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        The relationship between the Arctic Oscillation and ENSO as simulated by CCSM4

        2016-11-23 02:37:07ZHUYaliandWANGTao
        關(guān)鍵詞:正位二者北極

        ZHU Yaliand WANG Tao

        aNansen-Zhu International Research Centre, Chinese Academy of Sciences, Beijing, China;bClimate Change Research Centre, Chinese Academy of Sciences, Beijing, China

        The relationship between the Arctic Oscillation and ENSO as simulated by CCSM4

        ZHU Yalia,band WANG Taoa,b

        aNansen-Zhu International Research Centre, Chinese Academy of Sciences, Beijing, China;bClimate Change Research Centre, Chinese Academy of Sciences, Beijing, China

        The correlation between the Arctic Oscillation (AO) and ENSO refects the strength of the interaction between climate systems in the low and high latitudes. Based on the long-term (501 years) control simulation of CCSM4, the authors investigated the linkage between the AO and ENSO in boreal winter. Based on the correlation coefcients between them, the authors divided the entire period into two groups: one that included the years with statistically signifcant correlations (G1), and the other the years with insignifcant correlations (G2). In G1, the AO-related atmospheric circulation pattern resembles the ENSO-related one. The Aleutian Low (AL) acts as a bridge linking these two modes. In G2, however, the AO and ENSO signals are confned to the mid-high and mid-low latitudes,respectively. There is no signifcant linkage between the AO and ENSO in boreal winter, showing a low correlation coefcient. Further analysis suggests that changes in the climatological features,including the strengthened AO, the negative Pacifc Decadal Oscillation phase, and the weakened AL, may be responsible for the enhanced relationships.

        ARTICLE HISTORY

        Revised 29 December 2015

        Accepted 4 January 2016

        Arctic Oscillation; ENSO;

        CCSM4; Aleutian Low;

        climate interaction between low and high latitude

        北極濤動(dòng)(AO)和ENSO可以顯著影響我國(guó)冬季氣候。我們基于CCSM4的長(zhǎng)期(501年)參照試驗(yàn)結(jié)果, 揭示了冬季AO和ENSO間的關(guān)系存在年代際變化。在二者相關(guān)顯著時(shí)期,二者對(duì)我國(guó)南、北氣溫均有顯著影響; 而在相關(guān)不顯著時(shí)期, 二者分別主要影響我國(guó)北部和南部的氣溫。氣候態(tài)上出現(xiàn)的正位相AO、負(fù)位相太平洋年代際振蕩和減弱的阿留申低壓,可能有利于高低緯之間異常信號(hào)的傳播, 導(dǎo)致AO和ENSO的聯(lián)系顯著。

        1. Introduction

        Internal climate interactions between the low and high latitudes are important for regional climate variations. One example of such interaction is that between the Arctic Oscillation(AO) and ENSO. ENSO is the strongest signal at interannual timescales, and it can robustly infuence regional climate in the mid-low latitudes, such as the East Asian monsoon region(Alexander, Bladé, and Newman 2002; Wang 2002; Wang, Wu,and Fu 2000; Webster and Yang 1992). The AO, or its Atlantic counterpart, the North Atlantic Oscillation, is a dominant atmospheric mode in the northern high latitudes that can exert signifcant infuence on the Eurasian and African climate(e.g. Gong and Ho 2003; Gong, Wang, and Zhu 2001; McHugh and Rogers 2001; Sun and Wang 2006, 2012; Sun, Wang, and Yuan 2008; Thompson and Wallace 2001; Zhou 2013; Zhou and Cui 2014; Zhou and Wang 2015).

        Actually, the relationship between the AO and ENSO represents the collaboration of, and competition between,climate systems in the high and low latitudes. Therefore,it has critical implications for global and regional climate variations (e.g. Fraedrich and Müller 1992; Greatbatch and Jung 2007; Jia, Lin, and Derome 2009). Previous studies have revealed interdecadal changes in the relationship between the AO and ENSO (e.g. Greatbatch, Lu, and Peterson 2004; Li, Wang, and Liu 2014). Li, Wang, and Liu(2014) showed that the Aleutian Low (AL) acts as a bridge in the strengthening relationship between the AO and ENSO in January after the mid-1990s.

        In the present study, a long-term pre-industrial simulation by CCSM4 (Mu?oz et al. 2012) was used to explore the interdecadal variations in the relationship between the AO and ENSO, and associated atmospheric circulation.

        2. Data and methods

        CCSM4 is a global coupled climate model with a 1°, 26-level atmosphere coupled to a 1° (down to 1/48 in the equatorial tropics), 60-level ocean and state-of-the-art sea-ice and land-surface schemes (Gent et al. 2011). The 501-year control simulation was conducted with no interannual variations in external forcing agents, and greenhouse gas andtropospheric sulfate aerosol concentrations were fxed at pre-industrial (1850) levels. Thus, there was no long-term trend in the control simulation. Additionally, the changes in the AO and ENSO connection were mainly caused by the internal variability of the climate system in this study.

