Cyberinfrastructure Enabling Breakthrough Science: Changing the World with the IPCC AR4 Cyberinfrastructure Enabling Breakthrough Science: Changing the World with the IPCC AR4 Lawrence Buja National Center for Atmospheric Research Boulder, Colorado Lawrence Buja National Center for Atmospheric Research Boulder, Colorado CAM T340- Jim Hack

“Science exists to serve human welfare. It’s wonderful to have the opportunity given us by society to do basic research, but in return, we have a very important moral responsibility to apply that research to benefiting humanity.” Walter Orr Roberts Lawrence Buja Contributing Author, IPCC AR4 National Center for Atmospheric Research Boulder, Colorado Lawrence Buja Contributing Author, IPCC AR4 National Center for Atmospheric Research Boulder, Colorado Cyberinfrastructure Enabling Breakthrough Science: Changing the World with the IPCC AR4 Cyberinfrastructure Enabling Breakthrough Science: Changing the World with the IPCC AR4

NCAR Scientific Support facilities 2. Supercomputer/Network Resources 3. Scientific Models - National Science Foundation FFRDC Staff, 500 Scientists/Engineers - 4 Boulder-area campuses 1. Observational Facilities

Climate Modeling Basics The IPCC AR4 Simulations and Report Next Steps Cyberinfrastructure Lessons from the Past

Timeline of Climate Model Development

Chemistry Climate Chemistry Climate BioGeo Chemistry BioGeo Chemistry Software Engineering Climate Variability Polar Climate Polar Climate Land Model Land Model PaleoClimate Ocean Model Ocean Model CCSM Working Groups DevelopmentDevelopment Application Atm Model Atm Model Climate Change CCSM is primarily sponsored by the National Science Foundation and the Department of Energy

The Earth Climate System

TransportationTransportation Forecast Lead Time Warnings & Alert Coordination Watches Forecasts Threats Assessments Guidance Outlook Protection of Life & Property Space Operation RecreationRecreation EcosystemEcosystem State/Local Planning EnvironmentEnvironment Flood Mitigation & Navigation AgricultureAgriculture Reservoir Control EnergyEnergy CommerceCommerce Benefits HydropowerHydropower Fire Weather HealthHealth ForecastUncertaintyForecastUncertainty Minutes Hours Days 1 Week 2 Week Months Seasons Years Initial Conditions Boundary Conditions Seamless Suite of Forecasts Weather Prediction Climate Prediction Climate Change Trenberth

Predictability of weather and climate Trenberth

Years (constant-1870-conditions control run) TS (Globally averaged surface temperature) Figure 1. Schematic of the T control run.

380 b 400 c 420 d 440 e 360 a Years TS (Globally averaged surface temperature) Figure 2. Schematic of the 5-member historical run ensemble A B C DE

360 a 380 b 400 c 420 d 440 e Years (in the b control run) Ensemble (a,b,c,d or e appended to CASE name) TS (Globally averaged surface temperature) Figure 2. Schematic of the 5-member historical run ensemble

CO 2,CH 4 and estimated global temperature (Antarctic ΔT/2 in ice core era) 0 = mean. Source: Hansen, Clim. Change, 68, 269, 2005.

Climate of the last Millennium Caspar Ammann NCAR/CGD

Climate Modeling Basics The IPCC AR4 Simulations and Report Next Steps Cyberinfrastructure Lessons from the Past

WG1: Scientific aspects of the climate system and climate change. Summary for Policy Makers:Feb 2007 Full Report:May 2007 WG2:Vulnerability of socio-economic and natural systems, consequences of climate change & options for adapting to it. Summary for Policy Makers:Apr 2007 Full Report:Jun 2007 WG3: Options for limiting greenhouse gas emissions and otherwise mitigating climate change. Summary For Policy MakersMay 2007 Full Report 2007 IPCC AR4: Intergovermental Panel on Climate Change Fourth Assessment Report Assess the state of knowledge on climate change based on peer reviewed and published scientific and technical literature on regular intervals.

