RESEARCH

TROPICS

El-Nino Southern Oscillation(ENSO)

The El Nino-Southern Oscillation (ENSO) isn’t a linear system but a nonlinear system.
Linear properties such as amplitude, frequency can be explained by simple linear recharge oscillator model (Linear ROM). However, nonlinear properties such as
skewness, transition asymmetry cannot be explained at all. Here, we developed nonlinear ROM which includes nonlinear dynamical heating process (NDH) known
as driver of amplitude asymmetry of ENSO. Using a Fokker-Planck Equation (FPE), we directly calculated probability function of a nonlinear and linear ROMs.
The results clearly show that nonlinear ROM has following properties : 1. skewed probability distribution 2. warm/cold duration asymmetry 3. linear properties are
(amplitude, frequency) preserved.

To examine how nonlinear ROM portrays nonlinear characteristics well in practical sense, we assessed nonlinear properties of ENSO in CMIP5 models through
nonlinear ROM. Nonlinear parameters in ROM which indicate strength of nonlinear dynamical heating (NDH) is estimated by simple empirical method.
High correlation (r=0.8) between model skewness and nonlinear ROM’s skewness which is calculated by estimated parameters reveals that nonlinear ROM is
powerful tool for assessing nonlinear features of ENSO. Furthermore, we expect that nonlinear ROM provides insight for physical origin of intermodel-diversity in
ENSO skewness among CMIP5 Models.

(An et al., 2020)

Indian Ocean Dipole(IOD)

The Indian Ocean Dipole (IOD) is a prominent interannual climate variability in the tropical Indian ocean (TIO). The IOD is featured as the zonal sea surface
temperature (SST) dipole between tropical western and southeastern TIO. During the positive phase, the southeastern TIO sea surface temperature (SST) anomaly
(SSTA) becomes colder, whereas the western TIO SST becomes warmer than normal. The opposite pattern is observed during the negative phase (Ashok et al.,
2001: Black et al. 2003; Clark et al., 2003; Lareef et al. 2003; Saji and Yamagata, 2003; Cai et al., 2014; Luo et al., 2015).

Since the IOD has large climatic and socio–economic impacts not only in neighboring countries but also in remote regions, an in-depth understanding of the IOD
dynamics is critically important.

The development mechanism of the IOD can be largely understood by categorizing its contributors into three parts: the internal feedback process, external forcing,
and stochastic forcing. Internal feedback processes include Bjerknes feedback (involving winds, thermocline tilt, and SST) (Bjerknes. 1969; Saji et al. 1999),
wind–evaporation–SST feedback (Xie and Philander. 1994), and cloud–radiation–SST feedback (Li et al. 2003; Fischer et al. 2005), which directly contribute to IOD
development. In addition to the internal feedback process, the IOD is influenced by outside of the tropical Indian Ocean, such as the El Niño–Southern Oscillation
(ENSO), subtropical IOD (Zhang et al. 2020), and the North Tropical Atlantic (Zhang et al. 2022).

Among them, ENSO is known to be the most influential on the IOD, as it not only initiates the IOD but also influences both its amplitude and spatiotemporal
characteristics (An. 2004; Fischer et al. 2005; Yang et al. 2015; Steucker et al. 2017). Likewise, stochastic forcing associated with the Madden–Julian Oscillation and
weather noise can also independently initiate IOD events and modify IOD growth (Steucker et al. 2017; McKenna et al. 2020; An et al. 2022; An et al. 2023).

Despite numerous prior studies on IOD dynamics, a comprehensive understanding of IOD remains elusive due to its intricate nature. In our laboratory, we are
researching various aspects of IOD to gain a better understanding of its complexities.

Meanwhile, as global warming progresses, IOD characteristics are changing as rapid and unique warming patterns appear in the Indian Ocean region.
A positive IOD – like warming pattern is also projected in most climate model simulations of global warming (Zheng et al. 2010, and Cai et al. 2013). Because of the
significant impacts of IOD, understanding how the IOD responds to anthropogenic climate change is one of the most critical issues in climate science.