Six ALAMO floats, two EM-APEX floats, and a buoy were deployed in northwest
Australia on 22nd Nov 2018 (Feng et al. 2020). In the middle of December 2018, two
ALAMO floats, and two EM-APEX floats remained and recorded the ocean temperature,
salinity, and horizontal velocity during one MJO event when was from 14th to 18th Dec.
These data sets aided us in exploring the upper ocean response to the MJO and heat flux
variation to the MJO’s deep convection.
MJOs are typically associated with a westerly wind. During the MJO, the wind speed
rose to around 10 m s-1. In the upper ocean, the current velocity forced by the wind
increased up to 0.4 m s-1 above 40 m. At the same time, an upper ocean and SST cooling
event were observed since 14th Dec. The temperature in the upper 40 m dropped about
1.1 °C in one day. The cold water below the MLD should entrain into the upper ocean
and cool the SST near the sea surface. Due to the drop in SST, the difference between air
temperature and SST changed. In addition, the wind speed also favored evaporation. As
a result, air-sea heat flux was modified to rise from 100 Wm-2 to 400 Wm-2.
The MLD was deepened from 25 m to 50 m during this MJO period. By using the
float measurements, the buoyancy frequency was computed and was frequently less than
zero within the MLD. Additionally, the vertical shear was up to 3 3×104 N m-2. These
allowed the Richardson number to be less than 0.25, implying the upper ocean was
unstable. Using the Thorpe scale method, the turbulent dissipation rate was estimated by
10-8 to 10-6 W kg-1. These were larger than those within the typical thermocline. Thus,
strong turbulent mixing happened via shear instability during the MJO, resulting in MLD
deepening. This process allowed the cold water below the MLD to be entrained into the
upper ocean, resulting in SST cooling.
We used KPP in one-dimensional ROMS to simulate the MLD deepen under the buoy
wind measurement. In the model, MLD did not consist of observation MLD and did not
change significantly in the first two MJO days. Sensitive tests on the effect of vertical
resolution and mixing parameters were used to find the critical factor in simulating
turbulent mixing under MJO. By tuning the turbulence simulation parameter, increasing
the critical bulk Richardson number significantly affected the MLD simulation in that
higher critical bulk Richardson number was able to reach a deeper KPP boundary layer.
Comparing the current velocity between the observations and model, the mean
current velocity in the upper 20 m was 0.2 m s-1 and 0.1 m s-1, respectively. The difference
in current acceleration rate will result in different wind stress fluxes. The drag coefficient
is adjusted manually to perform the sensitive test, so different magnitudes of surface wind
stress will be used for forcing the ocean current. According to the model simulations, the
simulated results of MLD do not agree well with the observations unless 1.8 times of
wind drag coefficient is used. The momentum flux between the observations and model
results might be different. As a result, the linear momentum budget was used to estimate
wind stress. The results demonstrated that the difference between the observation and
model was about 0.2 N m-2 and 0.075 N m-2 in time rate change on velocity and Coriolis
force, respectively. Thus, the wind stress estimated by COARE 3.0 may be
underestimated in ROMS, resulting in the MLD being inconsistent with observation.
Even considering the buoyancy effect by tuning the heat flux with ± 50 W m-2 as the
uncertain wind speed and temperature variation, the effect is just about 2 m discrepancies.
Despite the fact that buoyancy allows MLD to get deepen. However, the wind stress effect
is more significant than buoyancy in MLD simulation under the MJO wind field.
Therefore, COARE 3.0 still underestimated wind stress on MLD simulation under MJO
when considering the buoyancy effect on turbulence simulation.
In summary, the high wind speeds during the active phase of MJOs trigger the ocean
current and thereby larger vertical shear for the growth of turbulence. The vertical velocity
shear should destabilize the upper ocean during the MJO. The turbulence mixing at the
base of MLD allows the cold water entrains to upper and cool down the SST. Due to the
SST variation, heat flux is modified and may influence the MJO convection developments.
In the model, wind stress estimation is the critical factor in MLD simulation. The wind
stress scheme from the COARE 3.0 algorithm in ROMS should be underestimated during
the MJO, which will result in the failure of the MLD simulation well. The consequence
of MLD failing to simulate may affect MJO simulation and forecast in the model. As a
result, field measurements on ocean current and wind speed are able to explore the
momentum flux between air-sea during MJOs. The correct wind stress estimation may
also improve the MJO forecast by being used in the global coupled model in the future.
