The Working Group on Coupled Modeling

1. The Working Group on Coupled Modeling Karl E. Taylor Program for Climate Model Diagnosis and Intercomparison (PCMDI) with credit and thanks to Sandrine Bony Presented to the Fourth WCRP Observation and Assimilation Panel Meeting Hamburg, Germany 29 March 2010

2. Who are the WGCM? • Ex-Officio Members • GokhanDanabasoglu • HelgeDrange • Greg Flato • FilippoGiorgi • John Mitchell • Ronald Stouffer • Karl Taylor Members Sandrine Bony (co-chair) Gerald Meehl (co-chair) Veronica Eyring Marco Giorgetta David Karoly M. Kimoto Corinne Le Quéré Natalie Mahowald Catherine Senior Bin Wang

3. What is the WGCM’s mission? • Foster the development of coupled climate models (and now ESMs) • Coordinate model experiments and inter-comparisons to: • better understand natural climate variability • predict the climate response to natural & anthropogenic perturbations • Promote and facilitate model evaluation and diagnosis of shortcomings A balance among: Predicting – Evaluating - Understanding

4. Major challenges • How can we improve our confidence in climate models? • How can we assess the credibility of model projections ?

5. How can we gauge and gain confidence in GCMsprojections? (1) Bottom-Up approach : evaluate and improve the physical basis of climate models through large-scale and process-scale evaluations High resolution global models (global CRM, MMF) Model projections Single Column Models 3D-Climate Models NWP Models LES models Cloud Resolving Models Analysis & Understanding climate change Field campaigns & instrumented sites Global observational datasets

6. How can we gauge and gain confidence in GCMsprojections? (1) Bottom-Up approach : evaluate and improve the physical basis of climate models through large-scale and process-scale evaluations (2) Top-Down approach : understand the models' results & identify critical processes to provide guidance for specific observational tests/process studies and model improvements High resolution global models (global CRM, MMF) Model projections Single Column Models 3D-Climate Models NWP Models LES models Cloud Resolving Models Analysis & Understanding climate change Field campaigns & instrumented sites Global observational datasets

7. The second approach has traditionally dominated WGCM’s interests, but this is changing. • Current activities focus on understanding why model projections differ • e.g., quantifying the strength of individual feedbacks across models. • Evaluate climate models over a wide range of scales and phenomena • From weather to paleo • From global to regional • From individual physical processes to climate (across all physical and biogeochemical components) • Explore how model formulation and present-day model performance translate to reliability of climate projections • Perhaps the biggest challenge of all.

8. CMIP3 transformed climate science by enabling community-wide participation in the analysis of model output. • 35 Tbytes of model • output stored at • PCMDI • More than 765 TB • downloaded • More than 3,000 • users • More than 550 • publications Jan 2007 (AR4 WGI) Aug 2009 Nov 2004 Courtesy of Bob Drach (PCMDI)

9. What are prospect for CMIP5? • Better understand robust and uncertain aspects of climate change • Enable quantification of strengths of major feedbacks • Include carbon cycle component (ESM’s) • Better meet the needs of the “impacts” community • A more comprehensive set of model output • Provide information needed to assess adaptation and mitigation strategies • Coordinate/integrate across the modeling community: • CMIP includes portions of: C4MIP, PMIP, AMIP, CFMIP, Aqua-planet

10. evaluation & projection hindcasts & forecasts CORE CORE diagnosis “Near-Term” (decadal prediction) “Long-Term” (century & longer) (initialized ocean state) TIER 1 TIER 1 TIER 2 CMIP5: Three Suites of Experiments AMIP CORE “time-slice” TIER 1 TIER 1 • Taylor et al. 2008, • http://cmip-pcmdi.llnl.gov/cmip5 TIER 2 TIER 2 Atmosphere-Only (for computationally demanding and NWP models)

11. Climate Projections Model Evaluation Understanding An important focus is model evaluation and understanding... Example: CMIP5 long-term suite of experiments individual forcing D & A ensembles ensembles: AMIP & 20 C extend RCP8.5 & RCP2.X to 2300 RCP2.X, RCP6 natural-only, GHG-only extend RCP4.5 to 2300 Control, AMIP, & 20 C RCP4.5, RCP8.5 lastmillennium Mid-Holocene & LGM E-driven control & 20 C E-driven RCP8.5 aqua planet (clouds) 1%/yr CO2 (140 yrs) abrupt 4XCO2 (150 yrs) fixed SST with 1x & 4xCO2 ensemble of abrupt 4xCO2 5-yr runs patterned ΔSST (clouds) aerosol forcing ca. 2000 Green subset is for coupled carbon-cycle climate models only uniform ΔSST (clouds) radiation code sees 1xCO2 (1%/yr or 20C+RCP4.5) AC&C4 (chemistry) carbon cycle sees 1XCO2 (1%/yr or 20C+RCP4.5)

