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Collaborative Climate Research with CCSM: Modeling Earth's Climate Dynamics

Explore the role of the Community Climate System Model (CCSM) in studying Earth's climate, seasonal variability, historical climate trends, and future environmental estimates. Learn about recent accomplishments and the CCSM project structure. Discover how CCSM features support a wide range of simulations and research needs.

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Collaborative Climate Research with CCSM: Modeling Earth's Climate Dynamics

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  1. ESSL / Integrated Climate Change Research: The role of the Community Climate System Model (CCSM) Jim Hurrell Director Climate and Global Dynamics Division NSF Briefing February 27, 2007

  2. Development and Evaluation of Community Climate Models Climate Analysis: Diagnostic, Theoretical and Modeling Studies ESSL / Themes of the CGD Scientific Program

  3. ESSL / The Community Climate System Model: A Framework for Collaborative Research Scientific Objectives • Develop a comprehensive climate model to study the Earth’s climate. • Investigate seasonal and interannual variability in the climate. • Explore the history of Earth’s climate. • Estimate the future of the environment for policy formulation. Recent Accomplishments • Release of a new version (CCSM3) to the climate community. • Studies linking SST fluctuations, droughts, and extratropical variability. • Simulations of last 1000 years, Holocene, Last Glacial Maximum, and Permian. • Creation of largest ensemble of simulations for the IPCC AR4. http://www.ccsm.ucar.edu

  4. Organization of the CCSM Project CCSM Advisory Board CCSM SSC Atmosphere Model Working Group Ocean Model Working Group Land Model Working Group Polar Climate Working Group Chemistry Climate Working Group Paleoclimate Working Group Climate Variability Working Group Biogeo- chemistry Working Group Climate Change Working Group Software Engineering Working Group Management Components Applications

  5. CCSM Features • CCSM is a collection of active and prescribed forcing (“data”) components, providing the user with the unique capability to run all active components or mixtures of active and data components; e.g., • Active ocean can be run with prescribed ice, atmosphere and land runoff forcing • used for evaluation of new ocean science • Runs on multiple platforms (vector and scalar architectures) • IBM-SP, Linux Clusters, Cray X1, Cray XT3, NEC, Earth Simulator, SGI Altix, IBM BlueGene/L • Supports a wide variety of grid resolutions • Coarser resolutions used for paleo simulations, higher resolutions for IPCC type of simulations. T85 x 1

  6. Marine Drinkwater et al. (2003) CCSM: a Tool to Study Modal Variability NAO Impacts on Ecosystems

  7. What Climate Processes Govern NAO Variability? • 200 years of CCM3 without variations • in “external” forcings • Basic structure & time scale arises • from internal nonlinear atmospheric • dynamics EOF1 SLP (Dec-Mar) Simulated (Dec-Mar) Random and Unpredictable Variations

  8. What Climate Processes Govern NAO Variability? Observed Consistent with Observations (Climate Noise Paradigm) Except for the latter half of the 20th Century Observed r (1yr) = 0.4 • 200 years of CCM3 without variations • in “external” forcings EOF1 SLP (Dec-Mar) • Basic structure & time scale arises • from internal nonlinear atmospheric • dynamics Simulated NAO Index Random and Unpredictable Variations r (1yr) = -0.07 r (1yr) = -0.06 A role for external forcing?

  9. The Role of Ocean Forcing Observed Global SST Tropical SST JFM 500 hPa Height Trend (1950-1999) m Hurrell et al. (2004); Hoerling et al. (2004) Falls Rises

  10. The Role of the Cryosphere Sea Ice Forcing Land Snow Cover ICE REMOVED ICE ADDED 500 hPa Z Response Cohen et al. 2007 Deser et al. 2003

  11. Leveraging the NRCM initiative The community has identified the requirement for alternative approaches to: • Improve the understanding of scale interactions and approaches to represent multi-scale processes • Address climate model biases (particularly tropical biases and precipitation biases) • Improve climate predictions at the regional scale (water cycle, extreme events such as hurricanes, and their impacts) • Improve predictions of the regional earth system for research and applications (e.g., water, land, air, carbon management)

  12. WRF WRF CAM CAM CLM CLM ROMS ROMS POP POP POP NRCM: Proposed Modeling Framework

  13. ESSL / OCEAN NRCM Motivation : CCSM3 SST BIAS

  14. P in Control DP Large-Scale Effects of DSST < 0 off North/South America and South Africa

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