Research ArticleOCEANOGRAPHY

Unprecedented reduction and quick recovery of the South Indian Ocean heat content and sea level in 2014–2018

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Science Advances  04 Sep 2020:
Vol. 6, no. 36, eabc1151
DOI: 10.1126/sciadv.abc1151
  • Fig. 1 Schematic showing the dynamic processes affecting the subtropical SIO heat content and sea level.

    Color shows the mean dynamic topography (MDT) in the horizontal plane and temperature climatology in the vertical planes. The atmospheric circulation in the SIO is dominated by southeasterly trade winds. The general ocean circulation consists of the Indonesian Throughflow (ITF) that feeds the South Equatorial Current (SEC) and the Leeuwin Current (LC), and the South Indian Counter Current (SICC). ENSO affects the SIO heat content via the ocean route (ITF) and atmospheric route (atmospheric bridge due to Walker Circulation). The ITF volume and heat transports into the eastern SIO (ESIO) increase during La Niña conditions (stronger trade winds in the Pacific) and decrease during El Niño conditions (weaker trade winds in the Pacific). Besides advection, signals generated in the Pacific reach the coast of West Australia as coastally trapped waves. Then, these signals propagate toward the western SIO (WSIO) as eddies and Rossby waves. Local wind stress curl can modify the waves radiated from the eastern boundary and/or generate other waves.

  • Fig. 2 Sea level changes, ENSO, and IOD.

    (A) Time series of (color shading) the standardized (divided by standard deviation, SD) MEI (El Niño/La Niña conditions are shown by blue/pink shading) and (blue curve) IOD index; (black curve) sea-level anomaly (SLA) from altimetry, and (red curve) thermosteric SLA from Argo data averaged over 55°E to 115°E and 10°S to 30°S. The time series are low-pass filtered with a cutoff period of 1 year. (B) Dynamic sea-level trends in 2004–2013 (global mean sea level is subtracted). During this time, the SIO was characterized as one of the major heat accumulators among the oceanic basins. (C to E) SLA relative to the record mean value and averaged in 2014, 2016, and 2018, respectively. The approximate location of the SEC is shown by red dashed arrows. Blue contours show the bottom topography for 2000, 4000, and 6000 m.

  • Fig. 3 Sea-level variability and Rossby waves.

    (A) Hovmöller (longitude-time) diagram of the low-pass–filtered SLA with a cutoff period of 1 year averaged between 10°S and 30°S. (B and C) Low-pass–filtered MEI (shaded area) and sea level components averaged over (B) 55°E to 90°E and 10°S to 30°S (WSIO) and over (C) 90°E to 115°E and 10°S to 30°S (ESIO). The sea level components include (black) SLA from satellite altimetry and (blue, red, green) steric (SSL), thermosteric (TSL), and halosteric (HSL) SLAs, respectively, computed from Argo data.

  • Fig. 4 Wind forcing over the Indian Ocean.

    (A and B) Regression of Ekman pumping (color shading) and 10-m winds (arrows) on (A) MEI and (B) IOD index, expressed in meter per month per 1 SD change of the respective index. (C to F) Ekman pumping and 10-m wind speed averaged for (C) 1997–1998 El Niño, (D) 1998–2001 La Niña, (E) 2014–2016 El Niño, and (F) 2017–2018 La Niña. Ekman pumping anomalies between 5°S and 5°N are blanked because f→0 toward the equator. Negative (positive) Ekman pumping anomalies associated with the upper-ocean warming (cooling) are shown by red (blue) color. Magenta rectangles show the area (55°E to 110°E and 10°S to 30°S) used to plot a longitude-time diagram of Ekman pumping anomaly in fig. S1A.

  • Fig. 5 Upper-ocean temperature changes.

    Profiles of the low-pass–filtered potential temperature, θ, averaged between 55°E and 110°E: (A) in 2016 (θ2016; blue contour), in 2014 (θ2014; dotted contour), and their difference, θ2016 − θ2014 (color); (B) in 2018 (θ2018; red contour), in 2016 (θ2016; dotted contour), and their difference, θ2018 − θ2016 (color); and (C) θ2016 − θ2014 (blue line) and θ2018 − θ2016 (red line) differences averaged between 55°E to 110°E and 10°S to 30°S.

  • Fig. 6 Observed and modeled sea-level variability in the SIO.

    Hovmöller diagrams of (A) the observed, low-pass–filtered (with a cutoff period of 1 year), and detrended SLA averaged between 10°S and 30°S; (B) the modeled SLA using both the eastern boundary and the local wind stress curl forcing; (C) the modeled SLA obtained using the eastern boundary forcing (first term of Eq. 4) only, and (D) the modeled SLA obtained using the local wind stress curl forcing (second term of Eq. 4) only. (E and F) Time series of the observed SLA (black curves) and modeled SLA using the eastern boundary forcing (blue curves), the local wind stress curl forcing (red curves), and both forcing terms (green curves), averaged between (E) 55°E to 90°E and (F) 90°E to 110°E.

Supplementary Materials

  • Supplementary Materials

    Unprecedented reduction and quick recovery of the South Indian Ocean heat content and sea level in 2014–2018

    Denis L. Volkov, Sang-Ki Lee, Arnold L. Gordon, Michael Rudko

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