The Impact of the Indian Ocean Basin Mode on Antarctic Sea Ice Concentration in Interannual Time Scales

Yu, Lejiang; Zhong, Sharon; Vihma, Timo; Sui, Cuijuan; Sun, Bо

doi:10.1029/2022gl097745

Cited by 11 publications

(10 citation statements)

References 52 publications

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“…For instance, in austral spring, the sea ice anomalies related to the IOSD show an opposite trend compared to those related to the IOD in certain regions of the western Ross, Weddell and Dumont d'Urville Seas (Nuncio & Yuan, 2015). Similarly, the IOSD‐related sea ice anomalies exhibit opposite trends to the IOBM‐related anomalies in the northern Weddell Sea during austral autumn, as well as in the Weddell, Bellingshausen, northern Ross and Dumont d'Urville Seas in austral spring (Yu et al, 2022). On the other hand, negative sea ice anomalies corresponding to the SASD index in the eastern Ross Sea during austral autumn have also been observed in relation to the AMM (Ren et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

“…Nuncio and Yuan (2015) showed that the Antarctic sea ice cover is related to the Indian Ocean Dipole (IOD) (Saji et al, 1999) characterized by departures of the SST in the opposite directions from normal in the western and eastern Indian Ocean, and that the relationship is modulated by ENSO. Yu et al (2022) established a teleconnection between the Antarctic sea ice and the Indian Ocean Basin mode (IOBM) (Klein et al, 1999), the dominant mode of SST variability representing basin‐wide warming or cooling, and the linkage is especially strong in austral autumn and spring. The SST anomalies in the tropical Atlantic affect the strength of the Amundsen Sea Low (ASL) and sea ice variability in Bellingshausen and eastern Ross sea in winter (Li et al, 2014) and spring (Simpkins et al, 2014), though the SST anomalies usually present an interdecadal variability.…”

Section: Introductionmentioning

confidence: 99%

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Antarctic sea ice variability linked to three dipole modes of subtropical sea surface temperature in the Southern Hemisphere

Zhong

Sun

2023

Intl Journal of Climatology

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Based on statistical analyses of gridded data over the past four decades (1979–2020), we examined the teleconnection between the variability of the Antarctic sea ice and the leading modes of subtropical sea surface temperature (SST) variability known as the Indian Ocean subtropical dipole (IOSD), the South Atlantic subtropical dipole (SASD) and the South Pacific subtropical dipole (SPSD). We show that the pattern and strength of the teleconnection differ with the SST modes. For each mode, while the regional distributions of significant Antarctic sea ice anomalies are broadly similar throughout the year, the areal extent and the magnitudes of the anomalies display a strong seasonality. Larger areas and magnitudes of significant sea ice anomalies occur in austral winter for the SASD, autumn and spring for the SPSD and non‐summer seasons for the IOSD. We demonstrate that the spatial and seasonal variations of the sea ice anomalies associated with each of the three subtropical SST variability modes are largely consistent with the patterns of the anomalous temperature advection and sea ice transport by the anomalous atmospheric circulations induced by planetary wavetrains that are triggered by anomalous convective activities over different regions of subtropical oceans. These relationships between subtropical SST modes and Antarctic sea ice may serve as a valuable reference for predicting seasonal to interannual scale variations of Antarctic sea ice concentrations across each austral season.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Antarctic sea ice variability linked to three dipole modes of subtropical sea surface temperature in the Southern Hemisphere

Zhong

Sun

2023

Intl Journal of Climatology

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“…Only during the austral autumn does the IOBM index exhibit a noteworthy correlation with the ANM index (0.33, p < 0.05). Interestingly, the spatial patterns of Antarctic sea ice anomalies align in the Ross Sea, while opposing patterns emerge in the Atlantic sector (Yu et al 2022b).…”

