Weather regime transitions and the interannual variability of the North Atlantic Oscillation. Part I: a likely connection



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5 The NAO regime transition and interannual variation of the NAO index, frequency and location

a) Regime transition and NAO frequency

To further investigate whether the result based upon the cluster analysis is robust, we present the time series of the number of the NAO event days for each phase by counting the number of days that comprise the NAO(NAO) events, according to the definition of NAO events presented in section 2. The number of NAO (NAO) event days per winter is shown in Fig.11a. A comparison between Figs.11a and 3a indicates that the result obtained from the cluster technique is valid. To facilitate a comparison with the results of the previous section, the NAO(NAO) events within the NAONAO (NAONAO) transitions are removed (Fig.11b). Such an approach can indicate the impact of in-situ events on interannual NAO variability. It is seen in Fig. 11a that the number of NAO days increases (decreases) within P1 (P2), whereas the number of NAO days decreases (slightly increases) within P1 (P2). The NAO and NAO event day time series tend to have a negative correlation of , which is statistically significant at the 99% confidence level for a two-sided student’s t-test. Amongst the various trends in Fig. 11, it is only the linear upward trend of the NAO days during P1 that is found to be statistically significant at the 85% confidence level for a student t-test. The other linear trends are less significant.

On the other hand, we can see in Fig. 11b that when there are no NAONAO (NAONAO) transition events, the linear trends of the NAO and NAO event days within P1 and P2 become weaker. The number of NAO days exhibits a slightly smaller linear downward trend during P1 and P2. As a result, during P2 the linear trend of the NAO days without NAO regime transition events becomes opposite to that with NAO regime transition events, indicating the important role of NAO regime transition events in the NAO interannual variability. The results can also be found by using cluster analysis (not shown). These results, especially when comparing the trends in Fig. 11b with those in Figs. 3a and 11a, suggest that the NAO regime transitions can have an important impact on the interannual variation of the winter mean NAO index.

In previous studies (Cassou et al. 2004, Johnson et al. 2008), the frequency of occurrence of NAO (NAO) events includes the frequency of the NAO transition events. In this work, we have found that the different frequency of NAO transition events between P1 and P2 can contribute to the interannual variability of the NAO pattern.



b) Impact of the regime transition on the variation of the winter monthly mean NAO index

In this subsection, to see the contribution of NAO transition events to the NAO index variability, we use the daily indices of NAO events to construct two new monthly mean NAO indices: one based on the removal of NAO transition events and the other on the retention of the transition events. Here, the removal of NAO transition events is represented by removing NAO(NAO) events or retaining NAO(NAO) events within the NAO NAO (NAONAO) transition events. The time series of the monthly mean NAO index obtained using daily NAO indices are shown in Fig.12 for two cases with and without NAO and NAO events within the NAO NAO (NAONAO) transition events. The solid (dotted) curve represents the monthly mean NAO index with and without transition NAO events, while the thick solid (cross) line indicates a linear trend for the case with (without) the transitions. It is found that during P1 (P2) the linear upward (downward) trend of this new monthly mean NAO index is statisically significant at the 95 % (90%) confidence level for a student’s t-test. However, such trends become statistically significant only at the 90% (80%) confidence level when the NAO(NAO) events within NAONAO (NAONAO) transition events within P1 (P2) are removed. A similar conclusion is obtained if the winter mean NAO index is used (not shown). Thus, it is suggested from the result obtained here that NAO transition events can significantly affect the linear trends of the NAO interannual variability in winter within P1 and P2.

c) Regime transition and NAO location

One can also see the impact of the NAO transition events on the location of the NAO anomalies by performing a separate cluster analysis for those times when the NAO and NAO events of the NAONAO (NAONAO) transition events are included and when they are removed. In contrast to the previous cluster analysis, all NAO transition events during 1978-2008 are excluded. The same four weather regimes as in previous calculations are obtained (see Fig. 13). A comparison with Fig. 2 shows that the northern center of the NAO pattern exhibits an eastward displacement when all NAO transition events during 1978-2008 are retained. Such an eastward shift appears more evident for the negative phase. Many studies have revealed that the NAO pattern has undergone a noticeable eastward displacement since the late 1970s (Hilmer and Jung 2000; Peterson et al. 2003). Several mechanisms have been proposed to account for this eastward shift (Ulbrich and Christoph 1999; Peterson et al. 2003; Cassou et al. 2004; Luo and Gong 2006; Johnson et al. 2008; Luo et al. 2010a). However, here we propose a new mechanism that the frequent occurrence of NAO transition events is also another important cause of the marked eastward shift of the NAO centers of action during 1978-2008.



