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Upper Ocean Processes in the Indian Ocean associated with the Madden - Julian Oscillation

Upper Ocean Processes in the Indian Ocean associated with the Madden - Julian Oscillation. 1. Large-scale ocean variability: Satellite observations and OGCM experiments 2. Impact on Indonesian T hroughflow 3 . Diurnal cycle 4 . Variability of the Seychelles- Chagos thermocline ridge.

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Upper Ocean Processes in the Indian Ocean associated with the Madden - Julian Oscillation

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  1. Upper Ocean Processes in the Indian Ocean associated with the Madden-Julian Oscillation • 1. Large-scale ocean variability: Satellite observations and OGCM experiments • 2. Impact on Indonesian Throughflow 3. Diurnal cycle 4. Variability of the Seychelles-Chagos thermocline ridge Toshiaki Shinoda (Texas A&M Univ.,Corpus Christi), WeiqingHan (Univ. of Colorado),YuanlongLi (Univ. of Colorado), Chunzai Wang (NOAA/AOML)

  2. Large-scale Ocean Variability

  3. CINDY/DYNAMO field campaignSeptember 2011 – March 2012 Describe large-scale upper ocean variations surrounding the intensive array based on the analysis of the satellite-derived data and OGCM experiments.

  4. MJO events during DYNAMO Strong westerly anomalies Strong convection in the Indian Ocean associated with the MJO

  5. Satellite-derived Data • Surface winds: Windsat • Daily 3-day average • 0.25x0.25 deg. • Precipitation: TRMM 3B52 • 3-hourly • 0.25x0.25 deg. • Sea Surface Height (SSH): AVISO • Daily • 1x1 deg. • Sea Surface Temperature (SST): Blended Analysis (Reynolds et al. 2007) • Daily • 0.25x0.25 deg. • Surface current: OSCAR • 5-day average • 1x1 deg. • Sea Surface Salinity (SSS): Aquarius • weekly • 1x1 deg.

  6. Global Hybrid Coordinate Ocean Model (HYCOM) • Horizontal resolution: 1/25º, 1/12º Period: 2003-2012 Surface forcing fields: NOGAPS

  7. Surface winds RAMA NCEP Windsat Shinoda et al. (2013)

  8. Large–scale SST variation

  9. Large-scale surface salinity Aquarius RAMA

  10. Zonal Current SSH

  11. Reflected Rossby waves SSH (Satellite) SSH (HYCOM) D20 (HYCOM)

  12. Yoneyama et al. (2013) Webber et al. (2010)

  13. Impact on Indonesian Throughflow

  14. Seasonal variation of the Indonesian Throughflow Observation (Gordon et al. 2008) Modeling (Shinoda et al. 2012) Wyrtki Jet Wyrtki Jet PAC Rossby waves Velocity component (50 m depth: shading )and SSH(contour) along the line

  15. How dostrong MJO events during DYNAMO impact the Indonesian Throughflow? Global HYCOM Yoshida Jet Wyrtki Jet

  16. Meridional velocity at Makassar Strait Large changes in upper ocean currents Southward current is very weak in Jan.-Feb. in contrast to the seasonal cycle (rapid recovery of southward currents in Jan.-Feb.)

  17. Indonesian Throughflow Yoshida jet Anomalous northward currents in the Indonesian Sea in January can be traced back to the Yoshida Jet generated by the MJO

  18. Diurnal Cycle

  19. High vertical resolution (1m) in the upper 10m  HYCOM is able to reproduce observed diurnal warming

  20. Impact of diurnal cycle on intraseasonal variability TOGA COARE Nov. 1992-Mar. 1993 SCTR 55°–70°E, 12°–4°S CEIO (65°–95°E, 3°S–3°N) Shinoda (2005), Shinoda and Hendon (1988) Li et al. (2013)

  21. Thermocline Ridge Variability

  22. Impact of SCTR interannual variation Interannual variations of SCTR (e.g., deeper thermocline during IOD) How does ocean interannual variabiliti (OIV) impacts intraseasonal SST in SCTR? Additional HYCOM experiments (NoOIV): No interannual variation of surface forcing fields. Li et al. (2014) ---------- 95% significance ----------- 85% significance based on F-test The OIV effect enhances the intraseasonal SSTs in the eastern TR region by about 0.1 C (20% of the total SST variability) (significant at 95% level)and slightly reduces them in the western TR (not significant).

  23. The OIV effect varies from year to year ! Amplitude of the 20-90-day SST Enhancing effect, strong-TR years, Shallow Z20 Reducing effect, weak-TR years, Deep Z20 MR NoOIV Yearly Z20 from MR and NoOIV • A Strong TR (shallow thermocline) enhances intraseasonal SSTs, while a weak TR (deep thermocline) reduces intraseasonal SSTs.

  24. An asymmetry between strong and weak years Composite analysis for strong and weak TR years Weak-year composite Strong-year composite SSTt HF ENT SST variability, HF and ENT are greatly enlarged by a strong TR year, but only slightly reduced by a weak TR.

  25. MLD is an important cause Weak-year composite Strong-year composite > 10 m < 5 m An important source of the asymmetry: the MLD changes, which is shallower than normal by at least 10m in strong TR years, but is deeper than normal by only less than 5m in weak TR years. This difference leads to the strong/weak asymmetry of ENT and HF and thus the overall enhancing effect of the OIV.

  26. 12S-4S Mean Winter Temperature Weak TR Strong TR

  27. Summary A variety of upper ocean processes associated with the MJO that influence SST are identified by the analysis of OGCM experiments and satellite observations. These include: Equatorial jet Diurnal cycle Variation of theromocline ridge Remote ocean variability Further analyses are needed to understand how SST changes caused by these upper ocean processes feedback on the atmosphere. References: Li, Y., W. Han, T. Shinoda, C. Wang, R.-C. Lien, J.N. Moum, and J.W. Wang, 2013: Effects of Solar Radiation Diurnal Cycle on the Tropical Indian Ocean Mixed Layer Variability during Wintertime Madden-Julian Oscillation Events. J. Geophys. Res., DOI:10.1002/jgrc.20395. Li Y., W. Han, T. Shinoda, C. Wang, M. Ravichandran, J.-W. Wang, 2014: Revisiting the Wintertime Intraseasonal SST Variability in the Tropical South Indian Ocean: Impact of the Ocean Interannual Variation. J. Phys. Oceanogr., doi: http://dx.doi.org/10.1175/JPO-D-13-0238.1. Shinoda, T,. Jensen, M. Flatau, S. Chen, W. Han, C. Wang 2013: Large-scale oceanic variability during the CINDY/DYNAMO field campaign from satellite observations. Remote Sensing –Special issue on Observing the Ocean’s Interior from Satellite Remote Sensing, 5, 2072-2092. • Shinoda, T., W. Han, E. J. Metzger, H. E. Hurlburt , 2012: Seasonal Variation of the Indonesian Throughflow in Makassar Strait. J. Phys. Oceanogr., 42, doi:10.1175/JPOD-11-0120.1.

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