Dynamics of seasonal and interannual variability of the ocean bottom pressure in the Southern Ocean
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Abstract: Seasonal and interannual variability of ocean bottom pressure (OBP) in the Southern Ocean was investigated using Gravity Recovery and Climate Experiment (GRACE) data and a Pressure Coordinate Ocean Model (PCOM) based on mass conservation. By comparing OBP, steric sea level, and sea level, it is found that at high latitudes the OBP variability dominates the sea level variability at seasonal-to-decadal time scales. The diagnostic OBP based on barotropic vorticity equation has a good correlation with the observations, indicating that wind forcing plays an important role in the variability of the OBP in the Southern Ocean. The unique interannual patterns of OBP in the Southern Ocean are closely associated with El Niño-Southern Oscillation (ENSO) and Southern Annular Mode (SAM). Regression analysis indicates that ENSO and SAM influence the OBP through altering the Ekman transport driven by surface wind. The leading pattern of OBP from PCOM are very similar to observations. Sensitive experiments of PCOM show that surface wind forcing explains the observed OBP variability quite well, confirming the importance of wind forcing and related oceanic processes. In the eastern South Pacific, the averaged OBP shows a decrease (increase) trend before (after) 2011, reflecting the reverse trend in westerly wind. In the South Indo-Atlantic Ocean, the averaged OBP has a weak increase trend during 2003–2016.
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Key words:
- ocean bottom pressure /
- Southern Ocean /
- interannual variability /
- PCOM
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Figure 1. Seasonal variability of AVISO SLA (top, a), steric sea level (middle, b), and GARCE OBP (bottom, c) in the Southern Ocean for the period of 2004–2016 (color shading, in unit of cm). From left to right, each column represents austral summer (DJF, December, January and February), autumn (MAM, March, April and May), winter (JJA, June, July and August), and spring (SON, September, October and November), respectively. The vectors in c represent Ekman transport anomaly (in unit of 104 m3/(s·(o)) calculated from ERA-interim. Climatological annual mean has been removed.
Figure 2. Ratio of steric sea level to sea level anomaly (a), and ratio of ocean bottom pressure to sea level anomaly (b).
Figure 3. Seasonal variability of OBP (in unit of cm) obtained from PCOM runs: a. in control run (Exp. 1), b. without air pressure forcing (Exp. 2), c. without wind forcing (Exp. 3) averaged in austral summer (DJF, December, January and February; first column), autumn (MAM, March, April and May; second column), winter (JJA, June, July and August; third column), and spring (SON, September, October and November; fourth column) in the Southern Ocean from 2004 to 2016. Climatological annual mean has been removed.
Figure 4. Time series of GRACE OBP anomaly (solid blue lines), SLA (solid black line), steric sea level anomaly (solid gray line) averaged in the South Pacific (40°–60°S, 150°–90°W) (a) and in the South Indo-Atlantic Ocean (40°–60°S, 60°W–120°E) (b) from 2004 to 2016. The anomalies are calculated by subtracting climatological annual cycle. The linear trends of GRACE OBP are displayed as blue dashed lines. In a, R12 is the correlation coefficient between South Pacific SLA and South Pacific steric sea level, and R13 is the correlation coefficient between South Pacific SLA and South Pacific steric GRACE OBP. In b, R12 is the correlation coefficient between South Indo-Atlantic SLA and South Indo-Atlantic steric sea level, and R13 is the correlation coefficient between South Indo-Atlantic SLA and South Indo-Atlantic steric GRACE OBP.
Figure 5. Time series of GRACE OBP anomaly (black lines), OBP anomaly reconstructed from wind forcing (pink lines) and topographic (topo) effect (blue lines) and sum of two terms (gray lines) averaged in the eastern South Pacific (40°–60°S, 150°–80°W) (a), the South Atlantic (40°–60°S, 60°–0°W) (b) , and the South Indian Ocean (40°–60°S, 30°–120°E) (c) from 2003 to 2016. The blue dashed lines are the trend of the GRACE OBP time series. The unit of the y-axis is cm. The anomalies are calculated by subtracting climatological annual cycle. In a, R14 is the correlation coefficient between South Pacific wind curl and South Pacific GRACE, R24 is the correlation coefficient between South Pacific topo and South Pacific GRACE, and R34 is the correlation coefficient between South Pacific wind curl+topo and South Pacific GRACE. In b, R14 is the correlation coefficient between South Atlantic wind curl and South Atlantic GRACE, R24 is the correlation coefficient between South Atlantic topo and South Atlantic GRACE, and R34 is the correlation coefficient between South Atlantic wind curl+topo and South Atlantic GRACE. In c, R14 is the correlation coefficient between South Indian wind curl and South Indian GRACE, R24 is the correlation coefficient between South Indian topo and South Indian GRACE, and R34 is the correlation coefficient between South Indian wind curl+topo and South Indian GRACE.
Figure 6. The spatial structures of the first EOF mode (a) and the second EOF mode (b) of the GRACE OBP (shade; cm) in the South Pacific Ocean from 2003 to 2016, and the spatial structures of the first EOF mode (c) and the second EOF mode (d) of the PCOM OBP (shade; cm) in the South Pacific Ocean from 2003 to 2016, and the rincipal component (PC) time series of the first EOF mode (e) and the second EOF mode (f). The green line in f represents the Niño 3.4 index. The pink line in f represents the SAM index. The vectors denote Ekman transport (104 m3/(°)) regressed on to each time series. Monthly climatology has been removed before EOF analysis.
Figure 7. The structures of the first EOF mode (a) and the second EOF mode (b) of the GRACE OBP (shade; cm) and the spatial structures of the first EOF mode (c) and the second EOF mode (d) of the PCOM OBP (shade) in the South Indo-Atlantic Ocean from 2003 to 2016, and the principal component (PC) time series of the first EOF mode (e) and the second EOF mode (f). The pink lines in e and f represent the SAM index. The vectors denote Ekman transport (m3/(°)) regressed on to each time series. Monthly climatology has been removed before EOF analysis.
Figure 8. GRACE OBP anomaly (shading) and Ekman transport anomaly (vectors) regressed onto Niño 3.4 index (a) and SAM index (b) and PCOM OBP anomaly (shading) Ekman transport anomaly (vectors) regressed onto Niño 3.4 index (c) and SAM index (d) from 2003 to 2016. Ekman transport anomaly data are from ERA-Interim.
Figure 9. SST (unit: °C) pattern regressed onto PC1 time series (upper panels) and SLP (unit: hPa) pattern regressed onto PC2 time series (middle panels) in the South Pacific Ocean, and SLP pattern regressed onto PC1 time series of OBP anomaly in the South Indo-Atlantic Ocean (lower panels); OBP based on GRACE (left panels) and PCOM (right panels). The anomalies are calculated by subtracting climatological annual cycle.
Figure 10. Standard deviation of interannual GRACE OBP (in unit of cm) in the Southern Ocean (a), standard deviation of interannual OBP in the Southern Ocean from control run of PCOM (Exp. 1) (b), standard deviation of interannual OBP in the Southern Ocean from control run of PCOM (Exp. 2) (c), and standard deviation of interannual OBP in the Southern Ocean from control run of PCOM (Exp. 3) (d) from 2003 to 2016.
Figure 11. Trends of OBP (color shading, mm/a) and Ekman transport (vector, m3/(°)) based on Grace (left panels) and PCOM (right panels). a, b, d and e. For the two periods of 2003–2010 (a, d) and 2011–2016 (b, e) in the South Pacific Ocean; c and f. for the period of 2003–2016 in the South Indo-Atlantic Ocean.
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