6 Conclusion and discussions

In this study, we have examined interannual changes in NAONAO and NAONAO transition events within P1 and P2 and evaluated their likely link with the interannual variability of the winter mean NAO index. It was shown that in P1 the frequency of NAONAO transition events is about twice that for the NAONAOtransition events. During P2, the transition events showed very different characteristics, as the frequency of NAONAO transition events was double that of the NAONAO transition events.

A cluster analysis showed that the difference in the number of NAO regime transition events between P1 and P2 can account in part for changes in the NAO amplitude, frequency, and location for each phase between the two subperiods, thus contributing toward the upward trend of the NAO event day time series in P1 and its downward trend in P2. Moreover, the frequent occurrence of the NAO regime transition events is also found to play an important role in the interannual eastward shift of the NAO centers of action found by many investigators (Hilmer and Jung 2000, Peterson et al. 2003; Cassou et al. 2004; Johnson et al. 2008).

Although the present study describes a plausible link between the intraseasonal NAO regime transitions and interannual variability of the NAO pattern from P1 to P2, it must however be pointed out that the interannual or decadal variability of the NAO index can be interpreted as a combination of both internally and externally generated variations (Osborn 2004). The externally generated variations are generally forced by the increased greenhouse gases concentrations (Ulbrich and Christoph 1999;Osborn 2004), stratospheric processes (Scaife et al. 2005) and ocean warming (Selten et al. 2004; Li et al. 2010) etc., while the internally generated variations arise from climate noise (Feldstein 2000, 2002) or are induced by the air-sea coupling (Timmermann et al. 1998; Hoerling et al. 2001;Marshall et al 2008; Muller et al. 2008). In this work, we did not examine the different roles of internal variability and external forcing in the interannual variability of the NAO index. Instead we have evaluated the impact of the intraseasonal NAO regime transitions on the interannual variability of the NAO pattern, and found that the intraseasonal NAO regime transitions can contribute significantly to the interannual variability of the winter mean NAO index. The occurrence of NAO transition events may also be linked to changes in the strengths of the AR and SBL patterns. Nevertheless, it is unclear how the NAO transitions depend upon the occurrence of AR and SBL regime events. Moreover, the dynamical processes that drive the NAO to SBL to NAO (NAO to AR to NAO) transitions within P2 (P1) are not examined in this work. The investigation of these problems will be the main purpose of Part II.


Acknowledgments
The authors acknowledge the support from the “one Hundred Talent Plan” of the Chinese Academy of Sciences (Y163011) and National Science Foundation of China (41075042, 40921004) and National Science Foundation grants ATM- 0852379 and AGS-1036858. The authors would like to thank two anonymous reviewers for valuable comments that improved this paper.
References

Bongioannini Cerlini P, S. Corti S and S. Tibaldi, 1999:An intercomparison

between low-frequency variability indices. Tellus A, 51,773–789.

Benedict J. J., S. Lee and S. B. Feldstein, 2004: Synoptic view of the North Atlantic Oscillation. J. Atmos. Sci., 61, 121-144.

Casado, M. J., M. A. Pastor and F. J. Doblas-Reyes,2009: Euro-Atlantic circulation types and modes of variability in winter, Theor. Appl. Climatol., 96, 17–29 DOI: 10.1007/s00704-008-0036-2.

Cassou, C., L. Terray, J. Hurrell, and C. Deser, 2004: North Atlantic winter climate regimes: Spatial asymmetry, stationarity with time, and oceanic forcing. J. Climate, 17, 1055–1068.

Cassou, C., 2008: Intraseasonal interaction between the Madden–Julian Oscillation and the North Atlantic Oscillation. Nature, 455, 523-527, doi:10.1038 /nature 07286.

