U'S' CLIVAR Office

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U.S. CLIVAR Town Hall Meeting Tuesday January 31,
2006 Annual AMS Meeting, Atlanta, GA

• U.S. CLIVAR Office
• www.usclivar.org

International CLIVAR Office www.clivar.org
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U.S. CLIVAR Town Hall Meeting
David M. Legler U.S. CLIVAR Office www.usclivar.
org legler_at_usclivar.org
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CLIVARClimate Variability and Predictability

• What causes the variability of the earth's
  climate on time scales from seasons to centuries
  and can we predict it?
• Can we distinguish natural from anthropogenic
  induced variability?

• CLIVAR Science Plan - 1995
• U.S. CLIVAR Scientific Steering Committee formed
  - Aug 1998
• Intl CLIVAR Commitments Conference - December
  1998
• U.S. CLIVAR draft strategic plans released -
  January 2000
• First Intl CLIVAR Science Conference - June 2004
• CLIVAR will extend through 2013

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2003 US Climate Change Science Program (CCSP)

• CCSP
• Coordinates integrates climate research
• Federation of 13 Departments / Agencies
• 2B/year investment
• CCSP Strategic Plan released 2003
• www.climatescience.gov
• US CLIVAR and CCSP
• Agencies that fund U.S. CLIVAR are accountable to
  CCSP Milestones, Products, and Payoffs.
• U.S. CLIVAR has been will continue to pursue
  these targets
• Agency priorities are linked to CCSP priorities
• CCSP provides a vital framework for CLIVAR
• CCSP is counting on U.S. CLIVAR!

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CCSP Questions and Number of Milestones
Climate Variability and Change
Q4.3 What is the likelihood of abrupt climate
changes such as the collapse of the ocean
thermohaline circulation, inception of a decades
long mega-drought, or rapid melting of the major
ice sheets? 5
Q4.4 How are extreme events, such as droughts,
floods, wildfires, heat waves, and hurricanes,
related to climate variability and change? 5
Q4.5 How can information on climate variability
and change be most efficiently developed,
integrated with non-climatic knowledge, and
communicated in order to best serve societal
needs? 8
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CLIVAR Implementation in the U.S.

• Scientific support from NASA, NOAA, NSF, and DOE
• 50-70 million in competed research relevant to
  U.S. CLIVAR
• Interagency group of program managers addresses
  coordination of support for CLIVAR activities in
  the US

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U.S. CLIVAR Infrastructure

• Federal research programs support a limited
  infrastructure (national and international
  committees, project office)
• Develop short- and long-term strategic plans
  based on community input
• Identify scientific priorities and recommend
  future research activities
• Identify gaps in current research activities
• Coordinate scientific and programmatic activities
  nationally, and develop effective links to other
  national and international

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Examples of U.S. CLIVAR Successes

• There have been many achievements sponsored,
  initiated, and/or coordinated by US CLIVAR and
  its sponsoring agencies
• Observations hydrography program
• Elucidating processes that should be in climate
  models EPIC (NSFNOAA)
• Targeted improvement of IPCC-class modelsCPTs
• Model assessment for IPCCCMEP
• Advances in assessing predictability, improving
  predictions, or attribution

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Town Hall Meeting

• Purpose
• Convey emerging scientific foci as developed by
  reorganized US CLIVAR committees
• Solicit input on future scientific plans and
  activities (e.g. where are the gaps? Are emerging
  new foci and objectives the best choices? What
  community activities could address U.S. CLIVAR
  goals?)
• Highlight opportunities for wider participation
  in U.S. CLIVAR

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• The initial science objectives of U.S. CLIVAR
• (Implementing US CLIVAR, Dec 2000)
• Identify and understand major patterns of climate
  variability, on S-I and longer time scales and
  evaluate their predictability
• Expand our capacity to predict S-I climate
  variability and search for ways to predict
  decadal climate variability
• Document past rapid climate changes and their
  mechanisms and evaluate the potential for them
  in the future
• Evaluate and enhance the quality of models used
  to project climate change
• Detect and describe any global climate changes