NSF/DOE IPCC Project NCAR, ORNL, NERSC, ES 6-Year Timeline 2002: Climate Model/Data-systems development 2003: Climate Model Control Simulations 2004: IPCC Historical and Future Simulations 2005: Data Postprocessing & Analysis 2006: Scientific Synthesis 2007: Publication Observations of the Earths Climate System Simulations Past, Present Future Climate States

NSF/DOE IPCC Computing Earth Simulator NERSC (DOE) ORNL (DOE) NCAR (NSF)

Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) Simulations NCAR Community Climate System Model (CCSM-3). Open Source 8-member ensembles 11,000 model years simulated “T85” - high resolution ~1 quadrillion operations/simulated year Rate of simulation: 3.5 sim. years/day Data volume for IPCC: ~110 TB Development effort: ~1 person-century

Figures based on Tebaldi et al. 2006: Climatic Change, Going to the extremes; An intercomparison of model-simulated historical and future changes in extreme events,

Figures based on Tebaldi et al. 2006: Climatic Change, Going to the extremes; An intercomparison of model-simulated historical and future changes in extreme events,

Figures based on Tebaldi et al. 2006: Climatic Change, Going to the extremes; An intercomparison of model-simulated historical and future changes in extreme events,

Abrupt Transitions in the Summer Sea Ice Observations Simulated 5-year running mean Gradual forcing results in abrupt Sept ice decrease Extent decreases from 80 to 20% coverage in 10 years. “Abrupt” transition Simulation of Future Climate

NCAR Projections of Degradation of Near-Surface Permafrost

Ammann et al.

Since 1970, rise in:Decrease in: Global surface temperatures NH Snow extent Tropospheric temperatures Arctic sea ice Global SSTs, ocean Ts Cold temperatures Global sea level Glaciers Hurricane intensity Drought & Heat waves Extreme high temperatures (Trenberth) Precipitation in extratropics Rainfall intensity Water vapor IPCC AR4 WG1: Climate Change 2007: The Physical Science Basis. Warming is “unequivocal” “Very likely” the observed 20 th century warming is due to human emissions.

Water shortages affecting hundreds of millions of people will worsen with increased temperatures. Declines in food production in the equatorial regions. 30% of plant and animal species facing extinction under a 1.5 to 2.5° rise. Increased risks of coastal flooding the sea level rise Extreme weather events to become more frequent and intense detecting human health and well-being Adaptation strategies to address unavoidable global warming outcomes. Mitigation strategies to avoid/minimize delay future emissions warming IPCC AR4 WG2: Climate Change 2007: Impacts, Adaptation and Vulnerability. Large-scale changes in food and water availability Changing ecosystems. Escalating flood hazards Increases in extreme weather

Alternative energy. Energy efficiency. Improved Industrial and agricultural practices Geoengineering options are risky and unproven Near term stabilization reduction has large long-term benefits Policies and economic incentives and technology transfer Additional research required to address some gaps in knowledge IPCC AR4 WG3: Climate Change 2007: Mitigation of Climate Change. Quick action can avoid some devastating effects Achievable with existing technologies, balancing economic costs with climate risks

Nature vol March 2007 The Government is coming around

The Energy Sector is Reversing Course

The Public is now engaging at a level never seen before

Strength and clarity of IPCC AR4 message: Greater trust in our models = f(↑ Science, ↑ HPC, ↑ CI ) More realistic processes Higher resolution More ensembles -> less uncertainty Long historical simulations More trust in the observations Satellites/obs showing a consistent picture of global warming worldwide Definitive resolution of problems in the observations Recent Temperature trends in the lower atmosphere (*) Historical sfc temperature reconstruction (Mann's hockey stick) {**} Natural variability: No observed trend in recent solar activity Better agreement between the models and observations Glaciers, nature's independent climate integrators, showing increased edge melting and buildup in the centers consistent with Tebaldi & Meehl’s warmer/wetter world conclusion