A.B. Kara, P.A. Rochford, H. Hurlburt, (2000). An optimal definition for ocean mixed
layer depth. J. Geophys. Res., 105 (2000), pp. 16803-16821.
Bernie, D. J., E. Guilyardi, G. Madec, J. M. Slingo, S. J. Woolnough and J. Cole, (2008).
Impact of resolving the diurnal cycle in an ocean–atmosphere GCM. Part 2: A
diurnally coupled CGCM. Climate Dynamics, 31, 909-925, doi:
Chen, D., L.M. Rothstein, and A.J. Busalacchi, (1994). A hybrid vertical mixing scheme
and its application to tropical ocean models. J. Phys.Oceanogr.,24, 2156–2179.
Cole, R., J. Kinder, C. L. Ning, W. Yu, and Y. Chao, (2011). “Bai-Long”: A TAO-hybrid
on RAMA. OCEANS’11 MTS/IEEE KONA, Waikoloa, HI, IEEE,
DeMott, C. A., Klingaman, N. P. & Woolnough, S. J. (2015). Atmosphere–ocean coupled
processes in the Madden-Julian Oscillation. Rev. Geophys. 53, 1099–1154.
Emanuel, K. A., 1995: Sensitivity of tropical cyclones to surface exchange coefficients
and a revised steady-state model incorporating eye dynamics. J. Atmos. Sci., 52,
3969–3976, doi:10.1175/1520-0469(1995)052, 3969: SOTCTS.2.0.CO;2.
Fairall, C. W., E. F., Bradley, D. P., Rogers, J. B., Edson, and G. S., Young, 1996a. Bulk
parameterization of air‐sea fluxes for Tropical Ocean‐Global Atmosphere Coupled
Ocean Atmosphere Response Experiment, J. Geophys. Res., 101, 3747– 3764,
Fairall, C.W., E. F. Bradley, J. E. Hare, A. A. Grachev, and J. B. Edson, 2003. Bulk
Parameterization of Air-Sea Fluxes: Updates and Verification for the COARE
Algorithm. J. Climate, 16, pp 571-591.
Feng, M., Y., Duan, S., Wijffels, J.-Y., Hsu, C., Li, H., Wang, Y., Yang, H., Shen, J., Liu,
C., Ning, and W., Yu, 2020. Tracking air-sea exchange and upper ocean variability
in the Southeast Indian Ocean during the onset of the 2018-19 Australian summer
monsoon. Bulletin of the American Meteorological Society.
Friedrich A. Schott, Shang-Ping Xie, Julian P. McCreary Jr (2009). Indian Ocean
circulation and climate variability. Rev. Geophys., 47 (1), p. G1002.
Geernaert, G. L., 1990: Bulk parameterizations for the wind stress and heat fluxes.
Surface Waves and Fluxes, G. L. Geernaert and W. J. Plant, Eds., Vol. 1, Kluwer
Academic, 336 pp.
Howard, L. (1961). Note on a paper of John W. Miles. Journal of Fluid Mechanics, 10(4),
Hsu, J.-Y., R.-C. Lien, E. A. D’Asaro, and T. B. Sanford, (2017). Estimates of surface
wind stress and drag coefficients in Typhoon Megi. J. Phys. Oceanogr., 47, 545–565,
Je-Yuan Hsu, Ming Feng and Susan Wijffels (2022). Rapid restratification of the ocean
surface boundary layer during the suppressed phase of the MJO in austral spring.
Environ. Res. Lett. 17 024031.
Large, W. G., J. C. McWilliams, and S. C. Doney, (1994). Oceanic vertical mixing: A
review and a model with a nonlocal boundary layer parameterization, Reviews of
Geophysics, 32, 363- 403.
Liu, L. L., Li, Y. L., & Wang, F. (2021). MJO-induced intraseasonal mixed layer depth
variability in the equatorial Indian Ocean and impacts on subsurface water
obduction. Journal of Physical Oceanography, 51, 1247– 1263.
Lorbacher, K., Dommenget, D., Niiler, P. P., & Köhl, A. (2006). Ocean mixed layer depth:
A subsurface proxy of ocean-atmosphere variability. Journal of Geophysical
Research, 111(C7). https://doi.org/10.1029/2003JC002157.