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• Building US CLIVAR - emphasizing natural
  variability
• (Implementing US CLIVAR, Dec 2000)
• Observations/observing systems to document
  climate variability and provide initial
  conditions
• Modeling, improvements, exploration of
  mechanisms, focusing of observations
• Empirical studies of the climate record to define
  patterns and test hypotheses
• Regional and process studies to quantify key
  processes needing to be represented well in
  climate models

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Present ARGO profiling float array
SI and decadal planning in the community, but the
challenge of basin scale observations was common,
and initial emphasis was placed on implementation
that would yield a dynamically consistent, global
data set.
Mantua
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U.S. CLIVAR Organization
CLIVAR Inter-Agency Group
CLIVAR SSC
US CLIVAR Office
Atlantic Region
Pan-American Region
Implementation Panels
Pacific Region
International CLIVAR Project Office
Asian-Australian Monsoon
Seasonal to Interannual Modeling and Prediction
Southern Ocean Sector
Working Groups
CLIVAR/PAGES
Linked to corresponding Intl CLIVAR body
CLIVAR/SEARCH
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Scientific Progress in Climate Variability
Prediction
Observe/Analyze
Hypothesize
Predictability?
Operational Predictions
Decision Support and Climate Services
Conceptualize
Model/Simulate
Experimental Predictions
Intraseasonal Variability
Design/improve observing system
Response / Outcome Droughts Floods Climate
changes Heat waves Cold spells Storms Extreme
events Abrupt changes
Forecast systems/techniques
Feedbacks
Monsoons/TBO
Assimilation systems
ENSO
Analysis tools/Diagnostics
Tropical Atlantic Variability
FORCINGS
Develop new products
Continuum of Climate Research Activities
AO/NAO
Assess model fidelity
Decadal/Interdecadal Variability
Improve model parameterization
Southern Annular Mode
Process studies
Analyze existing observational and model data sets
Feedbacks
Ocean Thermohaline Circulation
Centennial-scale variability
Mine historical observations
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• The Vision of US CLIVAR
• Overarching improve the ability to predict
  responses of the climate system

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• The Vision of US CLIVAR
• Overarching improve the ability to predict
  responses of the climate system, and see that
  improvement in place at major applications
  centers (NCEP, IRI, NCAR-CCM, GFDL,.)

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• The Vision of US CLIVAR
• Overarching improve the ability to predict
  responses of the climate system, and see that
  improvement in place at major applications
  centers (NCEP, IRI, NCAR-CCM, GFDL,.)
• The challenge US CLIVAR must facilitate this.

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• The Vision of US CLIVAR
• Overarching improve the ability to predict
  responses of the climate system, and see that
  improvement in place at major applications
  centers (NCEP, IRI, NCAR-CCM, GFDL,.)
• The challenge US CLIVAR must facilitate this.
• Thus, research priorities should be informed (not
  necessarily determined, but informed) by needs of
  the applications community.

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• The Vision of US CLIVAR
• Overarching improve the ability to predict
  responses of the climate system, and see that
  improvement in place at major applications
  centers (NCEP, IRI, NCAR-CCM, GFDL,.)
• The challenge US CLIVAR must facilitate this.
• Thus, research priorities should be informed (not
  necessarily determined, but informed) by needs of
  the applications community. So, the needs of
  centers involved in climate risk management (CRM)
  identify or inform CLIVAR about the needs of
  prediction research the challenges to better
  predictions identify the needs for model
  improvement/phenomena investigation needs of
  model improvement informs needs for process
  studies needs for process studies/phenomena
  investigation informs needs from observational
  network.

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• The Vision of US CLIVAR
• This is going beyond the notion that process
  research and the investigation of phenomena feeds
  improved predictability and advances in
  predictions
• This had led to a new structure to US CLIVAR,
  where the building blocks are neither basin
  panels nor model development groups focused on a
  specific time scale. The new groups recognize
  the global nature of climate research and
  facilitate the incorporation of improvements to
  prediction in applications.