        Figure 1.The 21-year running correlation between the AO and Ni?o3.4 indices during the entire period.

        The variables used included SLP, surface air temperature(SAT), wind felds, and SST. In this study, the ENSO index was defned as the areal mean SST in the Ni?o3.4 region(5° S—5° N, 120—170° W). The AO index was defned as the leading principal component of monthly SLPs north of 20° N (Thompson and Wallace 1998). Here, we focus on the boreal winter season (i.e. December—February). The sign of the AO index was reversed (-AO) before calculating the spatial correlation patterns to facilitate the comparison between AO-related and ENSO-related signals.

        Prominent interdecadal changes can be found in the 21-year running correlation between the AO and ENSO indices (Figure 1). To perform composite analysis, we grouped years into those with statistically signifcant (G1,129 years) and insignifcant (G2, 136 years) AO—ENSO correlations. Group G1 included years with correlation coeffcients greater than the 95% confdence level (-0.41),while group G2 included years with correlation coefcients smaller than -0.2. The criterion of -0.2 was used to eliminate marginal efects of running correlation and keep G2 clear of the AO—ENSO relationship, as well as to obtain a sample size of G2 comparable with that of G1.

        3. Results

        Large-scale signifcant positive correlations between -AO and SLP are evident over northern high latitudes in both G1 and G2 (Figures 2(a) and (b)). For group G1, correlations are opposite across the meridian line (east, positive; west,negative) in the low latitudes, resembling warm ENSO signals (Figures 2(a) and (e)). In group G2, however, there is no signifcant correlation between the AO index and SLP over the Maritime Continent and Indian Ocean. At the same time, the negative correlations over the northern and eastern tropical Pacifc become weaker than those in G1 (Figure 2(b)). For the -AO and SAT, positive correlations can be observed over the eastern tropical Pacifc (Figure 2(c)), suggesting a warm ENSO pattern during the negative AO phase. However, there is no ENSO signal during the negative AO phase in G2 (Figure 2(d)). In G1, the correlation patterns between the ENSO index and SLP (Figure 2(e)),as well as between the ENSO index and SAT (Figure 2(g))are both similar to the -AO-related SLP and SAT patterns(Figures 2(a) and (c)). However, the -AO-related SLP and SAT are stronger than their ENSO-related counterparts over the polar region, but weaker over the lower latitudes. In G2, signifcant correlations exist, mostly in the mid-low latitudes, while almost no signifcant correlations exist in the polar region.

        Because the correlations with wind felds in the lower and upper levels present similar patterns, we have shown those in the upper level, which show stronger signals. In G1, -AO is signifcantly related to an anomalous anticyclone—cyclone—anticyclone wave-train pattern from the northern high latitudes through the North Pacifc to the tropical Pacifc (Figure 3(a)). The ENSO-related patterns in G1 (Figure 3(c)) are very similar to the -AO patterns (Figure 3(a)), with the exception of weaker correlations in the high latitudes and higher correlations in the mid-low latitudes. A negative AO can induce signifcant easterly anomalies in the midlatitudes, leading to signifcant cyclonic anomalies in the North Pacifc and anticyclonic anomalies in the northwestern Pacifc in G2 (Figure 3(b)). However, no robust signals can be found in the eastern tropical Pacifc. Similarly, a warm ENSO can induce signifcant circulation anomalies over the tropics, as well as cyclonic anomalies over the North Pacifc (Figure 3(d)). However, there are only weak anomalies over the high latitudes (Figure 3(d)). This suggests that the connection between the AL and both the AO and ENSO is enhanced in G1 compared with G2,which validates the AL bridging efect linking the AO and ENSO (Li, Wang, and Liu 2014).

        Figure 2.The correlation patterns between the -AO index and both (a, b) SLP and (c, d) SAT, as well as between the Ni?o3.4 index and both (e, f) SLP and (g, h) SAT in G1 (left column) and G2 (right column).

        To determine why there are diferences in the relationship between the AO and ENSO, as well as any connections with the atmospheric circulation in G1 and G2, we analyzed the climatological diferences in SLP, SAT, and wind felds between G1 and G2 (Figure 4). Statistically signifcant negative SLP anomalies are evident in the north of the Eurasian continent corresponding to a positive AO anomaly in G1 (Figure 4(a)). Positive SLP anomalies appear over the North Pacifc, though the values are not statistically signifcant. In the SAT felds, signifcant warming is observed over an area spanning from Northeast Asia to the central North Pacifc, which is accompanied by cooling to the east (Figure 4(c)). This distribution resembles a negative Pacifc Decadal Oscillation (PDO) pattern. Lowerlevel (not shown) and upper-level (Figure 4(e)) winds showsignifcant westerlies occurring over northern Eurasia; this indicates a positive AO. Meanwhile, anticyclonic anomalies appear over the North Pacifc, indicating a weakened AL. However, no systematic anomalies can be found in the climate variables in group G2.

