The South Atlantic–South Indian Ocean Pattern: a Zonally Oriented Teleconnection along the Southern Hemisphere Westerly Jet in Austral Summer

Lin, Zongkai

doi:10.3390/atmos10050259

Cited by 15 publications

(10 citation statements)

References 57 publications

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“…At the same time, SST response to the atmosphere is found to be of a wavenumber-3 type in a global view 16 , 25 , 26 . Recently, it is reported that tropical Rossby waves have the potential to generate a zonal W4 pattern in the southern Indo-Atlantic Ocean basin that affects precipitation over Australia 27 .…”

Section: Introductionmentioning

confidence: 99%

Global wave number-4 pattern in the southern subtropical sea surface temperature

Senapati

Dash

Behera

2021

Sci Rep

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Exploratory analysis using empirical orthogonal function revealed the presence of a stationary zonal wavenumber-4 (W4) pattern in the sea surface temperature (SST) anomaly in the southern subtropics (20°S–55°S). The signal over the Southern subtropics is seasonally phase-locked to the austral summer and persists up to mid-autumn. Thermodynamic coupling of atmosphere and the upper ocean helps in generating the W4 pattern, which later terminates due to the breaking of that coupled feedback. It is found that the presence of anomalous SST due to W4 mode in the surrounding of Australia affects the rainfall over the continent by modulating the local atmospheric circulation. During positive phase of W4 event, the presence of cold SST anomaly over the south-eastern and -western side of Australia creates an anomalous divergence circulation. This favours the moisture transport towards south-eastern Australia, resulting in more rainfall in February. The scenario reverses in case of a negative W4 event. There is also a difference of one month between the occurrence of positive and negative W4 peaks. This asymmetry seems to be responsible for the weak SST signal to the South of Australia. Correlation analysis suggests that the W4 pattern in SST is independent of other natural variabilities such as Southern Annular Mode, and Indian Ocean Dipole as well as a rather weak relationship with El Niño/Southern Oscillation.

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Section: Introductionmentioning

confidence: 99%

Global wave number-4 pattern in the southern subtropical sea surface temperature

Senapati

Dash

Behera

2021

Sci Rep

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“…The correlations between EP El Niño events, represented by a positive EP index, and AUMR are weak and insignificant over northern Australia (Figure 5a, red circles). The large spread of precipitation anomalies associated with the positive EP index suggests that other factors are more influential on precipitation over northern Australia, for example, local SSTa, as observed in austral spring (Van Rensch et al, 2015, 2019. Nonlinearity in the relationship is linked to large-scale shifts in rainfall patterns, and a weak decrease in AUMR during El Niño events (Chung & Power, 2017).…”

Section: Eastern Pacific El Niñomentioning

confidence: 97%

“…It is associated with ascending motion and a negative surface temperature anomaly in the eastern Indian Ocean as well as convergence in the lower troposphere and strengthened westerly winds towards NW Australia (Lin, 2019). It has been suggested that the pattern may be caused by internal, interannual atmospheric variability that is related to zonal shifts of the South Atlantic Convergence Zone and is only weakly related to tropical Atlantic SSTs (Lin, 2019), highlighting the uncertainty about it. Further research is required to clarify the causes of the pattern, its associated variability, long‐term changes and impacts on AUMR.…”

Section: Aumr: Decadal Variability and Trendsmentioning

confidence: 99%

Variability and long‐term change in Australian monsoon rainfall: A review

Heidemann

Cowan

Henley

et al. 2023

WIREs Climate Change

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The Australian monsoon delivers seasonal rain across a vast area of the continent stretching from the far northern tropics to the semi-arid regions. This article provides a review of advances in Australian monsoon rainfall (AUMR) research and a supporting analysis of AUMR variability, observed trends, and future projections. AUMR displays a high degree of interannual variability with a standard deviation of approximately 34% of the mean. AUMR variability is mostly driven by the El Niño-Southern Oscillation (ENSO), although sea surface temperature anomalies in the tropical Indian Ocean and north of Australia also play a role. Decadal AUMR variability is strongly linked to the Interdecadal Pacific Oscillation (IPO), partially through the IPO's impact on the strength and position of the Pacific Walker Circulation and the South Pacific Convergence Zone. AUMR exhibits a century-long positive trend, which is large (approximately 20 mm per decade) and statistically significant over northwest Australia. The cause of the observed trend is still debated. Future changes in AUMR over the next century remain uncertain due to low climate model agreement on the sign of change. Recommendations to improve the understanding of AUMR and confidence in AUMR projections are provided. This includes improving the representation of atmospheric convective processes in models, further explaining the mechanisms responsible for AUMR variability and change. Clarifying the mechanisms of AUMR variability and

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“…The second mode reflects a distinct wavenumber-4 pattern in the Southern Ocean (e.g., Wang and Dommenget 2016;Lin 2019), with high amplitude in the Atlantic sector. As Fig.…”

Section: Spatiotemporal Variability Modes Of Q Netmentioning

confidence: 99%

Optimizing Mooring Placement to Constrain Southern Ocean Air–Sea Fluxes

Wei

Gille

Mazloff

et al. 2020

Journal of Atmospheric and Oceanic Technology

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Proposals from multiple nations to deploy air–sea flux moorings in the Southern Ocean have raised the question of how to optimize the placement of these moorings in order to maximize their utility, both as contributors to the network of observations assimilated in numerical weather prediction and also as a means to study a broad range of processes driving air–sea fluxes. This study, developed as a contribution to the Southern Ocean Observing System (SOOS), proposes criteria that can be used to determine mooring siting to obtain best estimates of net air–sea heat flux (Qnet). Flux moorings are envisioned as one component of a multiplatform observing system, providing valuable in situ point time series measurements to be used alongside satellite data and observations from autonomous platforms and ships. Assimilating models (e.g., numerical weather prediction and reanalysis products) then offer the ability to synthesize the observing system and map properties between observations. This paper develops a framework for designing mooring array configurations to maximize the independence and utility of observations. As a test case, within the meridional band from 35° to 65°S we select eight mooring sites optimized to explain the largest fraction of the total variance (and thus to ensure the least variance of residual components) in the area south of 20°S. Results yield different optimal mooring sites for low-frequency interannual heat fluxes compared with higher-frequency subseasonal fluxes. With eight moorings, we could explain a maximum of 24.6% of high-frequency Qnet variability or 44.7% of low-frequency Qnet variability.

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The South Atlantic–South Indian Ocean Pattern: a Zonally Oriented Teleconnection along the Southern Hemisphere Westerly Jet in Austral Summer

Cited by 15 publications

References 57 publications

Global wave number-4 pattern in the southern subtropical sea surface temperature

Global wave number-4 pattern in the southern subtropical sea surface temperature

Variability and long‐term change in Australian monsoon rainfall: A review

Optimizing Mooring Placement to Constrain Southern Ocean Air–Sea Fluxes

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