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U.S. CLIVAR Scientific Coordination Advisory
Committees
US CLIVAR Committee
Committee
Predictability, Predictions Applications
Interface (PPAI)
Panels
Phenomenology, observations, synthesis (POS)
Process studies model improvement (PSMI)
Working Groups
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U.S. CLIVAR Scientific Coordination Advisory
Committees
Predictability, Predictions Applications
Interface (PPAI)
Panels
Phenomenology, observations, synthesis (POS)
Process studies model improvement (PSMI)
Working Groups
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U.S. CLIVAR Scientific Coordination Advisory
Committees
Predictability, Predictions Applications
Interface (PPAI)
Panels
Phenomenology, observations, synthesis (POS)
Process studies model improvement (PSMI)
Working Groups
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U.S. CLIVAR Scientific Coordination Advisory
Committees
Predictability, Predictions Applications
Interface (PPAI)
Panels
Phenomenology, observations, synthesis (POS)
Process studies model improvement (PSMI)
Working Groups
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U.S. CLIVAR Scientific Coordination Advisory
Committees
Predictability, Predictions Applications
Interface (PPAI)
Panels
Phenomenology, observations, synthesis (POS)
Process studies model improvement (PSMI)
Working Groups
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Possible foci -ENSO - links to higher and lower
frequencies -Reduction in model biases in eastern
basins -Improved prediction of drought -Mechanisms
of extratropical decadal modes -
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The CLIVAR Vision...
An important legacy of CLIVAR will be an improved
climate observing system,as well as a more
comprehensive and useful climate record
CLIVAR will contribute the fundamental
underpinnings of critical physical processes that
lead to reducing uncertainties in coupled climate
models used for prediction
CLIVAR will contribute to the development of
robust dynamical frameworks for understanding and
predicting climate changes and interface with
applications centers
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U.S. CLIVAR Prediction, Predictability
Applications Interface Panel (PPAI)

• Tom Delworth (GFDL)
• Lisa Goddard, co-chair (IRI)
• Alex Hall, co-chair (UCLA)
• Wayne Higgins (NOAA/NCEP)
• Marty Hoerling, ex-officio (NOAA/ESRL)
• Ben Kirtman (COLA)
• Randy Koster (NASA-GSFC)
• Nate Mantua (U. Washington)
• Simon Mason (IRI)
• Gerry Meehl (NCAR)
• Kelly Redmond (DRI)
• Gavin Schmidt (NASA/GISS)

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U.S. CLIVAR Prediction, Predictability
Applications Interface Panel (PPAI)

• Our mission is to foster improved practices in
  the provision, validation, and uses of climate
  information and forecasts through coordinated
  participation within U.S. and international
  climate science and applications communities.

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Goal 1 Further fundamental understanding of
climate predictability at seasonal to centennial
time scales
Potential gains in seasonal forecast skill that
might be realized by transitioning research
forecasts methodologies into operational
forecasts. Also shown is potential
predictability, approximating an upper limit to
skill.
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Goal 2 Improve provision of climate forecast
information, particularly with respect to
drought and other extreme events
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Goal 3 Foster research and development of
prediction systems for climate impacts on
ecosystems
Link between low-frequency climate variability
and ecosystems
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Goal 4 Enable use of CLIVAR science for
improved decision support

• Transforming knowledge into solutions
• The needs of decision makers and risk managers
  inform the research priorities of the climate
  prediction community

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U.S. CLIVAR Phenomena, Observations and
Synthesis Panel (POS)

• John Marshall MIT (Co-Chair)
• Sumant Nigam U of Maryland (Co-Chair)
• Michael Alexander NOAA/CDC
• James Carton U of Maryland
• David Easterling NOAA/NCDC
• Sarah Gille Scripps, UCSD
• Dave Gutzler U of New Mexico
• Gabriel Lau NOAA/GFDL, Princeton Univ
• Dimitris Menemenlis NASA/JPL
• Walter Robinson U of Illinois
• Siegfried Schubert NASA/GSFC
• Eli Tziperman Harvard University

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U.S. CLIVAR Phenomena, Observations and
Synthesis Panel (POS)

• Our mission is to improve the understanding of
  climate variations in the past, present, and
  future develop syntheses of critical climate
  parameters and sustain/improve the global
  climate observational system.

