1 CLIVAR SSC Meeting, Jan 9, 2012 Office of Science
Office of Science Office of Biological and Environmental Research
Renu JosephJanuary 9, 2012
CLIVAR SSC Meeting
DOE’s Climate Modeling Efforts
PMs: Dorothy Koch, Renu Joseph, Bob Vallario
Climate Modeling Programs
Climate and Environmental Sciences Division
Biological and Environmental Sciences
2 CLIVAR SSC Meeting, Jan 9, 2012 Office of Science
Department of EnergyOffice of Science
William BrinkmanDirector
Patricia DehmerDeputy Director
HighEnergyPhysics
Biological and Environmental
Research (BER)
Sharlene Weatherwax,
Associate Director
BasicEnergy
Sciences
FusionEnergy
Sciences
AdvancedScientific
ComputingResearch
NuclearPhysics
Biological Systems ScienceSharlene
Weatherwax,Director
Climate and Environmental
SciencesGary Geernaert,
Director
3 CLIVAR SSC Meeting, Jan 9, 2012 Office of Science
Climate and Environmental Sciences DivisionClimate and Environmental
Sciences
Atmospheric Science
Atmospheric System Research
(Ashley Williamson)
Atmospheric Radiation
Measurement Climate Research
Facility(Wanda Ferrell)
Climate and Earth System
Modeling
Regional & Global Climate
Modeling(Renu Joseph)
Earth System Modeling
(Dorothy Koch)
Integrated Assessment(Bob Vallario)
Environmental System Science
Terrestrial Ecosystem
Science(Mike
Kuperberg, Dan Stover)
Terrestrial Carbon
Sequestration Research
Subsurface Biogeochemical
Research
Environmental Molecular Sciences
Laboratory
4 CLIVAR SSC Meeting, Jan 9, 2012 Office of Science
Why DOE?The Energy-Climate Nexus
DOE seeks to:
• Understand the effects of GHG emissions on Earth’s climate and the biosphere
• Provide world-leading capabilities in climate modeling and process research on clouds and aerosols, and the carbon cycle
• Provide unique, world-leading capabilities in cloud and aerosol observations and large scale ecological experiments
• Build foundational science to support effective energy and environmental decision making
Greenhouse gases are emitted during energy production… and climate change will impact energy production
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Key Points to keep in mind!
• The Integrated approach to answer key science questions:– Two examples (NGEE, GOAMAZON)
• Most DOE climate modeling research is around the development and analysis of the CESM
• The Lab-University funding distribution is 50-50.
• All our funding is peer reviewed– Through solicitations
– Science Focus Areas
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Climate Modeling as CESD integrator
• Develop Community Atmosphere Model (CAM) clouds, aerosols and dynamics
• Apply ARM and other cloud/atmosphere/aerosol datasets to improve and test model
• Use model to discern most sensitive and uncertain elements of CAM to inform ASR research and ARM deployments
Links between Atmospheric Sciences Research/Atmospheric Radiation Measurement (ASR/ARM) and Climate Modeling
7 CLIVAR SSC Meeting, Jan 9, 2012 Office of Science
Climate Modeling as CESD integrator
• Develop Carbon cycle in Community Land Model (CLM)
• Apply Ameriflux and other TES datasets to improve and test CLM
• Use model to discern most sensitive or uncertain elements of CLM to inform TES research
Links between Terrestrial Ecosystem Sciences (TES) and Climate Modeling
8 CLIVAR SSC Meeting, Jan 9, 2012 Office of Science
Next Generation Ecosystem Experiment
• Goal– Develop Earth System Model simulation of Arctic Ecosystem
evolution under climate change by developing a process-rich ecosystem model, from bedrock to the top of the vegetative canopy, at the scale of an Earth System Model (ESM) grid cell (e.g. 30x30 km grid size)
• Approach– Collaborative effort among DOE National Laboratories and
universities, with opportunity for leveraging through external collaboration with other agencies
– Interdisciplinary, multi-scale approach to advance predictive understanding through coupled modeling and process research
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Green Ocean Amazon (GOAmazon) 2014• Study interactions of the tropical rain forest and cloud systems: role
of biogenic aerosols, surface fluxes as well as impact of pollution on cloud system developments
• Deployment of the ARM Mobile Facility and G1 aircraft to Manaus, Brazil in 2014
• All CESD programs are collaborating to leverage this investment and improve the representation of these processes in Earth system models
• International coordination (e.g., Brazilian scientists and research institutions). Opportunities for U.S. scientists and other Federal agencies to collaborate.
