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Multi-Model Ensembles for Climate Attribution

Multi-Model Ensembles for Climate Attribution. Arun Kumar Climate Prediction Center NCEP/NOAA Acknowledgements: Bhaskar Jha; Marty Hoerling; Ming Ji & OGP; Participants in the Seasonal Diagnostics Consortium. What is Attribution?.

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Multi-Model Ensembles for Climate Attribution

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  1. Multi-Model Ensembles for Climate Attribution Arun Kumar Climate Prediction Center NCEP/NOAA Acknowledgements: Bhaskar Jha; Marty Hoerling; Ming Ji & OGP; Participants in the Seasonal Diagnostics Consortium

  2. What is Attribution? • Attribution: ascribe to or regard as the effect of (a stated cause) (e.g., the delays were attributed to the heavy traffic). • In the context of the observed climate, “attribution” refers to: can we relate observed climate anomalies to external forcing(s)?

  3. Atmospheric anomalies  Sea Surface Temperatures; Soil Moisture; …OR a manifestation of variability internal to the atmosphere • Trends in the ocean-atmosphere system changes in solar forcing; aerosols; CO2…OR are intrinsic to the coupled system

  4. 200-mb Z SST

  5. Why is Attribution Relevant? • Helps in understanding what the dominant forcing mechanisms controlling climate variability are • Provides an understanding of why climate is evolving the way it is • Provides a basis for making long-range predictions and projections

  6. An Approach to Attribution Analysis • Analysis of observed anomalies (atmosphere, ocean, solar,…) • Conceptual separation of system into internal and external (or forced and forcing) components • Formulation of hypothesis (e.g. such and such anomaly may be because of such and such forcing…) • Testing the hypothesis involves analyzing response to the external forcing • Empirical approach • General circulation model approach

  7. OBS Model DJF 1997/98 200-mb Z

  8. OBS Model DJF 2001/02 200-mb Z

  9. Problems with attribution based on a single AGCM • In the AGCM approach, attribution keys on the comparison of the observed anomalies with the AGCMs response to the external forcing • Is the AGCM response to an external forcing correct?

  10. One possible solution is to • Use Multi-model approach as a “confidence (or consensus) builder” in documenting response to an external factor • Once a level of confidence could be placed in the atmospheric response to the external forcing, more definite statements about the causality of observed anomalies can be made

  11. DJF 1997/98

  12. DJF 2001/02

  13. Seasonal Diagnostics Consortium Total # of Simulations : 81

  14. 2004 EOS

  15. 2004 EOS • Add the line plot

  16. MM Climate Attribution • Other Application of MM attribution runs • Documenting atmospheric responses to boundary forcings • Inferring current state of climate • Analyzing successes and failures of operational SI forecasts • Generating different SI prediction scenarios • Model validation (has long been the implicit basis for various MIP activities)

  17. Atmospheric Response to SST Forcing

  18. (2000-2004) - (1961-90)

  19. Atmospheric Climate Model Simulations • Observed SST Forcing • Institution Model Ensemble Size • GFDL AM-2 10 • MPI/IRI ECHAM-4 24 • NASA GMAO 23 • Simulation production for 1950-2004 • Specified monthly varying global SSTs • Climatological GHG/Aerosols • 57 member multi-model ensemble • Experiments are part of Seasonal Climate Diagnostics Consortium http://www.cpc.ncep.noaa.gov/products/people/bjha/

  20. (2000-2004) - (1961-90)

  21. Atmospheric Climate Model Simulations • Idealized Indian Ocean SST Forcing • Institution Model Ensemble Size • GFDL AM-2 10 • NCEP GFS 10 • NCAR CCM3 10 • NCAR CAM3 10 • Transient +0.1°C/yr Indian Ocean warming • Each run is 11-yrs in duration. • Climatological SSTs elsewhere. • Climatological GHG/Aerosols • 40 member multi-model ensemble • http://www.cgd.ucar.edu/cas/asphilli/Results/Ramped-IndianOcean/

  22. Inferring Current State of Climate (consistent with the external forcing)

  23. Response Forced by the Observed SSTs

  24. Coupled Ocn-Atm Climate Model Simulations • Observed GHG/Aerosol Forcing • Simulation production for 1895-2004 • Specified monthly varying GHG/Aerosol 1895-2000 • A1B Scenario 2001-2004 • 18 Different Coupled Models/47 total runs • Experiments are part of the IPCC AR-4 Suite http://www-pcmdi.llnl.gov/ipcc/about_ipcc.php

  25. SSTs Land Temp

  26. (2000-2004) - (1961-90)

  27. Validating Forecasts

  28. NDJFM 2004/2005

  29. Efforts in NOAA • What currently exists: An informal activity maintaining monthly updates in AMIP runs forced by Global SSTs • Within NOAA, need to formalize attribution activity for different time scales [could be centralized or a virtual activity] • Such an activity can also support other model based “hypothesis testing” efforts (e.g., impact of different ocean basins; causality of trends and droughts; …)

  30. OBS June 1998-May 2002 (The Perfect Oceans for Drought) MODEL

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