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Goal 1 Advance understanding of thestructure
and mechanisms of climate variability in the
past, present and future

• Priorities
• Climate change detection, attribution
• Regional hydroclimate variability monsoons,
  droughts, western water
• Role of tropical oceans in global climate
• Climate variability modes (ENSO, PDV, TAV, NAO,
  Annular modes, MJO) and their interaction in 20th
  century observations and simulations

The Effect of Indian Ocean Warming on the NAO
JFM 500 hPa (m)
Observed Trend
Simulated Response
JFM Indian Ocean SST (C)
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Goal 1 Advance understanding of thestructure
and mechanisms of climate variability in the
past, present and future

• Activities in the next 1-3 years (FY2006-08)
• ?Arctic climate change analysis International
  Polar Year activity in collaboration with SEARCH
  CLiC
• ?Origin of North American Droughts Role of
  ocean-atmosphere .vs. land-atmosphere processes
  CLIVAR-GEWEX coordinated research
• ?Role of Indian Ocean in global climate
  Analysis sampling strategies
• ?Pacific Decadal Variability

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Goal 2 Sustain and improve the Global Climate
Observing System and the US Climate Reference
Network

• Next 1-3 years (FY 2006-08 beyond)
• Maintain continuity of satellite altimetry and
  climate data records
• Achieve current deployment objectives
• Satellites - Aquarius (salinity), WSOA (wide
  swath altimeter), GPM (Global Precipitation
  Mission)
• Expand the US Climate Reference Network
• Argo array, flux buoys, hydrography
• Plan future observing systems
• Remote sensing of Sea ice parameters thickness
• Observing System Simulation Experiments
• Sensitivity analysis, influential regions and
  variables

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3 Synthesis
Goal 3 Improve and develop consistent
ocean-atmosphere-land data sets for climate
studies Climate Data Assimilation

• Intellectual synthesis Advance understanding of
  variability using a hierarchy of models and
  diagnostic studies
• Next 1-3 years (FY06-08)
• Reanalysis for climate studies (ocean,
  atmosphere, land, coupled).
• Large-scale synthesis of ocean and
  ocean/atmosphere observations (data only)
• Development of Coupled Data Assimilation
  techniques

Sea level trend 1993-2000 (ECCO)
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Proposed Working Groups

• Salinity (active)
• Droughts (with PPAI)
• Climate Data Assimilation
• Subseasonal variability/predictability (with
  PPAI)

