The name El Niño (referring to the Christ child) was originally given by
Peruvian fishermen to a warm current that appeared every year around
Christmas. What we now call El Niño seemed to them like a stronger
version of the same event, and the usage of the term evolved over time until it
only referred to the irregular strong events. It wasn't until the 1960s that
people started realizing this was not just a local Peruvian occurrence, but was
associated with changes over the entire tropical Pacific and beyond. In
effect, El Niño was too big to be seen as the mega-event it is; it just seemed
like a lot of unconnected unusual weather events around the world.
The name El Niño as scientists now use it refers to the warm phase of a
large warm/cold oscillation in the water and atmosphere of the Pacific region.
The complete phenomenon is known as the El Niño/Southern Oscillation,
abbreviated ENSO. The warm El Niño phase typically lasts for
approximately eight to 10 months. The entire ENSO cycle usually lasts about
three to seven years, and often includes a cold phase (known as La Niña)
that may be similarly strong, as well as some years that are neither abnormally
hot nor cold. However, the cycle is not a regular oscillation like the change
of seasons; it can be highly variable in strength and timing. At present we do
not fully understand what causes these changes in the ENSO cycle.
The Southern Oscillation was named by Sir Gilbert Walker in 1923, who noted
that "when pressure is high in the Pacific Ocean it tends to be low in the
Indian Ocean from Africa to Australia." This was the first recognition that
changes across the tropical Pacific and beyond were not isolated phenomena but
were connected as part of a larger oscillation. Walker was Director of
Observatories in India and was mostly concerned with variations in the Indian
monsoon and the huge consequences that too much or too little monsoon rain
could have in India.
The first modern scientific description of the mechanics of El
Niño/Southern Oscillation was made by Professor Jacob Bjerknes of the
University of California, Los Angeles in 1969; our knowledge of the Earth's
largest and most powerful weather engine is still incomplete.
Why is El Niño frequently described as a disruption of the usual
situation in the tropical Pacific?
To understand El Niño, you have to think about the normal tradewind
system in the tropical Pacific. The sun heats the equatorial regions more
strongly than the rest of the globe, so a lot of heated air tends to rise from
the surface there, to be replaced by inflow from the subtropics. Have you ever
tried to walk straight across a merry-go-round while it was revolving? Then
you know something seemed to push you sideways as you walked, and your actual path was
curved diagonal line. That sensation of sideways motion is due to something called
the Coriolis Effect, and it applies to both a merry-go-round and the spinning Earth.
On Earth, inflowing winds from higher latitudes try to rush straight to the equator,
but the Coriolis force turns these inflows to the right in the northern hemisphere and to the
left in the southern, resulting in the great tradewind belts that blow towards
the equator and westward over the width of the tropical Pacific. In the ocean,
these winds tend to push the surface water towards the west, so sea level at
Indonesia is usually about 50 centimeters higher than at the South American
coast, which gives an idea of the power and steadiness of the tradewinds. As
surface water is pushed west, cooler subsurface water is drawn up to the
surface in the eastern equatorial Pacific, making the entire region about ten
degrees Fahrenheit cooler than in the west. This cool
water from the deep layers of the ocean is full of nutrients, and supplies food to the
plankton, which form the base of the eastern Pacific food chain. That's why the
eastern Pacific supports vast communities of fish and other sealife, as well as
birds who eat fish.
During normal conditions, as seawater journeys west, the sun steadily heats the
layer of surface water over a huge area west of the International Dateline,
known as the West Pacific Warm Pool. This air is also very humid because the warm water it's been riding over
has been steadily evaporating. When this air rises in the west, heavy
precipation falls over Indonesia and Southeast Asia as the moisture
condenses back out as rain. As water condenses from vapor to liquid, it
throws off heat. It is this heat—which can be vast—which energizes
the atmosphere, creating storms.
The warm pool is one of the major driving forces of world climate. Its heat
strengthens the rising motion in the west and thereby reinforces the westward
winds of the tradewind system. The rising, moisture-laden air pumps heat and
water vapor into the upper atmosphere, where it can be carried great distances.
The huge source of heat helps set the path of the jetstreams (stormtracks) that
control and direct temperate-zone weather, much as a boulder in a riverbed
determines the pattern of water flow, including wavy motions and ripples that
extend well downstream of the rock. In effect, a huge mass of rising warm
moist air acts like a big boulder stuck up into the atmosphere, deflecting
the rivers of air flowing in the midlatitude jet streams. The effects of this
ripple outward to affect much of the world's weather.
