CLIM; founding chair of AOES), Stan, Straus (chair, AOES) Adjunct:Doty, Krishnamurthy Bold = 2012 graduate Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion Educating the Next Generation of Earth System Modelers 18

ONR Briefing – 24 May 2012 COLA Overview GMU Climate Dynamics PhD Recipients Deepthi AchuthavarierRole of the Indian and Pacific Oceans in Indian Summer Monsoon Variability Research Scientist NASA Goddard Whit Anderson Oceanic Sill - Overflow Systems: Investigation and Simulation with the Poseidon OGCM Research Scientist NOAA GFDL Kristi Arsenault (2011)Impact of Model and Observational Error on Assimilating Snow Cover Fraction Observations Research Scientist NASA Goddard Susan BatesThe Role of the Annual Cycle in the Coupled Ocean-Atmosphere Variability in the Tropical Atlantic Ocean Research Scientist NCAR Robert BurgmanENSO Decadal Variability in a Tropically-Forced Hybrid Coupled ModelAssistant Professor Florida International University Carlos CruzGlobal Ocean Circulation Variability Induced by Southern Ocean WindsResearch Scientist NASA Goddard Meizhu FanLow Frequency North Atlantic SST Variability: Weather Noise Forcing and Coupled Response Research Scientist NOAA NESDIS Xia FengNew Methods For Estimating Seasonal Potential Climate PredictabilityPost-doctoral Research Scientist George Mason University Laura FeudaleExtreme Events in Europe & N. America During : An Observational & Modeling Study Research Scientist ARPA/OSER (Italy) Youkyoung Jang (2011)The Atmospheric Influence of Tropical Diabatic Heating Associated with Developing ENSO on Indian Monsoon Post-doctoral Research Scientist Florida International University Liwei Jia (2011)Robust Multi-year Predictability on Continental ScalesPost-doctoral Research Scientist COLA Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 19

ONR Briefing – 24 May 2012 COLA Overview GMU Climate Dynamics PhD Recipients Daeho JinThe Impact of ENSO on the ExtratropicsPost-doctoral Research Scientist University of Maryland, College Park Jian Li (2011) SST Diurnal Variability in the CFS and its Influence on Low Frequency Variability Research Scientist NOAA NESDIS Julia ManganelloThe Influence of SST Anomalies on Low-Frequency Variability of the North Atlantic Oscillation Research Scientist COLA Bala NarapusettyImpact Of Tropical Instability Waves In The Eastern Equatorial PacificPost-doctoral Research Scientist COLA Xiaohua Pan Impact of Mean Climate on ENSO Simulation and Prediction Post-doctoral Research Scientist University of Maryland, Baltimore County Kathy Pegion Potential Predictability of Tropical Intraseasonal Variability in the NCEP CFS Post-doctoral Research Scientist CIRES, University of Colorado Mary Ellen Verona Observational Analysis and Numerical Simulation of El Niño deceased Yuri VikhliaevDecadal Extra-Tropical Pacific VariabilityPost-doctoral Research Scientist NASA Goddard Li Xu (2011) Snow Cover as a Source of Climate Predictability: Mechanisms of Snow- Atmosphere Coupling Research Scientist COLA Tugrul YilmazImproving Land Data Assimilation Performance With A Water Budget Constraint Post-doctoral Research Scientist U.S. Department of Agriculture Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 20

ONR Briefing – 24 May 2012 COLA Overview CLIM 101: Global Warming - Weather, Climate and Society General Education Natural Science (non-laboratory) undergraduate course that surveys the scientific and societal issues associated with weather and climate variability and change. CLIM 101 enables students to critically examine arguments being discussed by policy makers, corporations, and the public at large. Scientific basics, potential impacts, decision-making under uncertainty, and policy challenges are all discussed. In a course capstone project, students prepare briefings to the Governor of Virginia on the impact of changing climate on various sectors of the Commonwealth’s socio-economic fabric. Instructors: Jim Kinter and Jagadish Shukla Offered since students enrolled in 2011 ~100 students anticipated in 2012 Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 21

ONR Briefing – 24 May 2012 COLA Overview Critical Mass Multi-agency funding – keeping a team of excellence together Testing hypotheses that require large resources – often not possible by individual PIs High productivity Working with –Large, complex models –Large complex data sets Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 22

ONR Briefing – 24 May 2012 COLA Overview “Omnibus” Funding Predictability and Variability of the Present Climate Funding: $2.25M /yr Principal Investigator:J. Shukla Co-PIs:J. Kinter, E. Schneider, D. Straus 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 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. * Thanks to our peers and the agencies 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 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 Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 23

ONR Briefing – 24 May 2012 COLA Overview “Omnibus” Funding COLA is viewed as a major interagency National center of excellence: 2006 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) 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) Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 24