Climate Change Epochs Reproduce historical trends Prove Climate Change is occurring SRES Scenarios Investigate Mitigation Approaches Test Adaptation Strategies Look at Regional Details Work with Gov’t/IndustryPublic Before IPCC AR4 After

Climate Modeling Basics The IPCC AR4 Simulations and Report Next Steps Cyberinfrastructure Lessons from the Past

Geo-engineering The intentional large-scale manipulation of the global environment. The term has usually been applied to proposals to manipulate the climate with the primary intention of reducing undesired climatic change caused by human influences. Geoengineering schemes seek to mitigate the effect of fossil-fuel combustion on the climate without abating fossil fuel use; for example, by placing shields in space to reduce the sunlight incident on the Earth.(D. Keith,1999. Geoengineering. Encyclopaedia of Global Change. New York) Humans are already manipulating the environment deliberately, but generally not with the intention of inducing climate change. Phil Rasch, NCAR

Krakatau Santa Maria Pinatubo El Chichòn Agung Global average surface temperature (relative to mean) Major volcanic eruptions °C A1B °C change relative to baseline

Alternate strategies being considered Space mirrors, (Wood, Angel) High Altitude Sulfur injections Seeding stratocumulus clouds to brighten clouds Sequestration of CO2 Iron Fertilization,... Phil Rasch NCAR

Why do this study? –A worry that we are transforming our energy system far too slowly to avoid the risk of catastrophic climate change. –What might be deployable in a planetary emergency to mitigate some of the effects of greenhouse gas warming? –We are not proposing that geo-engineering be done! We are proposing that the implications be explored (see Crutzen study and Cicerone commentary, Climatic Change, 2006) Phil Rasch NCAR

Global Averaged Annual Averaged Surface Temperature change (flawed representation for evap and sedimentation) Phil Rasch

Cautions There are obviously very important Moral, Ethical, Legal issues to be considered here Arguments have been made that we shouldn’t even be considering these types of “solutions”. –Geoengineering will undercut society’s resolve to deal with emissions –Action would change climate in different ways for different nations. People in threatened regions most likely to use intervention Worst case outcomes –unanticipated impacts (e.g. CFC and ozone hole) –forestall global warming only to find we had triggered a new ice age Phil Rasch - NCAR

DOE CCRD Directions Less emphasis on climate change detection and attribution More emphasis on decision support for policy makers provide decision-makers with scientific information on "acceptable" target levels for stabilizing atmospheric CO2 possible adaptation and mitigation strategies for the resulting climates before or after stabilization. Areas 1. Advance climate & Earth systems modeling 2. Improve understanding and model representations of climate and Earth system processes that can affect climate 3. Improve understanding of human impacts and consequences of climate change 4. Improve capabilities and infrastructure for conducting climate change research

Likelihood of warming Stabilizing temperature requires stabilizing atmospheric CO2, Limiting warming to 2°C requires stabilization at ppm CO2 (Meinshausen et al., realclimate.org) A short overshoot of atmospheric CO 2 might be compatible with the 2°C target.

Preparing for IPCC AR5

5 HPC dimensions of Climate Prediction (Tim Palmer, ECMWF) Data assimilation/ initial value forecasts Simulation complexity All require much greater computer resource and more efficient modelling infrastructures Resolution Ensemble size Timescale

Data assimilation/ initial value forecasts Simulation complexity Spatial (x*y*z) Resolution Ensemble size Timescale (Years*timestep) Today Terascale 2015 Exoscale CM: 5 Components Petascale 1.4° 160km 0.2° 22km 1000 (AMR) Km ESM = CM+ 10 Components (Life, $$$) ESM + multiscale GCRM 100yr/ 20min 100??? 1000yr 3min 1000yr ? Code Rewrite

