Xiaoqin Xiong, Xuhua Cheng, Niansen Ou, Tao Feng, Jianhuang Qin, Xiao Chen, Rui Xin Huang. Dynamics of seasonal and interannual variability of the ocean bottom pressure in the Southern Ocean[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1878-z
Citation:
Xiaoqin Xiong, Xuhua Cheng, Niansen Ou, Tao Feng, Jianhuang Qin, Xiao Chen, Rui Xin Huang. Dynamics of seasonal and interannual variability of the ocean bottom pressure in the Southern Ocean[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1878-z
Xiaoqin Xiong, Xuhua Cheng, Niansen Ou, Tao Feng, Jianhuang Qin, Xiao Chen, Rui Xin Huang. Dynamics of seasonal and interannual variability of the ocean bottom pressure in the Southern Ocean[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1878-z
Citation:
Xiaoqin Xiong, Xuhua Cheng, Niansen Ou, Tao Feng, Jianhuang Qin, Xiao Chen, Rui Xin Huang. Dynamics of seasonal and interannual variability of the ocean bottom pressure in the Southern Ocean[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1878-z
College of Oceanography, Hohai University, Nanjing 210024, China
2.
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519080, China
3.
College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang 524088, China
4.
Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA
Funds:
The National Key R&D Program of China under contract No. 2018YFA0605703; the National Natural Science Foundation of China under contract Nos 41876002 and 41876224.
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.
Figure 1. Seasonal variability of 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, Decamber, January and February), autumn (MAM, March, April and May), winter (JJA, June, July, August), and spring (SON, September, October and Norember), respectively. The vectors in c represent Ekman transport anomaly (in unit of 104 m3/(s·degree)) calculated from ERA-interim. Climatological annual mean has been removed.
Figure 2. Ratio of steric sea level to sea level (a), and ratio of ocean bottom pressure to sea level (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 (first column), autumn (second column), winter (third column), and spring (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 (150°–90°W, 40°–60°S) (a) and in the South Indo-Atlantic Ocean (60°W–120°E, 40°–60°S) (b) from 2004 to 2016. The anomalies are calculated by subtracting climatological annual cycle.
Figure 5. Time series of GRACE OBP anomaly (black lines), OBP anomaly reconstructed from wind forcing (pink lines) and topographic effect (blue lines) and sum of two terms (gray lines) averaged in the eastern South Pacific (150°–80°W, 40°–60°S) (a), the South Atlantic (60°–0°W, 40°–60°S) (b) , and the South Indian Ocean (30°–120°E, 40°–60°S) (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.
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. (c) and (d) the same as (a) and (b), but for PCOM OBP. Time series of e the first EOF mode and f the second EOF mode. The green line in f represents the Niño3.4 index. The pink line in f represents the SAM index. The vectors denote Ekman transport (104 m3/s·degree) regressed on to each time series. Monthly climatology has been removed before EOF analysis.
Figure 7. The spatial structures of the first EOF mode (a) and the second EOF mode (b) of the GRACE OBP (shade, cm) in the South Indo-Atlantic Ocean from 2003 to 2016. (c) and (d) the same as (a) and (b), but for PCOM OBP. Time series of e the first EOF mode and f the second EOF mode. The pink lines in e and f represent the SAM index. The vectors denote Ekman transport (m3/(s·degree)) regressed on to each time series. Monthly climatology has been removed before EOF analysis.
Figure 8. GRACE OBP anomaly (color shading, cm) and Ekman transport anomaly (vectors is unit of m3/(s·degree), data from ERA-Interim) regressed onto Niño3.4 index (a) and SAM index (b) from 2003 to 2016. (c) and (d) the same as (a) and (b), but for PCOM OBP.
Figure 9. (a) SST (unit: °C) pattern regressed onto PC1 time series (upper panels) and SLP (unit: mbar) 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. (a) Standard deviation of interannual GRACE OBP (in unit of cm) in the Southern Ocean from 2003 to 2016. (b) standard deviation of interannual OBP in the Southern Ocean from control run of PCOM (Exp. 1) from 2003 to 2016. (c) and (d) are the same as (b), but for Exp.2 and Exp.3.
Figure 11. Trends of OBP (color shading, mm/a) and Ekman transport (vector, m3/(s·degree·a)) based on Grace (left panel) and PCOM (right panels). For the two periods is 2003–2010 (upper panels) and 2011–2016 (middle panels) are in the South Pacific Ocean; for the period 2003–2016 (lower panels) is in the South Indo-Atlantic Ocean.
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