Cheng, X., and J. M. Wallace, 1993: Cluster analysis of the Northern Hemisphere wintertime 500-hPa height field: Spatial patterns. J. Atmos. Sci., 50, 2674– 2696.

Choi, D. H., J. S. Kug, W. T. Kwon, F. F. Jin, H. J. Min, 2010: Arctic Oscillation responses to greenhouse warming and role of synoptic eddy feedback. J. Geophys. Res., 115, D17103, doi:10.1029/2010JD014160.

Cohen, J. and M. Barlow, 2005: The NAO, the AO, and Global warming: How closely related. J. Climate, 18, 4498-4513.

Corti, S., F. Molteni, and T. N. Palmer (1999), Signature of recent climate change in frequencies of natural atmospheric circulation regimes, Nature, 398, 799– 802.

Croci-Maspoli, M., C. Schwierz, and H. C. Davies, 2007: Atmospheric blocking: Space-time links to the NAO and PNA. Climate Dyn., 29, 713-725.

Feldstein, S. B., 2000: The timescale, power spectra, and climate noise properties of teleconnection patterns. J. Climate, 13, 4430–4440.

Feldstein, S. B., 2002: The recent trend and variance increase of the annular mode.  J. Climate, 15, 88-94.

Feldstein, S. B., 2003: The dynamics of NAO teleconnection pattern growth and decay. Quart. J. Roy. Meteor. Soc., 129, 901-924.

Franzke, C., 2009: Multi-scale analysis of teleconnection indices:climate noise and nonlinear trend analysis. Nonlinear Processes Geophys., 16, 65–76.

Franzke, C., S. Lee, and S. B. Feldstein, 2004: Is the North Atlantic Oscillation a breaking wave? J. Atmos. Sci., 61,145-160.

Franzke, C., I. Horenko, A. J. Majda, and R. Klein, 2009: Systematic metastable\ atmospheric regime identification in an AGCM. J. Atmos. Sci., 66, 1997– 2012.

Franzke, C., T. Woollings and O. Martius, 2011: Persistent circulation regimes and preferred regime transitions in the North Atlantic, J. Atmos. Sci., 68, 2809– 2825.

Graf, H. F., J. Perlwitz, I. Kirchner, and I. Schult, 1995: Recent northern winter climate trends, ozone changes and increased greenhouse gas forcing, Contrib. Phys. Atmos., 68, 233–248.

Hall, N. M., B. J. Hoskins, P. J. Valdes and C. A. Senior, 1994: Storm tracks in a high-resolution GCM with doubled carbon dioxide, Quart. J. R. Meteoro. Soc., 120, 1209-1230.

Hilmer, M., and T. Jung, 2000: Evidence for a recent change in the link between the North Atlantic Oscillation and Arctic sea ice export. Geophys. Res. Lett., 27, 989–992.

Honda, M., H., Nakamura, J. Ukita, I. Kousaka and K. Takeuchi, 2001: Interannual seesaw between the Aleutian and Icelandic lows. Part I: seasonal dependence and life cycle. J. Climate, 14,1029-1042

Honda, M., S.Yamane and H. Nakamura, 2005: Impacts of the Aleutian-Icelandic low seesaw on surface climate during the twentieth century. J. Climate, 18, 2793-2802

Hoerling, M. P., J. W. Hurrell and T. Xu, 2001: Tropical origins for recent North Atlantic climate change. Science, 292,90-92.

Hurrell, J. W., 1995: Decadal trends in the North Atlantic Oscillation: Regional temperature and precipitation, Science, 269, 676-679.

Johnson, N. C., S. B. Feldstein, and B. Tremblay, 2008: The continuum of Northern Hemisphere teleconnection patterns and a description of the NAO shift with the use of self-organizing maps. J. Climate, 21, 6354-6371.

Jung, T., M. Hilmer, E. Ruprecht, and S. Kleppek, 2003: Characteristics of the recent eastward shift of interannual NAO variability. J. Climate, 16, 3371– 3382.

