Nonlinear processes reinforce extreme Indian Ocean Dipole events

Ng, Benjamin; Cai, Wenju; Walsh, Kevin; Santoso, Agus

doi:10.1038/srep11697

Cited by 24 publications

(27 citation statements)

References 30 publications

(60 reference statements)

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“…The heat budget equation employed in this study was similar to Ng et al . [], i.e. :

\frac{\partial T}{\partial t} = - u \frac{\partial T}{\partial x} - v \frac{\partial T}{\partial y} - w \frac{\partial T}{\partial z} + \frac{Q}{ρ_{0} C_{p} H} + Re sidual,

where T and u , v , and w represent the climatological monthly means of potential temperature and zonal, meridional, and vertical ocean current velocities, respectively, Q represents the surface heat flux into the ocean, H is a thickness of the water column, and C p and ρ 0 denote the specific heat of seawater at constant pressure (set to 3994 J kg −1 K −1 ) and a reference density of seawater (set to 1025 kg m −3 ), respectively.…”

Section: Resultsmentioning

confidence: 99%

“…All the terms were averaged over the upper 50 m in this study. The use of a fixed depth of 50 m avoids complications associated with an MME such as variations in the MLD among the models [ Ng et al ., ]. Several studies have estimated the heat budget with consideration of the variation of the MLD [e.g., Kim et al ., ].…”

Section: Resultsmentioning

confidence: 99%

“…The time tendency of the upper 50 m temperature deviation in each model of the MME can be written as follows:

\begin{matrix} \frac{\partial T^{'}}{\partial t} = - true[u_{M} \frac{\partial T^{'}}{\partial x} + v_{M} \frac{\partial T^{'}}{\partial y} + w_{M} \frac{\partial T^{'}}{\partial z} true] - true[u^{'} \frac{\partial T_{M}}{\partial x} + v^{'} \frac{\partial T_{M}}{\partial y} + w^{'} \frac{\partial T_{M}}{\partial z} true] - true[u^{'} \frac{\partial T^{'}}{\partial x} + v^{'} \frac{\partial T^{'}}{\partial y} + w^{'} \frac{\partial T^{'}}{\partial z} true] \\ + \frac{Q^{'}}{ρ_{0} C_{p} H} + Re sidual, \end{matrix}

where subscript M denotes the MME of a quantity and the prime indicates its deviation from the MME. The first bracket represents the advection of temperature deviation by the MME currents, the second bracket is the advection of the MME temperature by the current deviation, and the third bracket is the advection of the temperature deviation by the current deviation, which is called the nonlinear dynamical heating [e.g., Ng et al ., ].…”

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Assessment of western Indian Ocean SST bias of CMIP5 models

et al. 2017

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The western Indian Ocean sea surface temperature (SST) is among the key factors that affect precipitation over India and East Africa. This study examined the western Indian Ocean SST biases among the Coupled Model Intercomparison Project phase 5 (CMIP5) models. It was found that the multimodel ensemble‐mean SST biases over the western equatorial Indian Ocean are warmer than the observations during the summer monsoon season. However, about half the models show positive SST biases, whereas negative ones in the other half. The models with warmer SST biases exhibit a pattern similar to the Indian Ocean Dipole, with stronger equatorial easterly wind biases during fall and a deeper thermocline in the western equatorial Indian Ocean. In the models with cooler SST biases, negative SST biases are observed over the entire tropical Indian Ocean throughout the year and the wind biases over the equatorial Indian Ocean are southeasterly during summer and fall. Heat budget analysis revealed the importance of ocean currents in forming the early summer development of SST biases over the western equatorial Indian Ocean. The formation of SST biases is related to surface current biases induced by the weaker biases of southwesterly monsoon winds and SST biases over the southwestern equatorial Indian Ocean, which are advected by the East African Coastal Currents. On the other hand, almost of all the CMIP5 models show prominent cold SST biases over the northern Arabian Sea during the premonsoon season. The SST biases are induced by excess surface cooling during the winter monsoon season.