Section: Effects Of Other Sst Modes On Antarctic Sea Icementioning

confidence: 97%

“…The two leading SST interannual variability modes in the tropical Indian Ocean, the Indian Ocean Basin mode (IOBM) and the Indian Ocean Dipole (IOD) mode (Chambers et al 1999, Klein et al 1999, Saji et al 1999, have also been linked to the Antarctic sea ice anomalies. Yu et al (2022b) have shown that IOBM is particularly influential in austral autumn and spring, while Nuncio and Yuan (2015) and Yu et al (2022b) have found that IOD can significantly influence sea ice in the region west of the Ross Sea. These teleconnections can be modulated by ENSO (Yu et al 2022b).…”

Section: Introductionmentioning

confidence: 99%

“…Yu et al (2022b) have shown that IOBM is particularly influential in austral autumn and spring, while Nuncio and Yuan (2015) and Yu et al (2022b) have found that IOD can significantly influence sea ice in the region west of the Ross Sea. These teleconnections can be modulated by ENSO (Yu et al 2022b). The large-scale circulation patterns typically set boundary conditions for the occurrence and tracks of synoptic-scale cyclones (Uotila et al 2013), which then generate the direct dynamic and thermodynamic forcing on sea ice (Uotila et al 2014).…”

Section: Introductionmentioning

confidence: 99%

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The seasonal Antarctic sea ice concentration anomalies related to the Atlantic Niño index

Yu,

Zhong,

Vihma

et al. 2023

Environ. Res.: Climate

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Antarctic sea ice concentration anomalies (ASICA) have been found to be linked to sea surface temperature anomalies (SSTA) in tropical oceans. However, it is not clear whether and how ASICA is linked to the Atlantic Niño mode (ANM). This study demonstrates a significant relationship between ASICA and ANM. The relationships vary by season, with a peak in austral winter and a secondary one in spring. Significant sea ice anomalies associated with a positive phase of ANM are mostly negative in austral winter and spring, and mostly positive in austral summer and autumn. This teleconnection is established by atmospheric wavetrains that are excited over the tropical southwestern Pacific and Indian Oceans and the southern Atlantic Oceans and propagate over the Southern Ocean. These wavtrains induce anomalous near-surface circulations, which generate dynamic and thermodynamic forcing on sea ice, resulting in the observed ASICA patterns. The absence of ENSO weakens the connection.

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Near‐surface wind variability in Prydz Bay and Amery Ice Shelf region, East Antarctica: A four‐decade SOM analysis

Yu,

Zhong,

Xiao

et al. 2024

Intl Journal of Climatology

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Near‐surface wind fields in the Prydz Bay and Amery Ice Shelf region of East Antarctica play a crucial role in the formation and variability of Antarctic Bottom Water, a cold, dense water mass that sinks and spreads across the deep ocean basins influencing ocean circulation and modulating earth's climate system. This study investigates the primary modes of variability of these wind fields using the self‐organizing map (SOM) method and data from the latest version of the European Centre for Medium‐Range Weather Forecasts (ECMWF) ReAnalyses (ERA5), spanning four decades from 1979 to 2020. While the wind field climatology, characterized by small seasonal variation, is dominated by katabatic and large‐scale forcing, the spatial patterns of the primary variability modes are mainly influenced by synoptic system activities. The overall trend in annual wind speed anomalies is positive across the study region, with the exception of the southwestern part and central Prydz Bay. However, significant trends are observed in only two out of nine SOM nodes (nodes 4 and 9), which collectively explain less than 30% of the averaged trends over the region. The interannual variability in the seasonal occurrences of certain nodes is linked to several well‐known climate modes, including the El Niño–Southern Oscillation, the Southern Annular Mode and Zonal Wavenumber 3. Our results provide a reference for forecasting the occurrence frequency of specific patterns, which could help mitigate the impact of extreme wind events through improved forecasting.

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The Impact of the Indian Ocean Basin Mode on Antarctic Sea Ice Concentration in Interannual Time Scales

Cited by 11 publications

References 52 publications

Antarctic sea ice variability linked to three dipole modes of subtropical sea surface temperature in the Southern Hemisphere

Antarctic sea ice variability linked to three dipole modes of subtropical sea surface temperature in the Southern Hemisphere

The seasonal Antarctic sea ice concentration anomalies related to the Atlantic Niño index

Near‐surface wind variability in Prydz Bay and Amery Ice Shelf region, East Antarctica: A four‐decade SOM analysis

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