U.S. CLIVAR Salinity Workshop8-10 May 2006Woods
Hole Oceanographic InstitutionRedfield
Auditorium
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US CLIVAR Process Study Model Improvement
Panel (PSMIP)
Meghan Cronin, co-chair (NOAA - PMEL) Raffaele
Ferrari (MIT) Jim Hack (NCAR) Dick
Johnson (Colorado State University) Terry Joyce
(WHOI) Bill Large (NCAR) Sonya Legg
(Princeton) Hua Lu Pan (NOAA - NCEP) Paul
Schopf, co-chair (GMU/COLA) Ken Sperber
(Lawrence Livermore) S.-P. Xie (University
of Hawaii)
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U.S. CLIVAR Process Study Model Improvement
Panel (PSMIP)
Mission Research on underlying uncertainties in
models and physics to improve the delivery of
climate science.
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US CLIVAR Process Study Model Improvement Panel
(PSMIP) Goal 1 Reduce major systematic errors
and biases in GCMs used for climate variability
prediction and climate change projection
Annual mean precipitation from NCAR CCSM3
relative to GPCP (observed precip). Courtesy J.
Hack.
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Processes related to biases in the stratus
deck region of the eastern basin.
Observed
Observed
ABL underestimated cloud too thin in GCMs. What
is relationship to drizzle aerosols? From
Bretherton et al (2004)
SST anomalies from the new GFDL coupled model for
IPCC (CM2). From Wittenberg, et al (In Press)
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Processes related to the biases in the
equatorial cold tongue region.
Forced OGCMs (GFDL OM3 NCAR POP) have
reasonable ENSO SST but significant problems with
subsurface ENSO temperature anomalies. Suggests
incorrect mixing upwelling. Courtesy
Wittenberg, Kessler.
SST anomalies from the new GFDL coupled model for
IPCC (CM2). From Wittenberg et al (In Press).
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US CLIVAR Process Studies
Goal 2 Use process studies to quantify
climatically important processes
Ocean-Land-Atm Studies
Ocean Dynamics, Mixing Studies
Atmospheric Dynamics, Clouds, Radiation
Enhanced Monitoring
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US CLIVAR Process Studies
Goal 3 Ensure that process studies lead to
climate model improvements
Ocean-Land-Atm Studies
Ocean Dynamics, Mixing Studies
Atmospheric Dynamics, Clouds, Radiation
Enhanced Monitoring
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Climate Process Modeling Teams (CPTs)
Traditional Approach
US CLIVAR Approach
Process model development
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Climate Process Modeling Teams are

• Teams of theoreticians, observational scientists,
  diagnostic scientists, process modelers, coupled
  model, data assimilation systems developers,
  organized to characterize address systematic
  critical issues that limit progress in improving
  climate models.

• NSF and NOAA AO (2003 2.5M per year) to
  address critical issues in comprehensive climate
  models
• Three pilot CPTs
• Low-latitude cloud feedbacks on climate
  sensitivity (Bretherton et al.)
  http//www.atmos.washington.edu/breth/CPT-clouds.
  html
• Ocean mixing in overflow regions (Legg et al.)
  http//cpt-gce.org/
• Mesoscale eddy interaction with upper-ocean
  mixing - EMILIE (Ferrari et al.)
  http//cpt-emilie.org/

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Goal 3 Ensure that process studies lead to
climate model improvements

• US CLIVAR Process Study Model Improvement
  Panels Proposed Best Practice for Process
  Studies
• Entrain Modelers during the planning stage
• Encourage broad use of the data
• Create synthesis data sets that can be used as
  benchmarks for assessing and validating models

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Goal 4 Facilitate collaborations with other
national and international partnersUS CLIVAR
PSMI Panel provides vital review feedback for
process studies
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How to Become Involved

• US CLIVAR activities range in size (individual
  projects, working groups, process studies,
  climate process teams, )
• Practice Best Practices
• PSMIP provides vital review feedback for large
  process studies
• Contact panels

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CCSP CLIMATE VARIABILITY AND CHANGE BUDGETS x 106

• NSF Basic climate research 80 (10)
• NOAA Prediction/projections 77 (5)
• NASA Satellite data products 60 (variable)
• DOE Climate change/Energy policy 55 (variable)
• USGS Water resources 10 ----------
• TOTAL 282 (15variable)

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U.S. CLIVAR
US CLIVAR Committee
U.S. CLIVAR Office
Committee
Predictability, Predictions Applications
Interface (PPAI)
Panels
Process studies model improvement (PSMI)
Phenomenology, observations, synthesis (POS)
Intl CLIVAR panels
Salinity WG
Working Groups
WG 2
WG 3
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U.S. CLIVAR Town Hall Meeting Providing Input
to US CLIVAR

• Weve presented draft U.S. CLIVAR scientific
  plans and activities
• We seek community feedback/input
• Where are the gaps?
• What are the compelling and new scientific foci
  that we should be addressing?
• What are the ongoing relevant programs and
  activities that contribute to CLIVAR goals?
• Suggestions for new activities?
• General questions?
• Send comments and questions on the following
  topics to
• usclivar-comments_at_usclivar.org

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