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“…The heat budget equation employed in this study was similar to Ng et al . [], i.e. :

\frac{\partial T}{\partial t} = - u \frac{\partial T}{\partial x} - v \frac{\partial T}{\partial y} - w \frac{\partial T}{\partial z} + \frac{Q}{ρ_{0} C_{p} H} + Re sidual,

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…The time tendency of the upper 50 m temperature deviation in each model of the MME can be written as follows:

\begin{matrix} \frac{\partial T^{'}}{\partial t} = - true[u_{M} \frac{\partial T^{'}}{\partial x} + v_{M} \frac{\partial T^{'}}{\partial y} + w_{M} \frac{\partial T^{'}}{\partial z} true] - true[u^{'} \frac{\partial T_{M}}{\partial x} + v^{'} \frac{\partial T_{M}}{\partial y} + w^{'} \frac{\partial T_{M}}{\partial z} true] - true[u^{'} \frac{\partial T^{'}}{\partial x} + v^{'} \frac{\partial T^{'}}{\partial y} + w^{'} \frac{\partial T^{'}}{\partial z} true] \\ + \frac{Q^{'}}{ρ_{0} C_{p} H} + Re sidual, \end{matrix}

Section: Resultsmentioning

confidence: 99%

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Assessment of western Indian Ocean SST bias of CMIP5 models

et al. 2017

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“…More recently the debate has also focused on the implications of global warming for the frequency and amplitude of natural variability oscillations, such as ENSO and IOD. While no consensus view has emerged to date, it is however expected that their amplitude, frequency and teleconnections might change as consequences of global warming (Cai et al, 2015a,b;and Kim et al, 2014;Ng et al, 2015;Coumou and Rahmstorf, 2012).…”

Section: Discussionmentioning

confidence: 99%

“…As pointed out by Cai et al (2015a,b; and Kim et al (2014), while no consensus view has emerged to date, it is however expected that ENSO extremes will increase in amplitude and frequency and ENSO teleconnections will shift eastward, both as consequences of mean climate state changes. A sizable increase in the frequency of extreme positive Indian Ocean Dipole (pIOD) events might also be expected (Ng et al, 2015). See also Coumou and Rahmstorf (2012) on these issues.…”

Section: Introductionmentioning

confidence: 99%

Temperature Anomalies, Radiative Forcing and ENSO

Morana

Sbrana

2017

SSRN Journal

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The paper investigates the linkages between temperature anomalies, radiative forcing and ENSO. By means of a new flexible trend modeling approach, we uncover a nonlinear linkage between radiative forcing and global temperature anomalies. The nonlinear trend closely tracks the low frequency evolution in temperature anomalies, also accounting for the mid-end 1990s level switch, the 1998-2013 "warming hiatus" and the current steepening in trend temperatures. Radiative forcing is also found to account for trend dynamics in the Southern Oscillation Index (SOI), therefore providing support for the view that global warming might affect natural variability oscillations such as ENSO, and therefore enhance their disruptive effects. We also document the feature of time-varying volatility of temperature anomalies and SOI, which is well described by an IGARCH process. By means of a new dynamic conditional correlation model (SP-DCC), we finally document the presence of time-varying conditional correlations relating temperature anomalies across various zones and SOI. The correlation pattern is found to be consistent with the effects of ENSO events in the Tropics and their teleconnections.

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Distinctive characteristics and dynamics of the summer and autumn Indian ocean dipole events

Tao,

Qiu,

Zhong

et al. 2023

Clim Dyn

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The Indian Ocean Dipole (IOD) with worldwide socio-economic impacts has been presented to mature either in boreal summer or autumn, leading to the classi cation of summer IOD and autumn IOD. Investigating the climate dynamics to distinguish between these two types of IOD can improve our understanding and prediction of the surrounding weather and climate. This study demonstrates that the emergence of the summer IOD is mainly attributed to internal air-sea interactions in the western tropical Indian Ocean (WIO), while the autumn IOD is signi cantly related to ENSO development. For the summer IOD, broad-scaled warm sea surface temperature anomalies in the WIO are conducive to the enhancement of convective perturbations. Then local ocean-atmosphere feedback associated with changes in convection and surface heat ux into the upper ocean plays a key role in triggering the summer IOD. For the autumn IOD, strong easterly wind anomalies in the eastern Indian Ocean initiate oceanic Rossby waves and Bjerknes feedback, leading to the formation of both the western and eastern poles. It is recognized that these intensi ed easterly wind anomalies mostly bene t from ENSO variability. The distinctive features and air-sea interactions intrinsic to the summer IOD and the autumn IOD revealed in this study can further contribute to more credible predictive models of diverse IOD events.

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Nonlinear processes reinforce extreme Indian Ocean Dipole events

Cited by 24 publications

References 30 publications

Assessment of western Indian Ocean SST bias of CMIP5 models

Assessment of western Indian Ocean SST bias of CMIP5 models

Temperature Anomalies, Radiative Forcing and ENSO

Distinctive characteristics and dynamics of the summer and autumn Indian ocean dipole events

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