Figure 2. (a) Correlation between DMI and surface chlorophyll
anomalies. The black solid and dashed square indicates the southeastern
IO (SEIO) and western IO (WIO) region respectively, used to define the
DMI. (b) Correlation between SWI chlorophyll index and surface
chlorophyll anomalies, and (c) correlation between WS chlorophyll index
and surface chlorophyll anomalies. In (b) and (c) the purple solid and
dashed square indicates the SWI and WS regions used to define the
biological dipole index (BDI). In each plot significant regions at the
95% confidence interval are marked by contours.
To explore the characteristics of IOD and BDI, we further examined the
amplitude and phase locking (Fig. 3). As shown in Fig. 3, both in the
observations and GFDL-ESM4, IOD and BDI show a dominant seasonal
dependency with a peak phase in autumn. In addition, consistent with
previous studies IOD peaks in October in the observations (Li et
al 2003, Saji et al 1999), while the BDI shows an early peak
(September, Fig. 3a). On the other hand, although the BDI peak month in
GFDL-ESM4 is consistent with observations, IOD in the GFDL-ESM4 shows an
early peak compared to the observations (Fig. 3c). However, apart from
the differences in the peak month, both observations and model show the
strong phase locking of IOD and BDI in the boreal autumn.
We further examined the relationship between BDI and IOD during
September to October (Fig. 3b). The months of September and October have
been chosen as the peak months of the two indices. The results clearly
show that there is a strong and significant correlation between BDI and
IOD amplitudes during autumn. In agreement with the observations,
GFDL-ESM4 also shows a strong and significant correlation (-0.85, Fig.
3d). We also examined the correlation between BDMI (defined according to
Shi and Wang 2022) and IOD during autumn and found that the correlation
(r = -0.62) is lower compared to that of BDI (Fig. S5). Also, the
previous BDMI does not capture chlorophyll variability during extreme
events because the region used to define the index does not reflect well
the changes in chlorophyll in response to IOD. For example, the extreme
negative IOD in 2016 is not apparent in the BDMI (BDMI=0.01 for
September 2016, Fig. S5), but the event is well represented in the BDI
(BDI=0.86 for September 2016, Fig. 3c). Therefore, compared to the BDMI
in previous studies, the BDI can well represent the IOD-induced
responses in chlorophyll. Thus, we demonstrate the presence of the
biological dipole pattern in the tropical IO and propose a new
definition (BDI) that can actively capture the variability of
chlorophyll in response to IOD.