El Niño-Southern Oscillation
Computer model simulations have given rise to three claims regarding the influence of global warming on El Niño/Southern Oscillation (ENSO) events: (1) global warming will increase the frequency of ENSO events, (2) global warming will increase the intensity of ENSO events, and (3) weather-related disasters will be exacerbated under El Niño conditions. Here, we test the validity of these assertions, demonstrating they are in conflict with the observational record. We begin by highlighting studies that suggest the virtual world of ENSO, as simulated by state-of-the-art climate models, is at variance with reality, once again drawing upon studies not included in, or published subsequent to, the 2009 NIPCC report.
Examining the subject over the past 3,500 years, Langton et al. (2008) used geochemical data—obtained from a sediment core extracted from the shallow-silled and intermittently dysoxic Kau Bay in Halmahera, Indonesia (1°N, 127.5°E)—to reconstruct century-scale climate variability within the Western Pacific Warm Pool. In doing so, they found “basin stagnation, signaling less El Niño-like conditions, occurred during the time frame of the Medieval Warm Period (MWP), from ca. 1000 to 750 years BP,” which was “followed by an increase in El Niño activity that culminated at the beginning of the Little Ice Age ca. 700 years BP.” Thereafter, their record suggests “the remainder of the Little Ice Age was characterized by a steady decrease in El Niño activity with warming and freshening of the surface water that continued to the present.” And they say “the chronology of flood deposits in Laguna Pallcacocha, Ecuador (Moy et al., 2002; Rodbell et al., 1999), attributed to intense El Niño events, shows similar century-scale periods of increased [and decreased] El Niño frequency.”
The nine researchers concluded “the finding of similar century-scale variability in climate archives from two El Niño-sensitive regions on opposite sides of the tropical Pacific strongly suggests that they are dominated by the low-frequency variability of ENSO-related changes in the mean state of the surface ocean in [the] equatorial Pacific.” And that “century-scale variability,” as they describe it, suggests global warming typically tends to retard El Niño activity, while global cooling tends to promote it.
In a contemporaneous study, Nicholls (2008) prefaced his contribution to the topic by noting there has been a “long-running debate as to how the El Niño-Southern Oscillation (ENSO) might react to global warming,” and “the focus in most model studies on ENSO and climate change has been on whether the Pacific will tend to a more permanent El Niño state as the world warms due to an enhanced greenhouse effect.” In an attempt to resolve the issue, Nicholls examined “trends in the seasonal and temporal behavior of ENSO, specifically its phase-locking to the annual cycle over the past 50 years,” where phase-locking, in his words, “means that El Niño and La Niña events tend to start about April–May and reach a maximum amplitude about December–February,” which is why he examined trends in ENSO indices for each month of the year.
The Australian researcher determined “there has been no substantial modulation of the temporal/seasonal behavior of the El Niño-Southern Oscillation”—as measured by the sea surface temperature averaged across the region 5°S–5°N by 120°W–170°W, and the Southern Oscillation Index (the non-standardized difference between sea level pressures at Tahiti and Darwin)—over the past 50 years, during what he describes as “a period of substantial growth in the atmospheric concentrations of greenhouse gases and of global warming.” Nicholls’ finding that “the temporal/seasonal nature of the El Niño-Southern Oscillation has been remarkably consistent through a period of strong global warming” clearly repudiates the early climate-model-derived inferences of Timmermann et al. (1999), Collins (2000a,b), and Cubasch et al. (2001) that global warming will increase both the frequency and intensity of ENSO events. Those projections (not surprisingly) followed fast on the heels of the powerful 1997–98 El Niño described by some as “the strongest in recorded history” (Jimenez and Cortes, 2003).
Lee and McPhaden (2010) reported “satellite observations suggest that the intensity of El Niño events in the central-equatorial Pacific (CP) has almost doubled in the past three decades,” citing the work of Cane et al. (1997) and Cravatte et al. (2009), while noting this phenomenon “appears to be consistent with theoretically predicted change of the background sea surface temperature under global warming scenarios.” To test this hypothesis, they used satellite observations of sea surface temperature (SST) over the past three decades “to examine SST in the CP region, distinguishing between the increases in El Niño intensity and changes in background SST.”
