DOE (Renu Joseph)

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Transcript DOE (Renu Joseph)

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
Renu Joseph
January 9, 2012
Office of Science
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CLIVAR SSC Meeting, Jan 9, 2012
Office of Biological
and Environmental Research
Office of Science
Department of Energy
Office of Science
William Brinkman
Director
Patricia Dehmer
Deputy Director
Basic
Energy
Sciences
Biological and
Environmental
Research
(BER)
Sharlene
Weatherwax,
Associate Director
Biological
Systems
Science
Sharlene
Weatherwax,
Director
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High
Energy
Physics
Nuclear
Physics
Fusion
Energy
Sciences
Advanced
Scientific
Computing
Research
Climate and
Environmental
Sciences
Gary Geernaert,
Director
CLIVAR SSC Meeting, Jan 9, 2012
Office of Science
Climate and Environmental Sciences Division
Climate and Environmental
Sciences
Atmospheric
Science
Atmospheric System
Research
(Ashley Williamson)
Atmospheric
Radiation
Measurement
Climate Research
Facility
(Wanda Ferrell)
Climate and
Earth System
Modeling
Environmental
System Science
Regional &
Global Climate
Modeling
(Renu Joseph)
Terrestrial
Ecosystem
Science
(Mike Kuperberg,
Dan Stover)
Earth System
Modeling
(Dorothy Koch)
Terrestrial
Carbon
Sequestration
Research
Integrated
Assessment
(Bob Vallario)
Subsurface
Biogeochemical
Research
Environmental
Molecular
Sciences
Laboratory
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CLIVAR SSC Meeting, Jan 9, 2012
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Why DOE?
The Energy-Climate Nexus
Greenhouse gases are emitted during energy production…
and climate change will impact energy production
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
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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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CLIVAR SSC Meeting, Jan 9, 2012
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Climate Modeling as CESD integrator
Links between Atmospheric Sciences Research/Atmospheric Radiation
Measurement (ASR/ARM) and Climate Modeling
• 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
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CLIVAR SSC Meeting, Jan 9, 2012
Office of Science
Climate Modeling as CESD integrator
Links between Terrestrial Ecosystem Sciences (TES) and Climate Modeling
• 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
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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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CLIVAR SSC Meeting, Jan 9, 2012
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Overarching Goal for Climate Modeling
To 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
Development
Analysis
Global
Multiscale
Regional
Earth System Modeling
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Regional and Global
Climate Modeling
CLIVAR SSC Meeting, Jan 9, 2012
Integrated Assessment
Research Program
Office of Science
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
Scientific leadership of “community
modeling” activities (e.g., AMIP, CMIP)
Development and application
of “broad brush” climate model
performance metrics
Leadership of software development and
infrastructure support for “community
modeling” activities
PCMDI
Climate change detection and
attribution research
Studies of aerosol, cloud,
precipitation, and radiation
processes
CAPT
project
(Cloud
Associated Project Testbed)
Diagnosis of global climate models
(variability, hydrological cycle, land
surface processes, ocean heat
content and circulation)
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CLIVAR SSC Meeting, Jan 9, 2012
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UCAR-DOE Cooperative Agreement
1.
2.
3.
4.
Research Areas
Modeling Future Climate Change with Various Climate Forcings
Evaluation of and Improvements to Components of Climate System
Models
Physical Parameterization Development and Process Studies Using a
Hierarchy of Modeling Frameworks
Climate Dynamics Applied to Climate Change
Impact
This 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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CLIVAR SSC Meeting, Jan 9, 2012
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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 Quantification
3 Components:
•Atmosphere
•Land
•Ocean and Sea-Ice
8 Labs:
ANL
BNL
LANL
LBNL
LLNL
ORNL
PNNL
SNL
3 Research Directions:
•Hydrologic simulation improvement
•Variable-resolution numerical methods
•Carbon cycle uncertainty reduction
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CLIVAR SSC Meeting, Jan 9, 2012
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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 highlatitude 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
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–
–
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POP/HYPOP/MPAS-Ocean
CICE
Glimmer-CISM
CCSM
High resolution and multi-resolution climate
eddy resolving models
CLIVAR SSC Meeting, Jan 9, 2012
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Priorities for CLIVAR Consideration
What changing priorities in your agency require US CLIVAR to consider
expanding or moving in new directions?
• 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
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CLIVAR SSC Meeting, Jan 9, 2012
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Priorities for CLIVAR Consideration
What changing priorities in your agency require US CLIVAR to consider
expanding or moving in new directions?
• 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
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CLIVAR SSC Meeting, Jan 9, 2012
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