a. Observations
The observed low-pass filtered AMV index shows a remarkable interdecadal variability from 1959 to 2016. In general, the AMV index shows a positive–negative–positive fluctuation, with positive phases in the time periods 1959–1964 and 1997–2013 and negative phases in the time periods 1965–1996 and 2014–present (Fig. 1a).
As indicated in previous research (Si and Ding 2016), the AMV is capable of driving the climate variability in the Northern Hemisphere through exciting a circum-global Atlantic–Northern Hemisphere (ANH) teleconnection. This teleconnection can be identified from the regression of the AMV onto the 500–hPa geopotential height, which displays a prominent global zonal wave train pattern with five centers of action located over the North Atlantic, Western Europe, Eastern Europe, northern Asia and the western North Pacific (Fig. 1b). To demonstrate this ANH teleconnection pattern more clearly, the AMV is regressed onto the 500–hPa stream function in the Northern Hemisphere (Fig. 1c). It is clear that the ANH teleconnection pattern can also be observed in the stream function field. The positive stream function corresponds to the positive (anticyclonic) center of action and the negative stream function corresponds to the negative (cyclonic) centers in Figure 1b. The wave activity flux is calculated to explore the propagation of the wave energy associated with the ANH (Fig. 1c). The wave activity flux shows that the wave energy propagates northeastward from the subtropical North Atlantic to Western Europe and then propagates eastward through the Eurasian continent to the North Pacific Ocean. This result indicates that the AMV is the origin of the circum-global atmospheric teleconnection pattern.
The atmospheric circulation is equivalent barotropic in the extra-tropical sector of the North Atlantic (Figs. 1b and 1d). The barotropic dipole mode, with high pressure over the mid-latitude North Atlantic and low pressure to the west of the UK, resembles the eastern Atlantic atmospheric pattern. The eastern Atlantic atmospheric pattern is excited by changes in the stationary waves, which are associated with SST anomalies in the North Atlantic (Msadek et al. 2011). The wave energy related to the eastern Atlantic atmospheric pattern emanates globally from the North Atlantic along the mid-latitude westerly jet (Fig. 1c).
At lower levels, anomalous low pressures are located over North Africa, western Europe and northern Asia, whereas there are anomalous high pressures over the mid-latitude North Atlantic, eastern Europe and the western North Pacific (Fig. 1d). The low-pressure anomalies correspond to an inflow of moisture toward the center and increased cloudiness, leading to above–normal precipitation anomalies and below–normal SAT anomalies in most parts of western Europe north of 42°N, in North Africa between 5° and 20°N, in the area around Lake Baikal and in parts of East Asia (Figs. 1e and 1f), and vice versa for the anomalous high-pressure circulation. The high pressure over the western North Pacific and low pressure over East Asia enhance the East Asian summer monsoon, which results in the northward movement of the East Asian rain belt to the north of the Yangtze River (Guo 1983).
The anomalies in the observed atmospheric circulation, precipitation and SAT (Figs. 1b–f) are consistent with previous observational (Sutton and Dong 2012; Si and Ding 2016) and numerical studies (Cheng et al. 2007; Liu and Chiang 2012). For example, observational analysis has shown that the warming of the North Atlantic causes a large–scale high–low–high pattern of anomalous circulation over the North Atlantic and western and eastern Europe, respectively, and the anomalous trough located over western Europe contributes to a North–South dipole of climate over western Europe with drier and warmer conditions over the South and wetter and mild conditions over the North (Sutton and Dong 2012). A coupled model study has suggested that the cooler North Atlantic in the 1960s weakened the African and Eurasian summer monsoon via an ANH–like atmospheric teleconnection (Cheng et al. 2007). These studies suggest that the AMV is a major force in the ANH teleconnection and is capable of causing hemispheric–scale changes in the Earth’s climate.
