The changing influences of the AMO and PDO on the decadal variation of the Santa Ana winds

The decadal variation of the SAD is examined in figure 1 by showing the 11 year running means of the SAD index. The figure indicates that the average length of SAD fluctuated by about ±2 std's (i.e., ±7.8 days year⁻¹) from the normal value (i.e., 23.6 days year⁻¹) during the past five decades. SAW activity is suppressed from early-1960 to early-1980, during which SAW activity stayed about two std's below normal. The activity became much stronger than normal in the 1980s, near normal in the 1990s, and much stronger than normal again in the first decade of the 21st century. The ongoing decade of strong SAW activity shows little sign of decrease in SAD anomalies up until 2010. The stronger-than-normal SAW activity observed in the 21st century is opposite from the projection that anthropogenic warming may weaken SAW activity (Hughes et al 2009). This inconsistency raises the possibility that the variation of SAW activity in the last few decades may be related to natural decadal variability, such as the PDO or the AMO. To examine this possibility, we superimpose the time series of the AMO and PDO indices on figure 1. We find the correlation coefficient of the SAD index with the AMO index to be 0.72 and to be 0.49 with the PDO index. The difference between the correlation coefficients is significant at the 95% confidence level using a bootstrapping procedure (von Storch and Zwiers 1999) with 1000 times resampling. Alternatively, we composite the SAD index for the positive and negative phases of the AMO or PDO (i.e., years in which the indices are larger (smaller) than +0.7 (−0.7) std's) and find the composite difference to be larger between the two phases of the AMO (9.2 days year⁻¹) than that of the PDO (5.6 days year⁻¹). It is intriguing to find the decadal SAW variation to have a larger association with the decadal SST variations in the Atlantic (i.e., AMO) than with the decadal SST variations in the Pacific (i.e., PDO). The variation of the AMO index matches up well with the SAD variation in most of the analysis period, during which the value of SAD increases (decreases) when the AMO value increases (decreases). Only the period of 1983–1999 shows that the variation of the SAD follows more closely with that of the PDO.

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The connection between the decadal SAD variation and the AMO and PDO is likely linked through large-scale circulation patterns in the atmosphere, which can affect either the SLP gradient between the Great Basin and Southern California (Raphael 2003) or the latitudinal location of the Pacific jetstream that controls the path of winter cyclones (Raphael and Mills 1996) to modulate SAW activity. We refer to the former mechanism as the Great Basin high (GBH)—pressure gradient mechanism and the latter as the Pacific subtropical high (PSH)—jetstream displacement mechanism. To explore these two hypothesized mechanisms, we regressed SLP and 850 hPa wind anomalies from the NCEP/NCAR Reanalysis dataset onto the 11 year running means of SAD, AMO, and PDO indices as shown in figure 2. For reference, the climatology of these two variables are shown in figure 2(a). For the SAD index, the regressed SLP anomaly pattern (figure 2(b)) is characterized by strong positive values over the Great Basin (outlined by a green box in the figure), which induces anti-cyclonic wind anomalies over the region and produces northeasterlies from the mountainous areas toward the southwest coast. The regressed SLP anomalies also indicate a strengthening of the PSH (also outlined by a green box in the figure) associated with above-normal SAD values. Since the associated wind anomalies off the Southern California area are either not statistically significant or are against the direction of the SAW, the strengthened PSH is unlikely to intensify SAW activity via the GBH—pressure gradient mechanism. It is more likely that the PSH—jetstream displacement mechanism links the variation of the PSH to SAW activity. A stronger PSH can push the Pacific jetstream more poleward and decrease the frequency of winter cyclones that move toward Southern California, which should favor the development of SAW activity and above-normal values of SAD. To further test this mechanism, we examine the latitudinal profile of the winter (December through February) zonal wind at 200 hPa (U200) outside North America (between 160°E–120°W) regressed onto the SAD index. We find from figure 2(f) that the U200 anomalies regressed onto the SAD index exert a northward displacement of the Pacific jetstream from its climatological location of 35°N (see figure 2(e)), which is consistent with the hypothesis.