12. Detection-Attribution (IDAG) Integrated Assessment Consortium (IAM), connection to WG-III Paleo (PMIP, IGBP-PAGES) Cloud and moist processes (CFMIP-GCSS WGNE) Chemistry, aerosols (SPARC, AC&C, CCMVal, aerocom) Carbon-climate feedbacks (C4MIP, IGBP-AIMES) CMIP now involves many WCRP/IGBP partners Example: CMIP5 long-term suite of experiments + Satellite simulators & process diagnostics (CFMIP-GCSS)

13. WGCM (with others) promotes a variety of community-wide activities to advance climate modeling • Mentioned already: • SPARC & IGBP/IGAC (CCMVal, AeroCom..): chemistry & aerosols • WGCM & IGBP/PAGES (PMIP): paleoclimate • WGCM, GCSS, and WGNE (CFMIP):clouds and cloud feedbacks • WGCM, IGBP/AIMES (C4MIP): carbon cycle • IDAG: detection and attribution studies • WGNE/WGCM (Transpose-AMIP): evaluation of climate models in NWP mode • CLIVAR WGSIP, WGOMD : seasonal to interannual prediction, ocean • TFRCD (CORDEX) : regional • GEWEX GCSS (GPCI) : processes • WGNE/WGCM Metrics panel • CF metadata conventions for archiving and sharing climate data • WGCM endorsed demonstration study (GeoMIP): geo-engineering

14. WGCM’s Challenge to WOAP • Push to make observations as easily available and useable as climate model output generated by CMIP. • Provide easy access and guidance on quality and limitations • Following CMIP3, store observational data in a standard way and make it available through a common portal. • The WGCM has endorsed a NASA/JPL pilot initiative to provide satellite data in a form useful to CMIP5 (Joao Texeira, Duane Waliser, Jerry Potter, S Boland). • A similar NOAA initiative may be launched soon, and this in the work plans ISENES (a European project to provide infrastructure support for climate model research) • These new projects were all partially inspired by CMIP The WGCM would like to see similar efforts undertaken by other providers of satellite and in-situ observations.

15. WGCM’s Challenge to WOAP • Provide encouragement and possibly a framework whereby • the observational and climate modeling community would interact to identify observational data sets useful in model evaluation • The highest priority would be to consider the CMIP output -– variables, temporal/spatial sampling, time-periods. • Establish guidelines for • Metadata that will facilitate search and discovery. • Formats and metadata that will facilitate analysis (as provided by the CF metadata standard) • Develop a strategy for making multiple datasets developed for this purpose accessible in a way that parallels the CMIP model output archive.

17. List of CMIP5 output fields • http://cmip-pcmdi.llnl.gov/cmip5/output_req.html • Domains: • Atmosphere (including aerosols) • Ocean (including carbon cycle variables) • Land surface (including carbon cycle variables) • Cryosphere • Temporal sampling • Annual • Monthly • Daily (including max., min. & mean surf. Air T, precip. humidity, surf. wind, PSL; many more 2-d & 3-d fields for 1950-2005) • 6-hourly • 3-hourly (including from 1950-2005) • ~ half-hour (but not globally)

18. Model output characteristics • Specified template for filenames and directory structure • Additional metadata • modeling_realm • tracking_id • model_id • creation_date • Forcing • initialization_method, • physics_version • Output may be on native grid, rather than longitude-latitude cartesian

19. CMIP5 Decadal Prediction Experiments additional predictions Initialized in ‘01, ’02, ’03 … ’09 hindcasts without volcanoes 100-yr “control” & 1% CO2 10-year hindcast & prediction ensembles: initialized 1960, 1965, …, 2005 alternative initialization strategies prediction with 2010 Pinatubo-like eruption 30-year hindcast and prediction ensembles: initialized 1960, 1980 & 2005 increase ensemble sizes from O(3) to O(10) members atmos. chemistry &/or aerosols &/or regional air quality AMIP

20. AMIP ensemble Future “time-slice” ensemble AMIP (1979-2008) future “time-slice” (2026-2035) AMIP SSTs with 4XCO2 aqua planet (clouds) patterned ΔSST (clouds) uniform ΔSST (clouds) CMIP5 Atmosphere-Only Experiments (targeted for computationally demanding and NWP models)