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Convection process in the North Pacific from ARGO data

Convection process in the North Pacific from ARGO data. 1 Eunjeong Lee, Yign Noh, 2 Bo Qiu 1 Department of atmospheric sciences, Yonsei University 2 Department of Oceanography, University of Hawaii. Department of Atmospheric Sciences, Yonsei University. Contents. Objective About ARGO

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Convection process in the North Pacific from ARGO data

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  1. Convection process in the North Pacific from ARGO data 1Eunjeong Lee, Yign Noh, 2Bo Qiu 1Departmentof atmospheric sciences, Yonsei University 2Department of Oceanography, University of Hawaii Department of Atmospheric Sciences, Yonsei University

  2. Contents • Objective • About ARGO • Data analysis - ARGO - NCEP/NCAR reanalysis I • Results PartⅠ - Response of the ocean to the surface cooling - Deepening of MLD - In the KE region (Eddy process) PartⅡ - Correlation - Efficiency (deepening, heating & cooling) • Conclusion Department of Atmospheric Sciences, Yonsei University

  3. Objective • Analysis of the convection process in the upper ocean to the atmospheric forcing using ARGO data • How are the variations of the MLD and SST related to the surface forcing?  i) Understanding the air-sea interaction in the North Pacific ii) Providing the information for the parameterization of convection in the mixed layer model Department of Atmospheric Sciences, Yonsei University

  4. About ARGO • Processing • Position of float • Profile data, metadata, trajectories and technical data • An ascending profile with measurements (e.g. pressure, temperature, salinity) • Data mode (e.g. R : Real time, D : Delayed mode, A : adjusted values) • Quality control (e.g. 1:good data, 4:bed data, 9:missing value) Department of Atmospheric Sciences, Yonsei University

  5. Data analysis : ARGO • 27 different locations • Area : North Pacific (130-240˚E, 20-60˚N) • 0-500m depth • Period : 2001 - 2007 • Data processing • - use data with quality control 1 or 2. • - semi-monthly averaging • - mixed layer depth : z = z [T(0)-0.5] Department of Atmospheric Sciences, Yonsei University

  6. Data analysis : NCEP data • NCEP reanlaysis I – surface heat flux, SST • Surface heat flux • (+) : direction from atmosphere to ocean • Data processing • semi-monthly averaging • 2001-2007 data on an average compare with each year value Department of Atmospheric Sciences, Yonsei University

  7. Location Mean Each year Heat Flux SST MLD Part Ⅰ : Response of the ocean to the surface cooling • 150-155˚E, 28-30˚N • 135-140˚E, 28-30˚N 2005-2006년 2005-2006년 Reduce Department of Atmospheric Sciences, Yonsei University

  8. slower deepening faster deepening Part Ⅰ : Deepening of MLD in winter 135-140˚E, 28-30˚N Location 2004-2005년 2005-2006년 Heat Flux SST MLD Department of Atmospheric Sciences, Yonsei University

  9. Insensitive to surface heat flux Part Ⅰ :Deepening of MLD in winter 175-180˚W, 42-44˚N Location 2003-2004년 2002-2003년 Heat Flux SST MLD Department of Atmospheric Sciences, Yonsei University

  10. The KE region • Near 145˚E, 35˚N • High T & S (20°, 34.5‰), 50~300m/s velocity • Eddy process Department of Atmospheric Sciences, Yonsei University

  11. The KE region PDO index EKE level [Qiu et al.(2008)] • Center of action of wind forcing is in the eastern half of the N Pacific basin • Positive (negative) phase of PDO generates – (+) local SSH through Ekman divergence (convergence) Department of Atmospheric Sciences, Yonsei University

  12. Part Ⅰ :Eddy process 145-150˚E, 32-34˚N Location 2004-2005년 2005-2006년 Heat Flux SST MLD Department of Atmospheric Sciences, Yonsei University

  13. Part Ⅰ :Eddy process Kuroshio Extension • 155-160˚E, 32-34˚N 2005-2006년 Location the effect of internal ocean dynamics is important → eddy process Due to eddy processing MLD Eddy processing interrupt MLD deepening Department of Atmospheric Sciences, Yonsei University

  14. No horizontal advection Part Ⅱ :Relation d(MLD)=MLD(t+15)-MLD(t) • 130-135˚W, 50-52˚N d(MLD)&Qdt d(SST)&Qdt SST&MLD Department of Atmospheric Sciences, Yonsei University

  15. Part Ⅱ :Relation • 155-160˚E, 32-34˚N d(MLD)&Qdt SST&MLD d(SST)&Qdt horizontal advection Department of Atmospheric Sciences, Yonsei University