Lukas, R., and E. Lindstrom, 1991. The mixed layer of the western equatorial Pacific
Ocean, J. Geophys. Res., 96(S01), 3343– 3357, doi:10.1029/90JC01951.
Madden, R. A., & Julian, P. R. (1972). Description of global-scale circulation cells in the
tropics with a 40–50 day period. Journal of the Atmospheric Sciences,
29(6), 1109– 1123. https://doi.org/10.1175/15200469(1972)029<1109:dogscc>2.0.
Marshall, A. G., and H. H. Hendon, (2014). Impacts of the MJO in the Indian Ocean and
on the western Australian coast. Climate Dyn., 42, 579–595,
Marshall, A.G., Hendon, H.H. Impacts of the MJO in the Indian Ocean and on the Western
Australian coast. Clim Dyn 42, 579–595 (2014).
Miles, J. W. 1961 On the stability of heterogeneous shear flows. J. Fluid Mech. 10, 496.
Moum, J. N., S. P. de Szoeke, W. D. Smyth, J. B. Edson, H. L. DeWitt, A. J. Moulin, E.
J. Thompson, C.J. Zappa, S. A. Rutledge, R. H. Johnson, and C. W. Fairall, (2014).
Air–Sea Interactions from Westerly Wind Bursts During the November 2011 MJO
in the Indian Ocean. Bull. Amer. Meteor. Soc., 95, 1185–1199,
Nagura, M., and M. J. McPhaden, (2008). The dynamics of zonal current variations in the
central equatorial Indian Ocean. Geophys. Res.Lett., 35, L23603,
Price, J. F., R. A. Weller and R. Pinkel (1986). Diurnal cycling: Observations and models
of the upper ocean response to diurnal heating, cooling, and wind mixing. Journal of
Geophysical Research: Oceans, 91, 8411-8427, doi: 10.1029/JC091iC07p08411.
Ruppert, J. H., and R. H. Johnson, (2015). Diurnally modulated cumulus moistening in
the preonset stage of the Madden-Julian oscillation during DYNAMO, Journal of
the Atmospheric Sciences, 72, 1622–1647.
Sanford, T. B., J. F. Price, and J. B. Girton, (2011). Upper-ocean response to Hurricane
Frances (2004) observed by profiling EM-APEX floats. J. Phys. Oceanogr., 41, 1041
Sanford, T. B., J. H. Dunlap, J. A. Carlson, D. C. Webb, and J. B. Girton, (2005).
Autonomous velocity and density profiler: EM-APEX. Proc. IEEE/OES Eighth
Working Conf. on Current Measurement Technology, 2005, Southampton, United
Kingdom, IEEE, 152–156, doi:10.1109/CCM.2005.1506361.
Shchepetkin, A. F., and J. C. McWilliams, 2005. The regional oceanic modeling system
(ROMS) a split-explicit, free-surface, topography-following-coordinate oceanic
model. Ocean Modelling, 9, pp. 347-404.
Thorpe Stephen Austen (1977). Turbulence and mixing in a Scottish Loch Philosophical
Transactions of the Royal Society of London. Series A, Mathematical and Physical
Ushijima, Y., Yoshikawa, Y (2020). Mixed layer deepening due to wind-induced
shear-driven turbulence and scaling of the deepening rate in the stratified ocean. Ocean
Dynamics 70, 505–512. https://doi.org/10.1007/s10236-020-01344-w.
Vialard, J., G. Foltz, M. McPhaden, J.-P. Duvel, and C. de Boyer Montegut, (2008).
Strong Indian Ocean sea surface temperature signals associated with the
Madden-Julian oscillation in late 2007 and early 2008. Geophys. Res. Lett.,35, L19608,
Vialard, J., K. Drushka, H. Bellenger, M. Lengaigne, S. Pous, and J. P. Duvel, (2013)
Understanding Madden-Julian-induced sea surface temperature variations in the
north western Australian Basin. Climate Dyn., 41, 3203–3218,
Wheeler, M. C. and H. H. Hendon, (2004). An all-season real-time multivariate MJO
index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132,
Wheeler, M. C., and H. H. Hendon, (2004). An all-season real-time multivariate MJO
index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132,
Wyrtki, K. (1973) Physical Oceanography of the Indian Ocean. In: B. Zeitzschel, and