        Figure 3.The correlation coefcients between both the (a, b) -AO index and (c, d) Ni?o3.4 index and wind at the 200 hPa level for G1(left column) and G2 (right column).

        4. Summary and discussion

        Using data from the control experiment conducted by CCSM4, we separated years based on the presence of signifcant (G1) or insignifcant (G2) AO—ENSO relationships. Composite analysis showed that AO- and ENSO-correlated patterns are diferent in G1 and G2. Connections with atmospheric circulation were statistically signifcant in both low and high latitudes in G1, while in G2 signifcant correlations were confned to the mid-high latitudes for AO and the mid-low latitudes for ENSO. In G1, the ENSO signal can propagate northward to the high latitudes, and the AO signal can propagate southward to tropical areas. The interactions between climate systems in the low and high latitudes are enhanced in G1, and the AL is likely to act as a bridge in the AO—ENSO linkage. The changes in climatological felds may be responsible for the diferent connections with the atmospheric circulation, such as the anomalous negative geopotential height over northern Eurasia, anomalous warming in the North Pacifc, and the weakened AL. These changes in the background circulation are consistent with the internal decadal changes in the climate system, such as an anomalous positive AO, negative PDO phase, and weakened AL. However, the underlying mechanisms for internal decadal changes are still unclear.

        Both ENSO and the AO have statistically signifcant implications for the winter East Asian climate (e.g. Chen et al. 2013; Gong, Wang, and Zhu 2001; Wang, He, and Liu 2013; Zhou, Chen, and Zhou 2013). The connection to the East Asian climate varies and accompanies changes in AO—ENSO relationships. In periods with insignifcant AO—ENSO interactions, the ENSO signals dominate East Asian temperature (Figure 2(h)), while the AO signals can only be found over small areas in northern East Asia (Figure 2(d)). Conversely, the infuence of the AO on East Asian temperature becomes stronger during periods with signifcant AO—ENSO interactions (Figure 2(c)); in the meantime, the impact from ENSO becomes weaker (Figure 2(g)). These phenomena indicate that the implications of predicting ENSO for East Asian temperature may decrease to some extent, accompanying a strengthened AO—ENSO relationship. In the real climate, the PDO shifted to a negative phase and the AL became weaker after the late 1990s, and a strengthened AO—ENSO connection appeared concurrently (Li, Wang, and Liu 2014). These results imply that the prediction of East Asian winter temperature, the success of which derives mainly from the ENSO phase, may become increasingly difcult.

        Figure 4.The climatological diference between G1 and the entire period (left column) and between G2 and the entire period (right column) for the (a, b) SLP, (c, d) TAS, and (e, f) 200 hPa wind feld. The maximum zonal wind in (e) is 1.21 m s-1.

        Funding

        This work was jointly supported by the Special Fund for the Public Welfare Industry (Meteorology) [grant number 201306026];National Natural Science Foundation of China [grant numbers 41130103, 41205054, and 41205051].

        Notes on contributors

        Yali Zhu is an associate professor. Yali Zhu's research interest is on interdecadal change in East Asian climate. Yali Zhu's publications are: Zhu, Y. L., H. J. Wang, J. H. Ma, T. Wang, and J. Q. Sun,2015: Contribution of the phase transition of Pacifc Decadal Oscillation to the late 1990s' shift in East China summer rainfall. Journal of Geophysical Research, 120(17), 8817-8827; Zhu, Y. L., 2012: Variations of the summer Somali and Australia cross-equatorial fows and the implications for the Asian summer monsoon. Advances in Atmospheric Sciences, 29(3), 509-513; Zhu,Y. L. H. J. Wang, W. Zhou, and J. H. Ma, 2010: Recent changes in the summer precipitation pattern in East China and the background circulation. Climate Dynamics, 36, 1463-1473.

        Tao Wang is an associate professor. Wang's research interests are paleoclimate simulation, interdecadal climate change in East Asian climate.Wang's publications are: Wang, T., and H.J. Wang,2013: Mid-Holocene Asian summer climate and its responses to cold ocean surface simulated in the PMIP2 OAGCMs experiments. Journal of Geophysical Research, 118, 4117-4128; Wang,T., H. J. Wang, O. H. Otter?, Y. Q. Gao, L. L. Suo, T. Furevik, and L. Yu,2013: Anthropogenic agent implicated as a prime driver of shiftin precipitation in eastern China in the late 1970s. Atmospheric Chemistry and Physics, 13, 12433-12450; Wang, T., O.H. Otter?,Y.Q. Gao, and H.J. Wang, 2012: The response of the North Pacifc Decadal Variability to strong tropical volcanic eruptions. Climate Dynamics, 39, 2917-2936.

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        北極濤動(dòng); ENSO; CCSM4;阿留申低壓; 高低緯相互作用

        21 December 2015

        CONTACT ZHU Yali zhuyl@mail.iap.ac.cn

        ? 2016 The Author(s). Published by Taylor & Francis.

        This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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