Kimoto, M., and M. Ghil, 1993a: Multiple flow regimes in the Northern Hemisphere winter. Part I: Methodology and hemispheric regimes. J. Atmos. Sci., 50, 2625– 2644.

Kimoto, M., and M. Ghil, 1993b: Multiple flow regimes in the Northern Hemisphere winter. Part II: Sectorial regimes and preferred transitions, J. Atmos. Sci., 50, 2645– 26473.

Lau, N. C., 1988: Variability of the observed midlatitude storm tracks in relation to low-frequency changes in the circulation pattern. J. Atmos. Sci., 45, 2718- 2743.

Li, J. and X. L. Wang, 2003: A new North Atlantic oscillation index and its variability. Adv. Atmos. Sci., 20, 661-676.

Li, S., J. Perlwitz, M. P. Hoerling and X. Chen, 2010: Opposite annular responses of the Northern and Southern Hemispheres to Indian ocean warming, J. Climate, 23, 3720-3738.

Lin, H., G. Brunet and J. Derome, 2009: An observed connection between the North Atlantic Oscillation and the Madden-Julian Oscillation. J. Climate, 22, 364- 380.

Luo, D., and T. Gong, 2006: A possible mechanism for the eastward shift of interannual NAO action centers in last three decades. Geophys. Res. Lett., 33, L24815, doi:10.1029/2006GL027860.

Luo, D., A. Lupo and H. Wan, 2007a: Dynamics of eddy-driven low frequency dipole modes. Part I: A simple model of North Atlantic Oscillations. J. Atmos. Sci., 64, 3-38.

Luo, D., T. Gong and Y. Diao, 2007b: Dynamics of eddy-driven low-frequency

dipole modes. Part III: Meridional displacement of westerly jet anomalies during two phases of NAO. J. Atmos. Sci., 64, 3232-3248.

Luo, D., Z. Zhu, R. Ren, L. Zhong and C. Wang, 2010a: Spatial pattern and zonal shift of the North Atlantic Oscillation. Part I: A dynamical interpretation. J. Atmos. Sci., 67, 2805-2826.

Luo, D., L. Zhong, R. Ren and C. Wang, 2010b: Spatial pattern and zonal shift of the North Atlantic Oscillation. Part II: Numerical experiments. J. Atmos. Sci., 67, 2827-2853

Luo, D., Y. Diao and B. S. Feldstein, 2011: The variability of the Atlantic storm track and the North Atlantic Oscillation: A link between intraseasonal and interannual variability. J. Atmos. Sci., 68, 577-601.

Luo, D., J. Cha and B. S. Feldstein, 2012: Weather regime transitions and the interannual variability of the North Atlantic Oscillation. Part II: Dynamical processes. J. Atmos. Sci. (Submitted).

Marshall J., Y. Kushnir, D. Battisti, P. Chang, A. Czaja, R. Dickson, J. Hurrell, M. McCartney, R. Saravanan and M. Visbeck, 2001: North Atlantic climate variability: phenomena, impacts and mechanisms. Int. J. Climatol., 21, 1863- 1898.

Michelangeli, P. A., R. Vautard, and B. Legras, 1995: Weather regimes: Recurrence and quasi stationarity, J. Atmos. Sci., 52, 1237–1256.

Michel,C. and G. Rivi`ere, 2011: The link between Rossby wave breakings and weather regime transitions, J. Atmos. Sci., 68, 1730-1745.

Müller, W.A, C. Frankignoul and N. Chouaib, 2008: Observed decadal tropical Pacific-North Atlantic teleconnections. Geophys. Res. Lett., 35, L24810. doi:10. 1029/2008GL035901.

Rivi`ere, G. and I. Orlanski, 2007: Characteristics of the Atlantic storm-track eddy activity and its relation with the North Atlantic Oscillation. J. Atmos. Sci., 64, 241- 266.

Osborn, T. J., 2004: Simulating the winter North Atlantic Oscillation: the roles of internal variability and greenhouse gas forcing. Climate Dyn., 22, 605-623.

Overland, J. E., and W. Wang, 2005: The Arctic climate paradox: The recent decrease of the Arctic Oscillation. Geophys. Res. Lett., 32, L06701, doi:10. 1029/2004GL021752.

