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Yan Xue Climate Prediction Center, NCEP

The NCEP GODAS Ocean Analysis of the Tropical Pacific Mixed Layer Heat Budget on Seasonal to Interannual Time Scales. Yan Xue Climate Prediction Center, NCEP. Acknowledgements: Boyin Huang, David Behringer, Arun Kumar (CPC) Dongxiao Zhang, Michael J. McPhaden (PMEL).

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Yan Xue Climate Prediction Center, NCEP

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  1. The NCEP GODAS Ocean Analysis of theTropical Pacific Mixed Layer Heat Budget on Seasonal to Interannual Time Scales Yan Xue Climate Prediction Center, NCEP Acknowledgements: Boyin Huang, David Behringer, Arun Kumar (CPC) Dongxiao Zhang, Michael J. McPhaden (PMEL) The CTB Seminar, COLA, Maryland, November 19, 2009

  2. Seasonal to Interannual Forecasting at NCEP Argo Ocean Initial Conditions Altimeter Moorings Seasonal Forecasts for North America XBT SST Climate Forecast System (CFS) CCA, OCN MR, ENSO Global Ocean Data Assimilation System (GODAS) IRI SST Anomaly Forecast Forecasters CCA, CA Markov Reanalysis 2 Surface Fluxes IRI Official Probabilistic Surface Temperature & Rainfall Forecasts Official ENSO Forecast

  3. Operational Global Ocean Data Assimilation System (GODAS) Model • GFDL’s Module Ocean Model v3 • Quasi-global 74oS – 64oN, 1ox1o (1/3o in tropics), 40 vertical levels • Monthly/pentad outputs, 1979-present, 1 day delay Forcing • Wind stress, heat fluxes, E-P from Reanalysis 2 • SST relaxed to OI SST • SSS relaxed to Levitus climatology Assimilation method • 3D variational scheme, limited to upper 750m • Univariate in temperature and salinity • Error covariance varies geographically and temporally Assimilation data • Temperature from XBTs, Argo, TAO/TRITON/PIRATA • Synthetic salinity constructed from temperature and local T-S climatology • Sea surface height from Jason-1 since March 14 2007

  4. Global Ocean Monitoring Products Based on GODAS (delivering climate information to society) http://www.cpc.ncep.noaa.gov/products/GODAS/ • Synthesis of global ocean observations by NCEP’s Global Ocean Data Assimilation System (GODAS) • Climatology and anomaly plots for each month in 1979 – present • Monthly Ocean Briefing • Annual Ocean Review • Intended for use by operational climate prediction centers, researchers, fishery managers, industries, news media, program managers, teachers and students Synthesis of Ocean Observations Contact: Yan Xue, NOAA/CPC

  5. The Ocean Component of the NCEP ENSO CFSNOAA/OGP/CTB Project (Mar 2006 – Feb 2009)PIs: Michael J. McPhaden, Dongxiao Zhang (NOAA/PMEL) Yan Xue, David Behringer (NOAA/NCEP) • Diagnose the physical processes in the upper tropical Pacific that determine the ENSO development using observations, GODAS, CFS forecasts. • Conduct tropical Pacific temperature, salinity and current analysis based on Argo, TAO, and XBT data. • Construct and maintain a web site for real time comparison between observations, GODAS, and CFS forecasts.

  6. Motivations for Heat Budget Analysis • What physical processes control the evolution of SST anomaly in the tropical Pacific? • Can GODAS provide a tool for monitoring and understanding the heat budget of the tropical Pacific mixed layer in real time? • How well does GODAS simulate the climatological heat budget? • How well does GODAS simulate the anomalous heat budget associated with ENSO? Huang, B., Y. Xue, X. Zhang, A. Kumar, and M. J. McPhaden, 2009: The NCEP GODAS ocean analysis of the tropical Pacific mixed layer heat budget on seasonal to interannual time scales, Submitted to J. Clim.. Xue, Y., Alves, O., Balmaseda, M., Ferry, N., Good, S., Ishikawa, I., Lee, T., McPhaden, M., Peterson, D., & Rienecker, M., 2010: Ocean state estimation for global ocean monitoring: ENSO and beyond ENSO. In Proc. "OceanObs’09: Sustained Ocean Observations and Information for Society" Conference (Vol. 2), Venice, Italy, 21-25 September 2009, Hall, J., Harrison D.E. and Stammer, D., Eds., ESA Publication WPP-306.

  7. Model Data Sets • Pentad Temperature, salinity, U, V, W with data assimilation (GODAS) • Pentad Temperature, salinity, U, V and W without data assimilation (CTL) • Pentad R2 surface heat fluxes Validation Data Sets • OI SST version 2 • Levitus temperature and salinity climatology • TAO currents at 165oE, 170oW, 140oW, 110oW • OSCAR surface currents • OAFluxlatent and sensible • ISCCP short and long wave radiation

  8. 1oS-1oN Sea Surface Temperature Biases OI GODAS GODAS - OI

  9. Mean Surface Heat Flux Biases(1984-2002) (W/m2) Net Heat Net Heat Flux Short Wave Latent Flux - 60 W/m2

  10. Surface Heat Flux Annual Cycle (1oS-1oN) Net Surface Heat Flux Biases R2 - OAFlux Surface Heat Flux Correction (Relaxation to OI SST) GODAS – OI SST

  11. Anomaly Correlation with OAFlux Net Heat Latent Flux Net Heat Flux Short Wave good correlation Net heat flux anomaly correlates well with OAFlux in the NINO3.4 region.