In conducting their analysis, the two U.S. researchers discovered the SSTs in the CP region during El Niño years were becoming significantly higher while those during La Niña and neutral years were not. Therefore, they reasoned “the increasing intensity of El Niño events in the CP region is not simply the result of the well-documented background warming trend in the western-Pacific warm pool,” but “it is the increasing amplitude of El Niño events that causes a net warming trend of SST in the CP region.” In light of these findings, they suggest “at least for the past three decades, the warming of the warm pool in the CP region is primarily because of more intense El Niño events in that region.” In addition, they report “in contrast to the CP region, the intensity of El Niño events in the EP region does not have a warming trend, and even has a cooling trend (though not significant at the 90% level of confidence) over the three-decade period.” Thus, they conclude further investigation is needed “to understand these issues better, given the uncertainty surrounding causal mechanisms and the implications the observed changes have for global climate and societal impacts.”
In a contemporaneous study focusing more on the modeling of ENSO behavior, Collins et al. (2010) reviewed the findings of what they describe as “a hierarchy of mathematical models [that] have been used to explain the dynamics, energetics, linear stability and nonlinearity of ENSO,” while noting “complex coupled global circulation models have become powerful tools for examining ENSO dynamics and the interactions between global warming and ENSO.”
Those powerful tools revealed, among other things, that “the tropical easterly trade winds are expected to weaken; surface ocean temperatures are expected to warm fastest near the equator and more slowly farther away; the equatorial thermocline that marks the transition between the wind-mixed upper ocean and deeper layers is expected to shoal; and the temperature gradients across the thermocline are expected to become steeper.” However, they state “it is not yet possible to say whether ENSO activity will be enhanced or damped, or if the frequency of events will change.” Nor, it could be added, whether their several expectations will ever come to pass, as Collins et al. conclude “it is not clear at this stage which way ENSO variability will tip," adding, “as far as we know, it could intensify, weaken, or even undergo little change depending on the balance of changes in the underlying processes.”
An even more damning assessment of the state of the ENSO modeling enterprise was given by Jin et al. (2008), who investigated the overall skill of ENSO prediction in retrospective forecasts made with ten different state-of-the-art ocean-atmosphere coupled general circulation models (CGCMs)—which they describe as “coupled ocean-land-atmosphere dynamical seasonal prediction systems”—with respect to their ability to “hindcast” real-world observations for the 22 years from 1980 to 2001.
The results indicated, according to the 12 U.S., South Korean, and Japanese researchers, that almost all models have problems simulating the mean equatorial sea surface temperature (SST) and its annual cycle. In fact, they write, “none of the models we examined attain good performance in simulating the mean annual cycle of SST, even with the advantage of starting from realistic initial conditions,” while noting “with increasing lead time, this discrepancy gets worse” and “the phase and peak amplitude of westward propagation of the annual cycle in the eastern and central equatorial Pacific are different from those observed.” What is more, they find “ENSO-neutral years are far worse predicted than growing warm and cold events” and “the skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November.” They and others refer to this behavior as “the spring predictability barrier,” which gives an indication of the difficulty of what they are attempting to do.
Given these findings, Jin et al. conclude “accurately predicting the strength and timing of ENSO events continues to be a critical challenge for dynamical models of all levels of complexity,” revealing that even the best ocean-atmosphere CGCMs are presently unable to make reasonably accurate predictions of ENSO occurrence and behavior.
A paper by White and Liu (2008) finds that El Niño/La Niña pairs may be "phase locked" to the quasi-decadal oscillation, which is linked to the 11-year solar cycle. The authors performed harmonic analysis as a diagnostic on a time series of Pacific region sea surface temperatures (SSTs) from 1895-2005. They also gathered 110 years of data from a multi-century run of a coupled atmosphere-ocean Global Climate Model corresponding to the observations.