ONR Briefing – 24 May 2012 COLA Overview 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 COLA Multi-Agency Funded Core Team Staff MemberHighest Degree Joined COLA Scientific Staff 1J. Shukla *Sc.D. MIT (1976); Ph.D. BHU (1971)1983 2J. L. Kinter III *Ph.D. Princeton (1984)1984 3E. AltshulerM.S. Maryland (1996)1998 4B. CashPh.D. Penn State (2000)2002 5T. DelSole *Ph.D. Harvard (1993)1997 6P. A. Dirmeyer *Ph.D. Maryland (1992)1993 7B. E. Doty *B.S. N. Illinois (1978)1984 8M. J. FennessyM.S. SUNY-Albany (1980)1984 9Z. GuoPh.D. Ohio State (2002) B. Huang *Ph.D. Maryland (1992) B. Klinger *Ph.D. MIT-WHOI (1992) V. Krishnamurthy *Ph.D. M.I.T. (1985) J. Lu *Ph.D. Dalhousie (2003) L. MarxM.S. MIT (1977) D. A. PaolinoM.S. Illinois (1980) E. K. Schneider *Ph.D. Harvard (1976) C. Stan *Ph.D. Colorado State (2004) D. M. Straus *Ph.D. Cornell (1977)1984 Information Systems Staff 1J. M. AdamsM.S. Washington (1993)2000 2C. SteinmetzPh.D. Purdue (1991)1998 3T. WakefieldB.S. Maryland (2004)2000 Also affiliated with George Mason University Exec. Dir. COLA ( ) Dir. COLA (2005-present) Pres., IGES (1993-present) Dir. COLA ( ) Over 400 person-years experience together Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 25

ONR Briefing – 24 May 2012 COLA Overview Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 26

ONR Briefing – 24 May 2012 COLA Overview COLA Publications > 550 peer-reviewed publications since 1993 Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 27

ONR Briefing – 24 May 2012 COLA Overview Multi-Model Ensemble CCSM4 CESM1 CFSv2 (CFSv1) CM2.x GEOS_CM Experimentation with the Nation’s Climate Models Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 28 POP4 NCAR CAM4 GMAO GEOS5 NCEP GFS2 MOM4 GFDL AM2 MOM4 CLM4 NOAH Catchment CICE4 SIS (mod) SIS CICE LM2 ESMFFMSESMF CPL7

ONR Briefing – 24 May 2012 COLA Overview Big Data at COLA Large data sets: CMIP5: samples from PIControl, Historical, AMIP, Decadal, RCP4.5, and RCP8.5 for 18 models (10 TB; 33K data sets) People from other labs (IRI, CCCma) are asking COLA for the data!! CFSv2: All NCEP seasonal hindcasts; decadal predictions NMME: 7 models, 25 years of hindcasts Athena: ECMWF and JAMSTEC ultra-high resolution models Atmospheric and oceanic reanalyses: NCEP, NARR, MERRA, CFS-R, ERA- 40, ERA-Interim, ESRL-20C, JRA, GSWP, GODAS, SODA, ECDA, ORA-S3, ORA-S4, and COMBINE-NV COLA recently adopted a more cost-effective design to isolate and curate frequently used static data (shared) and promote best practices among data curators, users Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 29

ONR Briefing – 24 May 2012 COLA Overview COLA’s long-term, stable, multi-agency funding enables GrADS to be both nimbly responsive to user needs and dedicated to long-term design and planning. GrADS is an essential tool for COLA research and data management (at COLA and at NCAR) and essential to the climate analysis research and operations community. GrADS has over 86,000 users worldwide –No comparable non-commercial geoscience software –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 ( Open source development model has inspired investment in GrADS by other groups, notably the OpenGrADS and PyGrADS projects at NASA Goddard GrADS Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 30

ONR Briefing – 24 May 2012 COLA Overview GrADS: 86,000 Users Worldwide Downloads from COLA February Present Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 31

ONR Briefing – 24 May 2012 COLA Overview GrADS: On Your Favorite Web Sites Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 32 p/CWlink/daily_ao_index/hgt.shtml Climate Prediction Center Arctic Oscillation Monitor

ONR Briefing – 24 May 2012 COLA Overview Summary NSF, NOAA and NASA can take credit for creating COLA: a unique institution organized to support highly productive, excellent research, graduate education and service to the Nation COLA’s innovative contributions are widely recognized and have significantly influenced our current understanding of climate dynamics COLA provides leadership in climate research and education, initiates national and international research programs, and strongly influences the direction of operational climate prediction COLA is the home of GrADS, a software package that revolutionized the practice of climate analysis when it was introduced 20 years ago and that continues to be the tool of choice for climate data analysis and visualization Graduates of the Climate Dynamics PhD program are taking up climate research positions and helping shape the future of Earth system modeling Introduction Welcome Goals Uniqueness Accomplishments Recent Advances Service Leadership Operations Education Critical Mass Team Scale Productivity Big Models Big Data Conclusion 33