1 st generation Earth System Model Atmosphere Ocean Coupler Sea IceLand C/N Cycle Dyn. Veg. Ecosystem & BGC Gas chem. Prognostic Aerosols Upper Atm. Land Use Ice Sheets

Global General Circulation Continental large-scale flow Regional local Paleoclimate BGC/Carbon Cycle Spin-ups MJO convergence Resolve Hurricanes IPCC AR TF IPCC AR IPCC AR TF CCSM Grand Challenge PF

Climate Modeling Basics The IPCC AR4 Simulations and Report Next Steps Cyberinfrastructure Lessons from the Past

CCSM IPCC Data Flow Tape Archive Device cpl atm ocn ice lnd disk Tape Archive Devices T85 IPCC: 10K 9.6 Gbytes/year Super Front end 0.1 Gbytes 4.5 Gbytes 4.2 Gbytes 0.5 Gbytes 0.3 Gbytes 9.6 GB/yr CDP/ESG Portals QC1 Raw Data NCAR Derived Products QC2 ORNL NERSC Earth Simulator Data Delivered to the World

ESG Data Customers

DOE ESnet4 Configuration Core networks: Gbps in , Gbps in Cleveland Europe (GEANT) Asia-Pacific New York Chicago Washington DC Atlanta CERN (30 Gbps) Seattle Albuquerque Australia San Diego LA Denver South America (AMPATH) South America (AMPATH) Canada (CANARIE) CERN (30 Gbps) Canada (CANARIE) Europe (GEANT) Asia- Pacific Asia Pacific GLORIAD (Russia and China) Boise Houston Jacksonville Tulsa Boston Science Data Network Core IP Core Kansas City Australia Core network fiber path is ~ 14,000 miles / 24,000 km 1625 miles / 2545 km 2700 miles / 4300 km Sunnyvale Production IP core (10Gbps) ◄ SDN core ( Gbps) ◄ MANs (20-60 Gbps) or backbone loops for site access International connections IP core hubs Primary DOE Labs SDN (switch) hubs High speed cross-connects with Ineternet2/Abilene Possible hubs

Lessons Learned 1. Observational data is very similar to model data

2. Obs data very different from model data Time Value Obs data Model data Lessons Learned

3. Don’t let scientists build their data management and distribution systems on their own! Building robust, useful data systems requires close collaboration between the two communities! …but don’t let the CS folks do it alone, either

4. Effective Data Distribution Systems Require Sustained Investment Home Grown Data Systems Earth System Grid / Community Data Portal Initially Cheap $$$ in long term Limited Scale Medium-Large Investment Infrastructure for Small & Large Projects Spans Institutions Lessons Learned

Climate Modeling Basics The IPCC AR4 Simulations and Report Next Steps Cyberinfrastructure Lessons from the Past

Significant changes observed at 4x CO2

Kiehl and Shields (2005)

Global Annual Mean Energy Budget Global Annual Mean Surface Temperature Permian coupled model run for 2700 years to new equilibrium state Forcing of 10X increase in CO 2 and Permian paleogeography  T s > = 8°C CCSM3 T31X3 Kiehl and Shields

Kiehl and Shields (2005) Inefficient mixing in Permian ocean indicative of anoxia, consistent with large extinction event

Wignall(2005) Clear evidence Some evidence No evidence

Summary: We’ve Changed the World. Broad acceptance of the IPCC AR4 is a breakthrough -Impossible without strong, mature cyberinfrastructure -Moving to studying solutions means increasing: –Model complexity/realism/comprehensiveness –Even more data to deliver to more diverse communities The next step will require many new partnerships –Science, Engineering, Technology, and Application –Regional, National & International Partnerships –Development Agencies –Economics/Financial Sectors –Energy Industry We can’t fulfill our science mission without the CI community –“Lets the scientists be scientists” –Huge return on investment: Cheaper, Easier, Better –Allows us to reach huge new communities

Thanks! Any Questions?