White and Liu report the existence of an 11-year QDO cycle in the observed record as well as strong peaks in the years associated with El Niño, especially at 3.6 and 2.2 years. When the authors ran the GCM without the 11-year solar forcing, however, the computer model could not reproduce the QDO in its SST record. When the GCM included this forcing, however, the model not only reproduced the QDO, it also showed the strong peaks in the 3.6 and 2.2 year period similar to observations. When they used the 3.6 and 2.2 year harmonics to compare to the observed record with the 11-year cycle filtered out, White and Liu found that this combination identifies reliably 26 of 32 El Niño events from 1895-2005. It is clear that models which include solar forcing have become more proficient at capturing interannual variability and that El Niño and La Niña onsets may be somewhat predictable even 10 years in advance.
In a comparison of 24 coupled ocean-atmosphere climate models, Latif et al. (2001) report that “almost all models (even those employing flux corrections) still have problems in simulating the SST [sea surface temperature] climatology.” They also note that “only a few of the coupled models simulate the El Niño/Southern Oscillation (ENSO) in terms of gross equatorial SST anomalies realistically.” And they state that “no model has been found that simulates realistically all aspects of the interannual SST variability.” Because “changes in sea surface temperature are both the cause and consequence of wind fluctuations,” and because these phenomena figure prominently in the El Niño-La Niña oscillation, it is not surprising that Fedorov and Philander (2000) conclude that current climate models do not do a good job of determining the potential effects of global warming on ENSO.
Human ignorance likely also plays a role in the models’ failure to simulate ENSO. According to Overpeck and Webb (2000), there is evidence that “ENSO may change in ways that we do not yet understand,” which “ways” have clearly not yet been modeled. White et al. (2001), for example, found that “global warming and cooling during earth’s internal mode of interannual climate variability [the ENSO cycle] arise from fluctuations in the global hydrological balance, not the global radiation balance,” and that these fluctuations are the result of no known forcing of either anthropogenic or extraterrestrial origin, although Cerveny and Shaffer (2001) make a case for a lunar forcing of ENSO activity, which also is not included in any climate model.
Another example of the inability of today’s most sophisticated climate models to properly describe El Niño events is provided by Landsea and Knaff (2000), who employed a simple statistical tool to evaluate the skill of 12 state-of-the-art climate models in real-time predictions of the development of the 1997-98 El Niño. They found that the models exhibited essentially no skill in forecasting this very strong event at lead times ranging from 0 to eight months. They also determined that no models were able to anticipate even one-half of the actual amplitude of the El Niño’s peak at a medium range lead-time of six to 11 months. They state that “since no models were able to provide useful predictions at the medium and long ranges, there were no models that provided both useful and skillful forecasts for the entirety of the 1997-98 El Niño” [italics in the original].
Given the inadequacies listed above, it is little wonder several scientists have criticized model simulations of current ENSO behavior, including Walsh and Pittock (1998), who say “there is insufficient confidence in the predictions of current models regarding any changes in ENSO,” and Fedorov and Philander (2000), who say “at this time, it is impossible to decide which, if any, are correct.” As a result, there is also little reason to believe that current climate models can correctly predict ENSO behavior under future conditions of changed climate.
Relationship to Extreme Weather
Changnon (1999) determined that adverse weather events attributed to the El Niño of 1997-98 negatively affected the United States economy to the tune of $4.5 billion and contributed to the loss of 189 lives, which is serious indeed. On the other hand, he determined that El Niño-related benefits amounted to approximately $19.5 billion—resulting primarily from reduced energy costs, increased industry sales, and the lack of normal hurricane damage—and that a total of 850 lives were saved due to the reduced amount of bad winter weather. Thus, the net effect of the 1997-98 El Niño on the United States, according to Changnon, was “surprisingly positive,” in stark contrast to what was often reported in the media and by some commentators who tend, in his words, “to focus only on the negative outcomes.”
Another of the “surprisingly positive” consequences of El Niños is their tendency to moderate Atlantic hurricane frequencies. Working with data from 1950 to 1998, Wilson (1999) determined that the probability of having three or more intense hurricanes during a warmer El Niño year was approximately 14 percent, while during a cooler non-El Niño year the probability jumped to 53 percent. Similarly, in a study of tropical storm and hurricane strikes along the southeast coast of the United States over the entire last century, Muller and Stone (2001) determined that “more tropical storm and hurricane events can be anticipated during La Niña seasons [3.3 per season] and fewer during El Niño seasons [1.7 per season].” And in yet another study of Atlantic basin hurricanes, this one over the period 1925 to 1997, Pielke and Landsea (1999) reported that average hurricane wind speeds during warmer El Niño years were about six meters per second lower than during cooler La Niña years. In addition, they reported that hurricane damage during cooler La Niña years was twice as great as during warmer El Niño years. These year-to-year variations thus indicate that, if anything, hurricane frequency and intensity—as well as damage—tend to decrease under warmer El Niño conditions.