b. Simulation by the North Atlantic pacemaker experiment
The idealized North Atlantic pacemaker simulations indicate that, for AMV+ minus AMV–, the SST pattern in the North Atlantic is characterized by positive SST anomalies above 0.2°C over the tropical North Atlantic and above 0.4°C over the extra-tropical North Atlantic exhibiting the positive phase of internally–generated AMV (Fig. 2a). There are significant same–sign SST anomalies above 0.1°C over the western North Pacific, which resembles the negative phase of Pacific Decadal Oscillation. It is noteworthy that the internally–generated AMV generate the ANH teleconnection pattern extending from the North Atlantic to the western North Pacific (Fig. 2b, c), with a close resemblance to the observations. The idealized simulation captures well the meridional tripolar pattern over North Atlantic and other three centers of action over eastern Europe, East Asia and western North Pacific. Eventually, the idealized simulation reproduces well the wet and mild climate over North Africa and western Europe, dry and warm climate over eastern Europe and southern East Asia, and wet and warm climate over northern East Asia corresponding to the positive phase of AMV (Fig. 2d, e). These results suggest that the ANH teleconnection indeed driven by the low-frequency and internally–generated component of AMV.
Because the SSTs in the time–series pacemaker experiments are nudged toward the time–evolving observed SST anomalies in the North Atlantic, it is not surprising that these experiments can capture well the observed variation in the SST anomalies in the North Atlantic (Fig. 3a). The simulated AMV index in the time–series pacemaker experiments is almost identical to the observations from 1959 to 2013, with the temporal correlation coefficient (TCC) reaching 0.99 and an RMSE of only 0.03 (Table 2). The time–series pacemaker experiment reproduces the ANH teleconnection pattern extending from the North Atlantic to the western North Pacific reasonably well, with a pattern correlation coefficient (PCC) of 0.19 (Fig. 3b, Table 3). The geographical positions of the action centers generally match the observed positions over the North Atlantic and western Europe, with an eastward shift of the action center over eastern Europe to the west of Lake Baikal. At the surface, the simulated sea–level pressure, precipitation and SAT anomalies also agree with the observations, with PCCs of 0.04, 0.37 and 0.61, respectively (Figs. 3c–e, Table 3). Physically, the negative sea–level pressure anomalies correspond to above–normal precipitation and below–normal SATs, and vice versa for the positive sea–level pressure anomalies, suggesting that the model can capture the basic physical processes well.
Despite these agreements, the teleconnection simulated in CESM1 is more biased further downstream than in the region directly over or near the North Atlantic, indicating that improvements are still needed for the model to be able to more accurately simulate the observed teleconnection patterns. Nevertheless, these results suggest that the AMV is capable of influencing the northern mid-latitude atmospheric anomalies and climate variability in the Northern Hemisphere in both the observations and numerical simulations (Sutton and Hodson 2005; Si and Ding 2016; Jiang et al. 2020).
c. Simulation by the MMLEA experiments
Figure 4 shows the AMV index simulated by the four models of the MMLEA (CanESM2, CSIRO–MK, GFDL–CM and CESM1). The models are generally capable of reproducing the observed positive–negative–positive phase variation of the AMV from 1959 to 2016. The TCC between the simulated AMV index in the MMLEA and the observations ranges from 0.44 to 0.69 with an RMSE <0.17, a number about five times larger than that in the CESM1 time–series pacemaker runs (Table 2).