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The SLP anomalies regressed with both the AMO index (figure 2(c)) and the PDO index (figure 2(d)) show strong positive values over the Great Basin similar to the SAD-regression pattern, which indicates that the AMO and PDO can promote SAW activity via the GBH—pressure gradient mechanism. However, these two decadal modes produce opposite SLP anomalies over the subtropical Pacific; while the AMO strengthens the PSH, the PDO weakly weakens the PSH. With a stronger PSH, the AMO can cause the Pacific jetstream to displace more poleward and prevent winter cyclones from traveling through Southern California. The U200 anomalies regressed onto the AMO index (figure 2(g)) confirm that the Pacific jetstream is displaced about 10° more poleward from its climatological location. By regressing the std's of the high-frequency (2–8 d) winter meridional wind at 250 hPa onto the AMO index, we show in figure 2(k) that the maximum center of winter storm activity is displaced more northward compared to the climatology (figure 2(i)). A similar displacement can also be seen in the regression onto the SAD index (figure 2(j)). As a result, the AMO can intensify SAW activity by strengthening the pressure gradient between the Great Basin and the Southern California coast and by simultaneously decreasing the hindering effect of winter cyclones on the SAW. In contrast, with a weakened PSH, the PDO can cause the Pacific jetstream to displace more southward (figure 2(h)) and bring more winter cyclones toward Southern California (figure 2(l)) to discourage the development of SAW. This southward displacement of the jetstream can cancel out the strengthening effect of the PDO on the SAW through the GBH—pressure gradient mechanism. The cancelation of these two mechanisms is the reason why the PDO has a weaker modulation effect on SAW activity than the AMO.

To further confirm the findings obtained from the 51 year long NCEP/NCAR Reanalysis dataset, we repeat the regression analysis using the 113 year long 20th century reanalysis dataset. The results confirm that the AMO strengthens both the GBH and PSH (figure 3(a)) and displaces the jetstream more northward (figure 3(c)), while the PDO strengthens the GBH but weakens the PSH (figure 3(b)) and shifts the jetstream more southward (figure 3(d)).

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To confirm our suggestion that the AMO is more influential in modulating SAW activity than the PDO for the entire analysis period, we further examine the intensity of the SAD, AMO and PDO indices and their associated atmospheric circulation patterns for different time periods. Based on the discussion of figure 1, we divided the analysis period into three sub-periods: the first period in 1965–1982 (i.e., P1) where the SAD values are below normal and follow more of the AMO variation, the second period in 1983–1999 (i.e., P2) where the SAD values are above normal and follow more of the PDO variation, and the third period in 2000–2010 (i.e., P3) where the SAD values are above normal and follow the AMO variation again. During P1, the AMO stayed in the negative phase for the majority of this period while the PDO changed from a negative phase to a positive phase around 1976–77. The SAD variation in this period is more in-phase with the AMO index than the PDO index. The mean intensity (i.e., mean value) is –0.92 std's for the AMO index during this period and −0.64 std's for the PDO index. During P2, the PDO index is in the positive phase throughout while the AMO index changed from a negative phase to a positive phase in the early 1990s. In this period, the SAD variation is more in-phase with the PDO index. The mean intensity of the PDO index in this period is 1.02 std's, which is much stronger than that of the AMO index (−0.11 std's). During P3, the AMO index stayed in the positive phase while the PDO index changed from a positive phase to a negative phase at the beginning of the period. At this time, the SAD variation is more in-phase with the AMO index. The mean intensity of the PDO index is very small (−0.08 std's) but the mean intensity of the AMO index is large (1.49 std's). It is apparent that the mean intensity of the AMO and PDO indices plays an important role in determining which index has a stronger control of the decadal variation of SAD. The decadal SAD variation is modulated more by the AMO during P1 and P3 when the AMO persistently stayed in one particular phase while, at the same time, the PDO changed its phase. The PDO took control of the SAD variation during P2 because the PDO persistently stayed in one particular phase while the AMO changed phases.

