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US National Multi-Model (NMME) Intra-Seasonal to Inter-Annual (ISI) Prediction System

US National Multi-Model (NMME) Intra-Seasonal to Inter-Annual (ISI) Prediction System. Why Multi-Model?. Multi-Model Methodologies Are a Practical Approach to Quantifying Forecast Uncertainty Due to Uncertainty in Model Formulation And, Apparently Improve Forecast Quality

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US National Multi-Model (NMME) Intra-Seasonal to Inter-Annual (ISI) Prediction System

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  1. US National Multi-Model (NMME) Intra-Seasonal to Inter-Annual (ISI) Prediction System

  2. Why Multi-Model? • Multi-Model Methodologies Are a Practical Approach to Quantifying Forecast Uncertainty Due to Uncertainty in Model Formulation • And, Apparently Improve Forecast Quality • Larger Ensembles Yield Better Resolved Uncertainty Due to Initial Condition Uncertainty • Multi-Model is also Multi-Institutional Bringing More Resources to the Effort • And, More Frequent Prediction System Updates

  3. Phase 1 NMME • CTB NMME Workshops February 18, April 8, 2011 • Establish Collaboration and Protocol for Experimental Real-time Multi-Model Prediction • Protocol Developed • Distributing Hindcast Data to CPC • Public Dissemination via IRI Data Library • Became Real-Time in August 2011 • Adhering to CPC Operational Schedule

  4. NMME Partners • University of Miami – RSMAS • Nation Center for Atmospheric Research (NCAR) • Center for Ocean-Land-Atmosphere Studies (COLA) • International Research Institute for Climate and Society (IRI) • University of Colorado – CIRES • NASA – GMAO • NOAA/NCEP/EMC/CPC • NOAA/GFDL • Canadian Meteorological Centre (Soon) • Princeton University

  5. (Preliminary) Hindcast Quality Assessment Verifying in February Each Ensemble Member from Each Model Weighted Equally – 83 Ensemble Members

  6. Complementary Correlation CFSv2(24) vs. CCSM3(4)+IRIa(4)+IRId(4)+CM2.1(4)+GEOS5(4)+CFSv1(4)

  7. Complementary Correlation NMME Benefits CFSv2 Ensemble CFSv2(24) vs. CCSM3(4)+IRIa(4)+IRId(4)+CM2.1(4)+GEOS5(4)+CFSv1(4)

  8. Complementary Correlation NMME Larger than CFSv2 Ensemble CFSv2 Larger than NMME CFSv2(24) vs. CCSM3(4)+IRIa(4)+IRId(4)+CM2.1(4)+GEOS5(4)+CFSv1(4)

  9. (Preliminary) Hindcast Quality Assessment Verifying in February Each Ensemble Member from Each Model Weighted Equally – 83 Ensemble Members

  10. Complementary Correlation NMME Larger than CFSv2 Ensemble NMME Benefits CFSv2 Ensemble CFSv2 Larger than NMME CFSv2 Benefits NMME CFSv2(24) vs. CCSM3(4)+IRIa(4)+IRId(4)+CM2.1(4)+GEOS5(4)+CFSv1(4)

  11. (Preliminary) Hindcast Quality Assessment 2 Each Ensemble Member from Each Model Weighted Equally – 83 Ensemble Members

  12. NMME Larger than CFSv2 Ensemble CFSv2 Larger than NMME CFSv2 Benefits NMME CFSv2(24) vs. CCSM3(4)+IRIa(4)+IRId(4)+CM2.1(4)+GEOS5(4)+CFSv1(4)

  13. Area Averaged Correlation (R2) Over North America: Model Ranks

  14. FMA2006 CMAP Precipitation Anomaly vs. All Model, All Ensemble Average FMA2006 (Aug2005 and Dec2005 IC) Precipitation Anomaly (*note color scale change for model images)

  15. FMA2006 NCDC SST Anomaly vs. All Model, All Ensemble Average FMA2006 (Aug2005 and Dec2005 IC) SST Anomaly

  16. FMA2007 CMAP Precipitation Anomaly vs. All Model, All Ensemble Average FMA2007 (Aug2006 and Dec2006 IC) Precipitation Anomaly (*note color scale change for model images)

  17. FMA2007 NCDC SST Anomaly vs. All Model, All Ensemble Average FMA2007 (Aug2006 and Dec2006 IC) SST Anomaly

  18. CPC Seasonal Prognostic Map Discussion (PMD): “PROGNOSTIC TOOLS USED FOR U.S. TEMPERATURE AND PRECIPITATION OUTLOOKS OUTLOOKS FOR JFM THROUGH AMJ 2012 WERE PRIMARILY BASED ON THE NEW NATIONAL MULTI-MODEL ENSEMBLE MEAN FORECAST (NMME).  THE FORECASTS STRONGLY AGREE WITH …”

  19. Phase 2 NMME • Continue Experimental Real-Time Predictions • Enhancing Current NMME Capability • Model Updates: GFDL-CM2.5 (20 km AGCM), IRI (T106), CCSM4, CESM1 • Assess Forecast Quality • MME Combinations, Model Independence • Drought Assessment • Include: soil moisture, runoff, evaporation • Sub-Seasonal Assessment • Forecast Protocol • Initial Condition Sensitivity Experiments • Ocean, Land • Improved Data Distribution • Under Discussion with NCAR

  20. May Initial Conditions 3-Months Lead Improved Correlation Due to Model Improvement and Better Initial Condition?

  21. 2012JFM NMME SSTA Predictions December 2011 Initial Conditions 2012FMA

  22. 2012JFM NMME Precip Predictions December 2011 Initial Conditions 2012FMA

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