Paeth, H., A. Hense, R. Glowienka-Hense, R. Vose and U. Cubasch, 1999: The North Atlantic Oscillation as an indicator for greenhouse-gas induced regional climate change, Climate Dyn., 15, 953-960.

Peterson, K. A., J. Lu, and R. J. Greatbatch, 2003: Evidence of nonlinear dynamics in the eastward shift of the NAO, Geophys. Res. Lett., 30,1030, doi:10.1029/ 2002 GL015585.

Pinto, J. G, M. Reyers and U. Ulbrich, 2011: The variable link between PNA and NAO in observations and in multi-century CGCM simulations, Climate Dyn., 36, 337-354.

Rogers, J. C., 1997: North Atlantic storm track variability and its association to the North Atlantic Oscillation and climate variability of Northern Europe. J. Climate, 10, 1635-1647.

Scaife A. A., J. R. Knight, G. Vallis and C. K., Folland, 2005: A stratospheric influence on the winter NAO and north Atlantic surface climate. Geophys. Res. Lett., 32:L18715. doi:10.1029/2005GL023226.

Schneider E. K., L. Bengtsson and Z. Hu, 2003: Forcing of Northern Hemisphere climate trends. J. Atmos. Sci., 60,1504-1521.

Selten, F. M., G. W. Branstator, H. A. Dijkstra and M. Kliphuis, 2004: Tropical origins for recent and future Northern Hemisphere climate change. Geophys. Res. Lett., 31, L21205,doi:10.1029/2004GL020739.

Song, J., C. Li, W. Zhou and J. Pan, 2009: The linkage between the Pacific-North American teleconnection pattern and the North Atlantic Oscillation, Adv. Atmos. Sci. 26, 229–239

Timmermann, A., M. Latif, R. Voss and A. Grötzner, 1998: North Atlantic interdecadal variability: a coupled air-sea mode. J. Climate, 11,1906-1931.

Shindell, D. T., R. L. Miller, G. A. Schmidt and L. Pandolfo, 1999: Simulation of

recent northern winter climate trends by Greenhouse-gas forcing, Nature, 399, 452-455.

Vautard, R.,1990: Multiple weather regimes over the North Atlantic: Analysis of precursors and successors, Mon. Wea. Rev., 118, 2056–2081.

Ulbrich, U., and M. Christoph, 1999: A shift of the NAO and increasing storm track activity over Europe due to anthropogenic greenhouse gas forcing. Climate Dyn., 15, 551-559.

Ulbrich, U., J. G. Pinto, H. Kupfer, G. C. Leckebusch, T. Spangehl and M. Reyers, 2008: Changing Northern Hemisphere Storm Tracks in an Ensemble of IPCC Climate Change Simulations, J. Climate, 21, 1669–1679.

Wanner, H., S.Bronnimann, C. Casty, D. Gyalistras D, J. Luterbacher, C. Schmutz, D. B. Stephenson and E. Xoplaki, 2001: North Atlantic Oscillation. Concepts and studies, Surv. Geophys.,22,321-382.

Werner, P. C., F. W. Gerstengarbe, K. Fraedrich and H. Oesterle, 2000: Recent climate change in the North Atlantic European sector, Int. J. Climatol., 20, 463-471.

Wang, C., H. Liu, and S.-K. Lee, 2010: The record-breaking cold temperatures during the winter of 2009/2010 in the Northern Hemisphere. Atmos. Sci. Lett., 11, 161–168, doi:10.1002/asl.278.

Woollings, T. J., J. G. Pinto and J. A. Santos, 2011: Dynamical evolution of North Atlantic Ridges and poleward jet stream displacements. J. Atmos. Sci., 68, 954-963.

Woollings, T. J., B. J. Hoskins, M. Blackburn and P. Berrisford, 2008: A New Rossby Wave-breaking Interpretation of the North Atlantic Oscillation. J. Atmos. Sci., 65, 609-626.



Yiou, P. and M. Nogaj, 2004: Extreme climate events and weather regimes over the North Atlantic: When and where? Geophys. Res. Lett., 31, L07202, doi:10. 1029/2003GL019119.
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