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Climate Reanalysis Task Force, Telecon, June 25, 2014

Real-time Ocean Reanalyses Intercomparison : Ocean/Climate M onitoring U sing Ensemble Ocean Reanalysis P roducts. Y. Xue 1 , M. Balmaseda 2 , Y. Fujii 3 , G. Vecchi 4 , G. Vernieres 5 , O. Alves 6 , A. Kumar 1 , T. Lee 7 , D. Legler 8 1 NCEP/NOAA, USA 2 ECMWF 3 JMA, Japan

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Climate Reanalysis Task Force, Telecon, June 25, 2014

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  1. Real-time Ocean ReanalysesIntercomparison: Ocean/Climate Monitoring Using Ensemble Ocean Reanalysis Products Y. Xue1, M. Balmaseda2, Y. Fujii3, G. Vecchi4, G. Vernieres5, O. Alves6, A. Kumar1, T. Lee7, D. Legler8 1 NCEP/NOAA, USA 2 ECMWF 3 JMA, Japan 4 GFDL/NOAA, USA 5 GSFC/NASA, USA 6 BOM, Australia 7 JPL/NASA, USA 8 CPO/NOAA, USA Climate Reanalysis Task Force, Telecon, June 25, 2014

  2. The GODAE (Global Ocean Data Assimilation Experiment) 1997-2008 • GODAE OceanView (2009-2013) • Improvement of operational ocean analysis and forecasting systems • Verification of ocean analysis and forecasting products • Utilization of ocean analysis and forecast products • Demonstration of value of sustained ocean observing systems

  3. Challenges for GODAE OceanView • Develop coupled ocean-atmosphere data assimilation system for improved weather and climate prediction • Develop ecosystem forecast products for coastal regions • Demonstrate benefits and optimize use of ocean observations • Improve ocean reanalyses for monitoring climate variability and climate change • Improve ocean estimations for environmental monitoring

  4. CLIVAR GSOP/GODAE OceanView • Ocean Reanalysis Intercomparison • (ORA-IP) • Reanalysis production is an on-going activity • New vintages are produced approximately every 5 years • Improved quality controlled observations (XBT corrections, Argo corrections and black lists) • Improved-extended forcing fluxes • Improved models and methods • We need to assess progress, learn lessons, exploit resources and ask questions for future improvement • We need to facilitate the use of reanalyses by other communities • We need to prepare for quasi-real time monitoring of the ocean Balmaseda et al. 2013, GODAE Symposium

  5. TAO/TRITON: Cornerstone of ENSO Observing System • Real time ENSO monitoring and prediction • Ocean initialization for seasonal predictions • Behringer et al. 1998; Alves et al. 2003; Balmaseda et al. 2007; Balmaseda and Anderson 2009; Stockdale et al. 2011; Xue et al. 2013 (for CFSv2) ENSO Diagnostic Discussion Yan Xue Climate Prediction Center

  6. Tropical Pacific Observing System (TPOS) 2020 Workshop Aims (January 27-30, 2014, La Jolla, CA) • Highlight the impactsof the tropical Pacific observing system on information/services of societal relevance – El Nino monitoring and prediction • Evaluate existing and potential requirements for sustained observations of ocean variables in tropical Pacific Ocean – uncertainties in state estimation in tropical Pacific • Evaluate the adequacy of existing observing strategies • Recommend revisions and/or adjustments to enhance resilience, efficiency, integration. • Evaluate logistical requirements for implementation of the recommended Tropical Pacific Observing System. • Assess readiness of new technologies, their potential impact and feasibility in addressing requirements, and/or lowering costs per observation.

  7. Operational Ocean Reanalysis Argo Ocean Observing System Altimeter CTD Moorings XBT SST Ocean Model Data Assimilation System Operational Atmosphere Reanalysis Surface Fluxes Operational Ocean Reanalysis Ocean Monitoring Seasonal Forecast Model ENSO Prediction

  8. Operational Ocean Reanalysesc Xue et al. 2012, J. Climate

  9. Real-Time Ocean Renalyses Intercomparison • Extend the CLIVAR-GSOP/GODAE OceanView Ocean Reanalyses Intercomparison Project (ORA-IP) into real time • Assess uncertainties in temperature analysis of tropical Pacific in support of ENSO monitoring and prediction • Explore any connections between gaps in TAO array and spreads among ensemble ORAs • Articulate needs for sustained ocean observing systems in support of TPOS2020 • Monitor consistency and discrepancy among ensemble ORAs Yan Xue Climate Prediction Center

  10. http://www.cpc.ncep.noaa.gov/products/GODAS/multiora_body.htmlhttp://www.cpc.ncep.noaa.gov/products/GODAS/multiora_body.html

  11. The spread is large (>0.6C) between 140W-100W, and 120E-140E, where data distribution is poor.

  12. Public Use of Ensemble Ocean Reanalysis Products NOAA ENSO blog issued on June 6 introduced the real-time multiple ocean reanalysis intercomparison products http://www.climate.gov/news-features/blogs/enso/details-june-2014-enso-discussion ENSO Blog by Watts Up With That also used many plots from real-time multiple ocean reanalysis intercomparison web site http://wattsupwiththat.com/2014/06/10/noaa-reaches-out-to-the-blogosphere/#more-111157

  13. Consistency among ORAs tends to increase with time, particularly in the tropical Pacific, the tropical Indian Ocean and extra-tropical southern oceans, and is partly due to constraints from tropical mooring arrays and Argo floats. • HC300 anomalies (HC300a) associated with ENSO are highly consistent among ORAs; HC300a associated with IOD are moderately consistent; HC300a associated with the Atlantic zonal mode has considerable uncertainties among ORAs, which are comparable to signals. • An ensemble of operational ocean reanalyses provide a tool to monitor signals and uncertainties in upper ocean heat content in real time. Summary

  14. Thanks! Comments and Suggestions?

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