  16. -0.1 -0.05 -0.6 -0.5 -0.4 -0.3 -0.2 0.05 0.1 0.2 0.3 0.4 0.5 0.6 -0.8 0 0.8 Part Ⅱ : Correlation summer • d(MLD) & Qdt MAY & JUN JUL & AUG d(SST)Qdt • Strong heating→strong stratification • → shallower MLD • Weak correlation in the KE region duo to advection effect • Already shallow MLD • → no longer weakening of MLD Department of Atmospheric Sciences, Yonsei University

  17. -0.1 -0.05 -0.6 -0.5 -0.4 -0.3 -0.2 0.05 0.1 0.2 0.3 0.4 0.5 0.6 -0.8 0 0.8 Part Ⅱ : Correlation Earlysummer • d(MLD) & Qdt Weak eddy Strong eddy Department of Atmospheric Sciences, Yonsei University

  18. -0.1 -0.05 -0.6 -0.5 -0.4 -0.3 -0.2 0.05 0.1 0.2 0.3 0.4 0.5 0.6 -0.8 0 0.8 Part Ⅱ : Correlation winter • d(MLD) & Qdt NOV & DEC JAN & FEB d(SST)Qdt • Strong cooling →weak stratification • → rapid convective deepening • Weak correlation in the KE region duo to advection effect • Already deep MLD • → no longer deepening of MLD • : Maximum MLD is insensitive to surface cooling Department of Atmospheric Sciences, Yonsei University

  19. -0.1 -0.05 -0.6 -0.5 -0.4 -0.3 -0.2 0.05 0.1 0.2 0.3 0.4 0.5 0.6 -0.8 0 0.8 Part Ⅱ : Correlation Early winter • d(MLD) & Qdt Weak eddy Strong eddy Department of Atmospheric Sciences, Yonsei University

  20. Part Ⅱ : Deepening efficiency • Deepening efficiency Department of Atmospheric Sciences, Yonsei University

  21. Stronger efficiency than NOV& DEC except KE region -0.02 -0.01 -0.005 -0.004 -0.001 0 0.001 11 0.003 12 0.004 0.005 0.007 0.01 0.02 -0.007 -0.003 -0.002 0.002 Part Ⅱ : Deepening efficiency winter • Deepening efficiency NOV & DEC JAN & FEB • Overall positive efficiency • Negative efficiency in the KE region Department of Atmospheric Sciences, Yonsei University

  22. Part Ⅱ : Heating(Cooling) efficiency • Heating(Cooling) efficiency Department of Atmospheric Sciences, Yonsei University

  23. -0.02 -0.01 -0.005 -0.004 -0.001 0 0.001 11 0.003 12 0.004 0.005 0.007 0.01 0.02 -0.007 -0.003 -0.002 0.002 Part Ⅱ : Heating(Cooling) efficiency summer • Heating efficiency MAY & JUN JUL & AUG Advection + heating effect Low heating efficiency Department of Atmospheric Sciences, Yonsei University

  24. Advection + heating effect Advection + cooling effect -0.02 -0.01 -0.005 -0.004 -0.001 0 0.001 11 0.003 12 0.004 0.005 0.007 0.01 0.02 -0.007 -0.003 -0.002 0.002 Part Ⅱ : Heating(Cooling) efficiency winter • Cooling efficiency NOV & DEC JAN & FEB Low cooling efficiency Department of Atmospheric Sciences, Yonsei University

  25. Conclusion • The response of the ocean mixed layer and sea surface temperature to surface forcing in the Pacific was investigated by analyzing ARGO data. • The d(SST) and d(MLD) has high correlation and efficiency with surface cooling except in the KE region in early summer and winter. • The d(MLD) are more sensitive to the surface heat flux in late summer and winter. • The initial convective deepening shows large variability, but the maximum MLD does not show much variability. • In the KE region, • - the MLD increase is interrupted by mesoscale eddies • - the heat transport by the Kuroshio is important to determine SST Department of Atmospheric Sciences, Yonsei University

  26. Reference • Argo Data Management Team (2004), Argo quality control manual, version 2.0b, p. 23, Argo Data Manage., Toulouse, France. • Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, A. Leetmaa, R. Reynolds, R. Jenne, and D. Joseph (1996), The NCEP/NCAR 40-Year Reanalysis Project, Bull. Am. Meteorol. Soc., 77, 437- 471. • Qiu, B., S. Chen, and P. Hacker (2007), Effect of mesoscale eddies on Subtropical Mode Water variability from the Kuroshio Extension System Study (KESS), J. Phys. Oceanogr., 37, 982-1000. Department of Atmospheric Sciences, Yonsei University

  27. Thank you Department of Atmospheric Sciences, Yonsei University

  28. (a) Upstream KE path length (141-153°E) (b) Eddy kinetic energy (141-153°E, 32-38°N) Stable yrs: 1993-94, 2002-04 Unstable yrs: 1996-2001, 2006-07

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