To identify the individual influences of the AMO and PDO in modulating the SAD variation, we reconstructed the anomalous atmospheric circulation patterns for these three sub-periods based on the mean intensity of the AMO and PDO indices. In figures 4(a)–(i), each of the SLP anomaly patterns is reconstructed by multiplying the SLP regression pattern (figures 2(b)–(d); obtained from the entire period) by the mean intensity of the index for each sub-period (figure 1). During P1, the reconstructed SLP pattern based on the SAD index (figure 4(a)) is characterized by strong negative anomalies over the Great Basin and the subtropical Pacific, which result in a weak SLP gradient to the Southern California coast and a weakened Pacific jetstream (figure 4(j)), which is consistent with the below-normal values of the SAD observed in the period (see figure 1). The AMO-reconstructed SLP pattern (figure 4(d)) is similar to the SAD-reconstructed pattern (see figure 4(a)). The PDO-reconstructed SLP pattern (figure 4(g)) shows negative SLP anomalies over the Great Basin but positive SLP anomalies over the subtropical Pacific. While the former anomalies can weaken SAW activity, the latter anomalies can strengthen SAW activity. As a result, the PDO's influence on the SAW (and SAD) is weaker than the influence of the AMO. During P2, the SAD-reconstructed SLP pattern (figure 4(b)) has weak positive anomalies over the Great Basin but little influence on the PSH. The PDO-reconstructed SLP pattern (figure 4(h)) is in-phase with the SAD-reconstructed pattern, but the AMO-reconstructed SLP pattern (figure 4(e)) has very weak magnitude, making the PDO the main influence on the SAD variability in P2. However, a portion of the PDO's strengthening effect on the SAW through the Great Basin pressure gradient is canceled out by the PDO's weakening effect on the SAW through the PSH, shifting the Pacific jetstream about 5° south from its climatological location (figure 4(k)). As a result, the mean intensity of the SAD index during this period (0.5 std's) is low. During P3, the SAD-reconstructed SLP pattern (figure 4(c)) also exhibits positive anomalies over the Great Basin and the subtropical Pacific with the above-normal SAD values. The magnitude of the AMO-reconstructed SLP pattern in P3 (figure 4(f)) is strongly positive, while the magnitude of the PDO-reconstructed SLP pattern (figure 4(i)) is very weak. Therefore, the AMO becomes the main influence on the SAD variability in this period. The U200 anomalies in figure 4(l) support this, showing that the jetstream is shifted more than 5° north of its climatological location, which would deflect mid-latitude cyclones away from Southern California, encouraging SAW development. This shift coincides with the high magnitude of the AMO-reconstructed SLP pattern in the subtropical Pacific (see figure 4(f)).

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The main findings we obtained from the past five decades of observation suggest that we can use the phase changes of the PDO and AMO to project how the SAD variability may behave in the coming few decades. This information, while not particularly accurate, can still be useful for city or state planning purposes. First, we applied the following multivariate linear regression model:

$$\begin{eqnarray}&&{\rm{SAD}}* \;=\;{a}{\rm{A}}{\rm{M}}{\rm{O}}+{b}{\rm{P}}{\rm{D}}{\rm{O}}\end{eqnarray} \tag{ 1 }$$

for the 1960–2010 period to determine the regression coefficients (i.e., a = 0.72 and b = 0.50). We then extended the AMO and PDO indices to 2050 (i.e., AMO* and PDO*, respectively; see figure 5) using a Fourier decomposition. Lastly, we projected SAD (i.e., SAD*) by replacing the original time series (AMO and PDO) with the extended time series (AMO* and PDO*) in equation (1). As shown in figure 5, the SAD* (i.e., projected) variation matches up well with the SAD (i.e., original) variation during most of the analysis period (i.e., a correlation coefficient of 0.87; significant at the 99% level). Our projection indicates that the AMO* will shift to a negative phase after 2020 while the PDO* will continue to stay in the negative phase until the year 2030. Based on the projection, the above-normal SAW activity we observed in the most recent decade may be terminated after 2016. More importantly, the projection indicates that Southern California is expected to experience an extended period of below-normal SAW activity all the way to 2030.

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