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Observational Issues Relevant to Seasonal-to-Interannual Modeling and Prediction

Observational Issues Relevant to Seasonal-to-Interannual Modeling and Prediction. Lisa Goddard and Dave DeWitt IRI. 25-27 April 2005. OCO 3 rd Annual Systems Review. Dominant pattern of precipitation error associated with dominant pattern of SST prediction error.

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Observational Issues Relevant to Seasonal-to-Interannual Modeling and Prediction

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  1. Observational Issues Relevant to Seasonal-to-Interannual Modeling and Prediction Lisa Goddard and Dave DeWitt IRI 25-27 April 2005 OCO 3rd Annual Systems Review

  2. Dominant pattern of precipitation error associated with dominant pattern of SST prediction error Loss of skill in AGCM due to imperfect predictions of SST (Goddard & Mason, 2002, Clim. Dyn.)

  3. Observations • FORCING – Climate Simulations - Investigate potential predictability of climate and regional/global climate diagnostics • INITIALIZATION – Climate Forecasts - Provide initial observed state • VERIFICATION – Climate Forecasts - Check performance of model generated SSTs (climatology, variability, predictability). • DIAGNOSTICS – Model Improvement - Identify model errors

  4. OIv2 vs. ERSSTv1 How can we verifyagainst the “truth” when we don’t know what “truth” is? SST AnomalyCorrelationsJanuary 1982-2003 ECH-MOM vs. OIv2 ECH-MOM vs. ERSSTv1

  5. SST AnomalyCorrelationsJanuary 1982-2003 OIv2 vs. ERSSTv2 ECH-MOM vs. OIv2 Success story! Reconstructed datanow agrees muchbetter with satelliteenhanced observations. ECH-MOM vs. ERSSTv2

  6. OIv2 ERSSTv2 2002/2003 El NiñoDec-Jan-Feb SST Anomalies

  7. SST Sampling Error Variance Average around 5S-5N belt Estimated Error Variance for July 2001

  8. Skillful climate prediction requires skillful SST prediction in the tropics. • Skillful SST prediction requires accurate GCMs • GCMs can be used for prediction and process studies if they do the right thing. We can really only assess what they do rightand wrong if the observations used for verification are accurate.

  9. COADS - Oberhuber COADS - DeSilva DaSilva - Oberhuber Pinker Pinker – Oberhuber Pinker – DaSilva “Observed” Surface Solar Flux(SW Heat Flux)January Climatology Ship-based Differences indeep tropics canexceed 60 W/m2 Ship-based Satellite-based

  10. Surface Solar Radiation from TAO ArrayNOTE: Incoming SW not net Totals Anomalies

  11. AGCM “Errors” in Surface Solar Radiation AGCM has too little SW relative to Pinker.AGCM has too much SW relative to Oberhuber.

  12. OGCM: MOM3 (Pacanowski and Griffies, 1998) Domain: 75°S to 65°N Resolution: Zonal Resolution – 1.5° everywhere Meridional Resolution – 0.5° between 10°S and 10°N Stretched to 1.5° between 10° and 30° Poleward of 30° fixed at 1.5° Vertical Resolution: 25 layers with 15 meter spacing in upper 10 layers Physical Parameterizations: KPP Vertical Mixing (Large et al. 1994) Penetrative Sunlight Smagoinsky Horizontal Mixing (1963) Gent-McWilliams (1990) – Quasi-adiabatic mixing Atmospheric Mixed Layer Model (AMLM):Seager and Blumenthal (1994) Forcing Data: • Wind – SSMI Level 3.0 (Atlas et al., 1996) • Specific Humidity & Temperature at Coast (NCEP Reanlysis (Kalnay et al., 1996) • Cloud Cover in Longwave Calculation (ISCCP) • Solar Flux: 1) Oberhuber (1988) 2) COADS (DaSilva, Young, and Levitus, 1994) 3) SRB (Pinker, 1992) 4) NCEP Reanalysis (Kalnay et al., 1996)

  13. Reynolds OIv2 Ann.Clim SST Error using COADS-DaSilva using COADS-Oberhuber using Pinker SST ErrorsAnnual Mean

  14. SST Sensitivity to Surface Solar Radiation SST Diff. : Pinker Forcing – DaSilva Forcing Solar Rad. Diff. : Pinker – DaSilva Sensitivity Sensitivity

  15. Annual Cycle DeviationsApril

  16. Annual Cycle DeviationsApril

  17. Annual Cycle DeviationsApril

  18. Relative Error in the Annual Cycle Large differences in deep convective regions of the Northern Hemisphere. Also sensitivity in the SPCZ region, whenactive.

  19. Issues Need ‘ground truthing’ of such observational data sets • Buoy measurements in place over many many years, preferably in regions of strong variability (both SST & clouds) However, those measurements must be amenable to rigorous testing in applications • Gridded format • Quality controlledError/uncertainty estimates (spatial & temporal) • Easily available

  20. Suggestions Would be more useful if TAO [gridded] data were filled in, both in space and time Model estimates are great, such as ECCO, but • Need components, not just total fluxes • Need estimate from more than 1 model If errors could be determined, might be able to go back and correct (e.g. ReAnalysis)

  21. Reynolds OIv2 Ann.Clim SST Error using COADS-DaSilva SST ErrorsAnnual Mean using COADS-Oberhuber using Pinker using NCEP/NCAR-RA1

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