The simulated ANH atmospheric teleconnection pattern in the MMLEA is compared with the observations. The MMLEA models are generally capable of producing an ANH–like teleconnection pattern from the North Atlantic through Eurasia to the western North Pacific, with shifts in the geographical positions of the action centers (left–hand panels in Fig. 5). The MMLEA multi-model mean generally capture the positive geopotential height anomalies over the mid-latitude North Atlantic and eastern Europe and the negative anomalies over western Europe and northern Asia associated with the ANH teleconnection pattern (Fig. 5e). Among the four MMLEA models, there are two or more models basically agree with the observed sign along the route of this teleconnection pattern. While more than three models reproduced the same sign with the observation over parts of North Atlantic and northern Asia. Compared with the observation, it can been seen that the negative anomalies over western Europe is weak and shift eastward. Moreover, the multi-model mean fail to capture negative geopotential height anomalies over Lake Baikal and positive geopotential height anomalies over northwest Pacific and produce an anomalies over the Lake Baikal–Okhotsk Sea sector of opposite sign to the observation. Among the four models, the GFDL–CM shows the best performances in simulating the geopotential height anomalies in the Lake Baikal–Okhotsk Sea sector and bear a strong resemblance to the observations. The PCCs between the simulations and observations for the 500–hPa geopotential height in the northern mid-latitudes are better over the Eurasian continent than over the North Atlantic and are positively correlated in two (CanESM2 and GFDL–CM) of the four MMLEA models (Table 3), but are negatively correlated in CSIRO-MK and CESM–LE. The PCC is negative over the North Atlantic in nearly all models because they all produce a positive North Atlantic Oscillation (NAO)–like pattern, but there is a negative NAO–like pattern in the observations. Previous multi-model comparison of the AMV and its climate impacts (Medhaug and Furevik 2011; Ting et al. 2011; Ba et al. 2014) is model dependent. Our study also highlights the large discrepancies associated with the atmospheric teleconnection related with AMV simulated by the CMIP5–like experiments. Although the RMSEs for all models are not very different from that in the CESM1 time–series pacemaker simulations, the simulated teleconnection pattern in MMLEA is more biased than that in the CESM1 time–series pacemaker simulations (Table 4), either due to a biased pattern or the more significantly shifted geographical locations of the active centers.
For the corresponding northern mid-latitude wave–train–like sea–level pressure anomalies in association with the ANH (right–hand panels in Fig. 5), the PCCs between the model simulations and the observations are positive in two models (CanESM2 and GFDL–CM), with a PCC higher than the CESM1 time–series pacemaker runs (Table 3), but negative in CSIRO–MK and CESM–LE over the Eurasian continent. Over the North Atlantic, only GFDL–CM produces a strong positive PCC and the other three models produce a negative or zero PCC. These results indicate that although the models are capable of producing wave–train–like sea–level pressure anomalies, the exact locations of these anomalies differ from those in the observations, which calls for further improvements in the simulated atmospheric circulation pattern.
The models capture the low-level convergence–divergence–convergence pattern of the Eurasian continent seen in the observations, eventually leading to a wet–dry–wet pattern in precipitation and a mild–warm–mild pattern in the SAT (Fig. 6). Although CESM-LE produces a negative PCC with the observed precipitation, the other three models all produce a positive PCC, but less than that in the CESM1 time–series pacemaker runs (Table 3). The PCCs between the observed and modeled SAT anomalies are fairly similar among the models. Overall, pattern correlation analysis shows that the skill of the MMLEA models with respect to the AMV–induced precipitation and SAT teleconnection are generally higher than the skill for the geopotential height and sea–level pressure (Table 3). The higher PCC for the SAT may be a result of its lack of detailed regional patterns. A particularly noteworthy point is that the time–series pacemaker simulations show a higher PCC and lower RMSE than the MMLEA simulations (Tables 3 and 4), implying that the North Atlantic SST biases in the free–run models may have played an essential part in deviating the atmospheric circulation pattern and the associated surface climate from the observations. By correcting these SST biases, the CESM1 time–series pacemaker runs produce AMV–related teleconnection patterns significantly better than those in CESM–LE.
Nevertheless, the MMLEA models suggest that the AMV can generate a circum-global atmospheric teleconnection pattern extending from the North Atlantic and propagating eastward around the globe. The overall better performance of the time–series pacemaker runs in simulating the AMV and associated atmospheric teleconnection than the free–run MMLEA historical simulations can be attributed to the SST, which is close to the observed North Atlantic SST, further demonstrating that this circum-global atmospheric teleconnection pattern is closely related with the AMV.