Influence of the Atlantic Multidecadal Oscillation and Interdecadal Pacific Oscillation on Antarctic surface air temperature during 1900 to 2015
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Abstract: The importance of the Atlantic Multidecadal Oscillation (AMO) and Interdecadal Pacific Oscillation (IPO) in influencing zonally asymmetric changes in Antarctic surface air temperature (SAT) has been established. However, previous studies have primarily concentrated on examining the combined impact of the contrasting phases of the AMO and IPO, which have been dominant since the advent of satellite observations in 1979. This study utilizes long-term reanalysis data to investigate the impact of four combinations of +AMO+IPO, –AMO–IPO, +AMO–IPO, and –AMO+IPO on Antarctic SAT over the past 115 years. The +AMO phase is characterized by a spatial mean temperature amplitude of up to 0.5℃ over the North Atlantic Ocean, accompanied by positive sea surface temperature (SST) anomalies in the tropical eastern Pacific and negative SST anomalies in the extratropical-mid-latitude western Pacific, which are indicative of the +IPO phase. The Antarctic SAT exhibits contrasting spatial patterns during the +AMO+IPO and +AMO–IPO periods. However, during the –AMO+IPO period, apart from the Antarctic Peninsula and the vicinity of the Weddell Sea, the entire Antarctic region experiences a warming trend. The most pronounced signal in the SAT anomalies is observed during the austral autumn, whereas the combination of –AMO and –IPO exhibits the smallest magnitude across all the combinations. The wavetrain excited by the SST anomalies associated with the AMO and IPO induces upper-level and surface atmospheric circulation anomalies, which alter the SAT anomalies. Furthermore, downward longwave radiation anomalies related to anomalous cloud cover play a crucial role. In the future, if the phases of AMO and IPO were to reverse (AMO transitioning to a negative phase and IPO transitioning to a positive phase), Antarctica could potentially face more pronounced warming and accelerated melting compared to the current observations.
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Figure 1. The 1900–2015 20CR (left; a, d, g, and j), 1979–2015 20CR (middle; b, e, h, and k) and 1979–2015 ERA5 (right; c, f, i, and l) surface air temperature trends in different seasons.
Figure 2. Variance in surface air temperature in austral summer (JFM) (a), autumn (AMJ) (b), winter (JAS) (c) and spring (OND) (d).
Figure 4. Distribution of SST anomaly of ERSST in different phases of the AMO and IPO in JFM, AMJ, JAS, and OND. The dots denote the values passing the 95% confidence level for the two-sided Student’s t-test.
Figure 5. Distribution of 2-m air temperature anomaly of 20CR in different phases of the AMO and IPO in JFM, AMJ, JAS, and OND. The dots denote the values passing the 95% confidence level for the two-sided Student’s t-test.
Figure 6. Distribution of 2-m air temperature anomaly of ERA-20C in different phases of the AMO and IPO in JFM, AMJ, JAS, and OND.
Figure 7. Distribution of the 10-m wind anomaly (m/s; vectors, scale in bottom right) and sea level pressure anomaly (hPa; shading, lower row) of 20CR in different phases of the AMO and IPO in AMJ. The dots denote the values passing the 95% confidence level for the two-sided Student’s t-test.
Figure 8. Distribution of the total cloud cover anomaly (left column) and downward longwave radiation flux anomaly at the surface (right column) of 20CR in different phases of the AMO and IPO in AMJ. The dots denote the values passing the 95% confidence level for the two-sided Student’s t-test.
Figure 9. Distribution of albedo anomalies (left column) and net shortwave radiation flux anomalies at the surface (right column) of 20CR in different phases of the AMO and IPO in AMJ. The dots denote the values passing the 95% confidence level for the two-sided Student’s t-test.
Figure 10. Anomalous surface precipitation rate (left column) and upward longwave radiation flux at the nominal top of the atmosphere anomaly (right column) from 20CR data in AMJ. The dots denote the values passing the 95% confidence level for the two-sided Student’s t-test.
Figure 11. The 200 hPa divergent wind anomaly (vectors), Rossby wave source in AMJ (shading) (left column) and the 200 hPa height anomaly (shading) and anomalous wave activity flux (vectors) of 20CR in AMJ (right column).
Table 1. Years in different phases of the AMO and IPO from 1900–2015
Month Years in different phases +AMO+IPO –AMO–IPO +AMO–IPO –AMO+IPO JFM
1929–1933
1938–1942
1908–1912
1914–1926
1964–19781934–1937
1943–1963
1998–20151900–1907/1913
1927–1928
1979–1997AMJ
1928–1933
1938–1942
1908–1912
1914–1925
1963–19781934–1937
1943–1962
1998–20151900–1907/1913
1926–1927
1979–1997JAS
1928–1933
1937–1942/1997
1908–1912
1914–1925
1963–19771934–1036
1943–1962
1998–20151900–1907/1913
1926–1927
1978–1996OND
1928–1932
1937–1941
1908–1925
1963–1977
1933–1936
1942–1962
1997–20151900–1907
1926–1927
1978–1996
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Table 2. Correlation coefficients of surface temperature anomalies between ERA-20C and 20CR in different phases of the AMO and IPO
Month Correlation coefficient +AMO+IPO –AMO–IPO +AMO–IPO –AMO+IPO JFM 0.62* 0.77* 0.86* 0.72* AMJ 0.93* 0.01 0.63* 0.74* JAS 0.79* 0.26* 0.69* 0.72* OND 0.62* 0.41* 0.64* 0.73* Note: Asterisk (*) denotes above 99% confidence level.
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