  12. 1oS-1oN Mixed Layer Depth Annual Cycle (m) Levitus GODAS GODAS 82-04 GODAS-WOD 2001 GODAS - Levitus

  13. Sea Surface Salinity and Mixed Layer Depth, 5oS-5oN Average GODAS PMEL GODAS-PMEL SSS SSS SSS Diff. MLD MLD MLD Diff. White contour shows the 29°C isotherm, indicating the edge of warm pool

  14. Zonal Current at 15m Depth (1oS-1oN, 1993-2007) OSCAR OSCAR GODAS GODAS GODAS-GODAS GODAS - OSCAR

  15. Surface Current Biases: GODAS vs TAO U V 140W 110W 170W 165E

  16. Methodology for Mixed Layer Heat Budget 1. Mixed layer temperature equation Stevenson and Niiler ,1983 Wang and McPhaden, 1999 Qu: Zonal advection; Qv: Meridional advection; Qw: Vertical entrainment Qzz: Vertical diffusion • Qq: (Qnet - Qpen + Qcorr)/ρcph; Qnet = SW + LW + LH +SH; • Qpen: SW penetration; Qcorr: Flux correction due to relaxation to OI SST 2. Low and high (<75 days) frequency decomposition Kessler et al. 1998 3. Annual cycle and anomalydecomposition

  17. Climatological Heat Budget Closure: NINO3.4 CTL ACC=0.99 GODAS ACC=0.97

  18. Anomalous Heat Budget Closure: NINO3.4 CTL ACC=0.95 GODAS ACC=0.70

  19. Mean Heat Budget (1982-2004, oC/month) Qv: cooling too strong Qu: cooling too strong Eddy: heating too weak

  20. Annual Cycle Heat Budget (0.5oN, oC/month) Qu Qv Qq Qw+Qzz Tt Eddy

  21. Annual Cycle Heat Budget at TAO Sites Qu Qv Tt Tt Qv Qu Qq Qw+Qzz Too weak Qq Qw+Qzz Wang and McPhaden, 1999

  22. ENSO Composite (1oS-1oN) Composite members: 82-83, 91-92, 94-95 02-03, 04-05, 06-07 86-88, 97-98 excluded Onset phase: Qu, Qv, Qw+Qzz Damping factors: Qq, Eddy Decay phase: Qu, Qq Warm biases

  23. ENSO Composite Heat Budget: NINO3.4 U’Tbar Qu Qq

  24. NINO3.4 Heat Budget: 09/10 El Nino The recent large warming tendency since Oct is largely due to Qu. The model simulated intraseasonal variability in Qu, but not in Qw+Qzz during Jul-Oct. This insensitivity of Qw+Qzz to oceanic Kelvin waves might be model biases that also lead to imbalance of heat budget. Qu and Qw+Qzz contributed to the warming tendency in Mar-Jun. Qq and Qu contributed to the decay of the cold anomaly in the early spring 09.

  25. NINO3.4 Heat Budget: 06/07 El Nino The model generally underestimated intraseasonal variability in the temperature tendency. Qucontributed to the sudden decrease of the warm anomaly in the early spring 07 due to upwelling oceanic Kelvin waves. Qu,QvandQw+Qzzall contributed to the onset of the warm anomaly in the summer 06.

  26. 09/10 El Nino 06/07 El Nino

  27. 09/10 El Nino 06/07 El Nino

  28. NINO3.4 Heat Budget: 02/03 El Nino Qu and Qqcontributed to the decay of the warm anomaly in the late winter 02/03 and spring 03. Qw+Qzz,QvandQuall contributed to the onset of the warm anomaly in the early summer 02.

  29. NINO3.4 Heat Budget: 97/98 El Nino The model underestimated the cooling tendency in spring 98, probably due to the westward zonal current anomaly biases. Qqcontributed to the decay of the warm anomaly in spring 98, while all the advection terms contributed to the sudden cooling in late May 98. Qw+Qzz,QvandQuall contributed to the onset of the warm anomaly in the spring 97.

  30. NINO3.4 Heat Budget: 91/92 El Nino Qu and Qqcontributed to the decay of the warm anomaly in the spring 92. Qw+Qzz,andQvcontributed to the onset of the warm anomaly in the spring/summer 91.

  31. Summary • Short wave radiation from Reanalysis 2 has about 50 W/m2 negative biases, which results in about 50 W/m2 deficient fluxes into the GODAS ocean. • GODAS simulates SST reasonably well due to relaxation to OI SST, which provides about 30 W/m2 warming to compensate the 50W/m2 deficit in Reanalysis 2 net surface heat fluxes. • GODAS simulates 20m too deep mixed layer depth west of the Dateline due to underestimation of the fresh pool and its interannual variability associated with ENSO. • GODAS has large (40 cm/s) westward surface current biases in the far western and eastern Pacific, and eastward biases in the east-central Pacific. However, zonal current anomaly is simulated reasonably well.

  32. Summary • GODAS simulates the mean and annual cycle of the heat budget in the tropical Pacific mixed layer with a moderate skill due to some biases in zonal and meridional advection and underestimation of eddy heating from TIW. • The heat budget anomaly for the NINO3.4 region for each El Nino event since 1980 has been examined. GODAS simulates interannual variability of the heat budget well, but underestimates the intraseasonal variability. • The heat budget closure is satisfied reasonably well for moderate events (91/92, 94/95, 02/03, 06/07), but not well for strong events (82/83, 86/87, 97/98), pointing to analysis and model errors. • All advection terms (Qu, Qw+Qzz, Qv) contribute to the onset of El Nino, Qq and Qu to the decay phase, and Qu and Qw+Qzz, to the onset of La Nina.

  33. Thanks!

  34. NINO3.4 Heat Budget: 94/95 El Nino

  35. NINO3.4 Heat Budget: 82/83 El Nino

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