Much the same story is being said of other parts of the world. In the North Indian Ocean, Singh et al. (2000) studied tropical cyclone data pertaining to the period 1877-1998, finding that tropical cyclone frequency there declined during the months of most severe cyclone formation—November and May—when ENSO was in a warm phase. In New Zealand, De Lange and Gibb (2000) studied storm surge events recorded by several tide gauges in Tauranga Harbor over the period 1960-1998, finding a considerable decline in both the annual number of such events and their magnitude in the latter (warmer) half of the nearly four-decade-long record, additionally noting that La Niña seasons typically experienced more storm surge days than El Niño seasons. And in Australia, Kuhnel and Coates (2000) found that over the period 1876-1991, yearly fatality event-days due to floods, bushfires, and heatwaves were greater in cooler La Niña years than in warmer El Niño years.
Zuki and Lupo (2008), when examining Southern South China Sea (SSCS) data on tropical storms and cyclones for interannual variability, found La Niña years were more active and El Niño years were less active than other years, and this result was significant at the 95 percent confidence level when examining the total sample. The variability of tropical storms and tropical cyclones of local origin was similar to that of the total sample. There was no apparent climatic variability (statistically significant) in the SSCS that could be attributed to interdecadal variability such as the PDO. A spectral analysis of the filtered climatological background variables such as SST, SLP, 200–850 hPa wind shear, 850 hPa divergence and 850 hPa vorticity showed that there was significant variability found in the 3–7 year period, which is consistent with that of the ENSO period.
Zuki and Lupo then examined a subset of the most active years (all La Niña and ‘‘cold’’ neutral years) versus those years with no tropical cyclone activity for the five years of warmest SSTs (predominantly El Niño years) and coolest SSTs. They found that during warm non-active SST years, tropical cyclone activity was likely suppressed as the low-level relative vorticity was considerably more anticyclonic, even though SSTs were about one standard deviation warmer and wind shears were similar to those of active years. The SSCS atmospheric environment for warm SST non-active years was drier than that of the active years, and did not exhibit a surface–500 hPa structure that would be as supportive of warm-core tropical cyclones. Most of these years were also ENSO years, and two thirds of all years with no activity were El Nino or warm neutral.
Apparently, even birds seem to know the dangers of La Niña vs. El Niño. In a study of breeding populations of Cory’s Shearwaters on the Tremiti Islands of Italy, for example, Brichetti et al. (2000) found that, contrary to even their hypothesis, survival rates during El Niño years were greater than during La Niña years.
Khider et al. (2011) developed a history of ENSO variability over a period of time that included both the Medieval Climate Anomaly and the Little Ice Age. This they did "by comparing the spread and symmetry of δ18O values of individual specimens of the thermocline-dwelling planktonic foraminifer Pulleniatina obliquiloculata extracted from discrete time horizons of a sediment core collected in the Sulawesi Sea, at the edge of the western tropical Pacific warm pool," and by interpreting the spread of individual δ18O values "to be a measure of the strength of both phases of ENSO," while the symmetry of the δ18O distributions was used by them "to evaluate the relative strength/frequency of El Niño and La Niña events."
Their results indicate that the strength/frequency of ENSO during the Medieval Climate Anomaly and the Little Ice Age was not statistically distinguishable and was comparable to that of the 20th century. However, ENSO during the Medieval Climate Anomaly was skewed toward stronger/more frequent La Niña than El Niño, while the Little Ice Age was characterized by an increase in the strength/frequency of ENSO events compared to the Medieval Climate Anomaly and the 20th century. With such discrepancies as these existing among real-world reconstructions of the effects of mean global temperature on the ratio of El Niños to La Niñas, it would appear that current climate model simulations are not capable of determining which of the similarly divergent scenarios is correct, or how close they may be to reality.
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