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

Atmospheric anomalies  Sea Surface Temperatures; Soil Moisture; …OR a manifestation of variability internal to the atmosphere 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; CO 2… OR are intrinsic to the coupled system Trends in the ocean-atmosphere system  changes in solar forcing; aerosols; CO 2… OR are intrinsic to the coupled system

200-mb Z SST

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

An Approach to Attribution Analysis Analysis of observed anomalies (atmosphere, ocean, solar,…) Analysis of observed anomalies (atmosphere, ocean, solar,…) Conceptual separation of system into internal and external (or forced and forcing) components 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…) 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 Testing the hypothesis involves analyzing response to the external forcing Empirical approachEmpirical approach General circulation model approachGeneral circulation model approach

DJF 1997/ mb Z Model OBS

DJF 2001/ mb Z Model OBS

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 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? Is the AGCM response to an external forcing correct?

One possible solution is to One possible solution is to Use Multi-model approach as a “confidence (or consensus) builder” in documenting response to an external factorUse 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 madeOnce 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

DJF 1997/98

DJF 2001/02

Seasonal Diagnostics Consortium ModelCCM3NCEPNSIPPECHAM4.5 (From IRI) GFDL TypeSpectralSpectralGridSpectralGrid ResolutionT40L18T62L64 2 Deg Lat/LonT40L18N45L18 # of Simulations Total # of Simulations : 81

2004 EOS

Add the line plot Add the line plot

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

Atmospheric Response to SST Forcing

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Atmospheric Climate Model Simulations Observed SST Forcing InstitutionModelEnsemble Size GFDLAM-210 MPI/IRIECHAM-424 NASAGMAO23  Simulation production for  Specified monthly varying global SSTs  Climatological GHG/Aerosols  57 member multi-model ensemble  Experiments are part of Seasonal Climate Diagnostics Consortium

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Atmospheric Climate Model Simulations Idealized Indian Ocean SST Forcing InstitutionModelEnsemble Size GFDLAM-210 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 

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

Response Forced by the Observed SSTs

Coupled Ocn-Atm Climate Model Simulations Observed GHG/Aerosol Forcing  Simulation production for  Specified monthly varying GHG/Aerosol  A1B Scenario  18 Different Coupled Models/47 total runs  Experiments are part of the IPCC AR-4 Suite

Land Temp SSTs

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Validating Forecasts

NDJFM 2004/2005

Efforts in NOAA What currently exists: An informal activity maintaining monthly updates in AMIP runs forced by Global SSTs 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] 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; …) Such an activity can also support other model based “hypothesis testing” efforts (e.g., impact of different ocean basins; causality of trends and droughts; …)

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