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Overarching Goal for Climate ModelingTo advance fundamental understanding of climate variability and climate change by developing and analyzing Climate and Earth System Models at temporal scales ranging from decades to centuries and spatial scales ranging from global to regional to understand climate and energy impacts
Regional
GlobalMultiscale
Development Analysis
Earth System ModelingRegional and Global Climate Modeling
Integrated Assessment Research Program
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Regional and Global Climate Modeling
Regional• High Resolution Modeling to obtain reliable climate
predictions/projections to enable us to understand climate and energy impacts and interactions at regional scales
• Focus on regions vital for assessing future climate– (e.g., Arctic, Tropics)
Regional and Global• Model Analyses to improve our understanding of the climate
system including– Distinction between natural variability and anthropogenic climate
change
– Extreme event representation and attribution
– Understanding the feedbacks and interactions between processes within the climate system
• Quantification of the uncertainties and feedbacks in the climate system to understand how reliable the projections/predictions are
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Program for Climate Model Diagnosis and Intercomparison: PCMDI
PCMDI
Scientific leadership of “community modeling” activities (e.g., AMIP, CMIP)
Development and application of “broad brush” climate model performance metrics
Climate change detection and attribution research
Diagnosis of global climate models (variability, hydrological cycle, land surface processes, ocean heat content and circulation)
CAPT project (Cloud Associated Project Testbed)
Studies of aerosol, cloud, precipitation, and radiation processes
Leadership of software development and infrastructure support for “community modeling” activities
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UCAR-DOE Cooperative Agreement
Research Areas1. Modeling Future Climate Change with Various Climate Forcings2. Evaluation of and Improvements to Components of Climate System
Models3. Physical Parameterization Development and Process Studies Using a
Hierarchy of Modeling Frameworks4. Climate Dynamics Applied to Climate Change
ImpactThis provided the largest set of simulations to the CMIP3 multi-model dataset that was assessed for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4).
They are currently participating in a set of coordinated experiments to address short term decadal climate change and new long term mitigation/adaptation scenarios for the IPCC Fifth Assessment Report
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Earth System Modeling
• Develop model physics of system components (CESM)
• Couple individual components
• Test and improve components using observations (“Test-bed”)
• SciDAC partnership with Advanced Scientific Computing (ASCR)
• Optimize computationally intensive processes and codes
• Evaluate process feedbacks and potential for abrupt climate change
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Earth System Modeling Projects
• FAST physics cloud model testbed: test and develop cloud parameterizations using ARM measurements
• Abrupt climate change: 1. Stability of WAIS (sheet-ocean interface), 2. Drought potential over US (Land hydrology, dust), 3. Arctic methane clathrate and permafrost release (land, ocean, atmosphere biogeochemistry)
• Arctic polar: pollution transport to Arctic, Arctic cloud, cryosphere development and coupling
• High Resolution: Challenges and benefits of running model at very high resolution (0.25x0.1 atmospherexocean), hydrologic extremes, eddies
• Integrated Earth System Model: Tighter coupling between human activity (e.g. water, land, energy use) and climate (effects on energy, biosphere)
• “Visualization” development of tools for analysis and visualization of large and diverse (spatio-temporal) model and observational datasets
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Climate Science for a Sustainable Energy Future: CSSEF
3 Science Themes:• Numerics• Testbeds• Uncertainty
Quantification3 Components:• Atmosphere• Land• Ocean and Sea-Ice
8 Labs:ANLBNLLANLLBNLLLNLORNLPNNLSNL
3 Research Directions:• Hydrologic simulation improvement• Variable-resolution numerical
methods• Carbon cycle uncertainty reduction
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Climate, Ocean and Sea Ice Modeling : COSIM
Develop advanced ocean and ice models for evaluating the role of ocean and ice in high-latitude climate change and projecting impacts of high-latitude change on regions throughout the globe.
• Science drivers– Ice sheets and sea level rise– Stability of ocean circulation– Arctic biogeochemistry and rapid ice retreat
• Model development– POP/HYPOP/MPAS-Ocean– CICE– Glimmer-CISM– CCSM– High resolution and multi-resolution climate
eddy resolving models
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Priorities for CLIVAR Consideration
• Looking at the Earth System as an integrated whole, while identifying science gaps– Examples the hydrologic cycle (atmosphere, surface, below
ground)
– Sea Level rise (ice-sheets, oceans, coasts)
– High latitude system (carbon cycle, hydrology, biogeochemical processes, clouds)
• Inter-agency Collaboration on solicitations that Complement Strengths– Activities that enhance collaboration between Ocean Modeling
and observations
What changing priorities in your agency require US CLIVAR to consider expanding or moving in new directions?
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Priorities for CLIVAR Consideration
• Address Challenges due to Increasing Volume of Model Data, Next Generation Data Analysis, Validation and Verification Needs– Increasing Data Challenges
• IPCC AR4 ~35 TB; AR5 > 3 PB (100 fold increase)By 2030, the combined model and observational records are projected to increase by another factor of 100
– Easy analysis and diagnostics capabilities• Dedicated infrastructure to support increasing data volume and
focused investments in “user-friendly” software tools to work with the data
– Validation and Verification of models• Agile frameworks to synthesize observations (e.g. from satellites, field
campaigns, and surface networks) with model output, either embedded in the model code or in post-processing frameworks
– Data Provenance Issues
What changing priorities in your agency require US CLIVAR to consider expanding or moving in new directions?