During El Niño events, the normal pattern relaxes. The tradewinds
weaken, particularly west of the Dateline, and the piled-up water in the west
sloshes back east, carrying the warm pool with it. The region of rising air
moves east with the warm pool, and so does the pumping of heat and moisture
into the upper atmosphere. Deflections in the normal
wind patterns distort the usual paths of the jetstreams,
pushing them from their accustomed places, which eventually causes the changes in
the weather that the rest of the world experiences. With weakened tradewinds,
the deep cool waters coming up in the east slow their ascent.
The food supply for plankton dwindles, and the effect travels up the food chain.
When eastern sea surface temperature becomes warm, the east-to-west
temperature contrast is small, and so the tradewinds weaken even further,
leading to a complete collapse with essentially flat conditions across the
entire equatorial Pacific.
The most severe effects are found close to the equator. The usual pattern of
deserts in Peru and Galapagos, and heavy rainfall over Indonesia and the west
Pacific, reverses. Forest fires can occur in Indonesia (as has been happening
in recent months, exacerbated by deliberate burning) and Australia, while Peru
suffers flooding, with accompanying epidemics of cholera and other sewage-borne
diseases. The food chain in the rich upwelling region is disrupted, so fish die
off, which means hardship for the birds, mammals and people that survive on
that stock. The warmer water near Central America spawns more and stronger
hurricanes, which can go as far west as Hawaii. The entire sequence of the
event lasts about one year, and events are usually separated by 2-7 years, in
an irregular and not-well understood pattern.
Should we take El Niño forecasts with a grain of salt?
Remember that El Niño is not the only thing that influences weather.
There are many other fluctuations and systems—some of which we are just
discovering—and the weather we experience results from the tumultuous
interplay of all these systems. Most of the interactions are poorly understood,
particularly the longer-term ones, all the way up to Ice Ages, which may
operate over periods of hundreds of thousands of years. As we get longer and
longer records we become aware of more and more complexity, more cycles.
Successive El Niños occur during different general conditions, at
different times of year, and therefore have different total effects. Therefore,
you can't simply speak of the isolated effects of El Niño on weather in,
say, San Diego. There is only the ever-changing combination of influences. That
is the main reason why we cannot produce reliable long-term forecasts.
Scientists study El Niño partly for its own effects, but also partly as
an example of how this kind of climate oscillation interacts with the rest of
the climate system. (In other words, El Niño is a great weather and
climate laboratory.) We know there are many such oscillations, and we would
like to be able to fit the whole picture together. We hope that what we learn
about the climate system from studying El Niño will help us understand
other, less obvious, variability.
Why don't you see much in the news about the causes of El Niño?
The reason that you don't see much publicity about the causes of El Niño
is that we don't understand the origins of the event. We do, however, have a
pretty good understanding of how it evolves once it has begun, and that gives a
useful ability to make forecasts six to nine months ahead for some regions.
That is the information you see because that is the present state of reasonably
secure knowledge. Of course, there are a variety of theories, and many
scientists are working on various aspects of the genesis, which would
presumably extend the predictive skill out another few months or even years.
At several points over the last 20 years, we thought we had decent
theories of what causes El Niño. Unfortunately (or perhaps fortunately
for those who like scientific challenges), nature has shown that those theories
were incomplete at best. For example, during the mid-1980s, a group at Columbia
University developed a fairly simple theory and wrote a computer program to
make predictions based on it. This was successful in predicting the 1986-87 and
1991-92 events almost a year in advance, and they were breaking out the
champagne. Then along came the event of 1993, followed by another in 1994-95,
and most prominently the present event, none of which developed according to
the ideas in their theory. The champagne went back in the fridge.
The main reason this is so difficult is that El Niños involve the full
complexity of ocean-atmosphere interaction on a global scale. That's about as
complex as it gets. We have developed a reasonably good understanding of how
the atmosphere works (at least in theory), once the sea surface temperature
(SST) that drives the atmospheric circulation is known. (We are somewhat
further behind when it comes to the ocean, which is much harder to observe).
Atmospheric models work well enough to make short-term weather forecasts,
because, in the short term, you can pretend the ocean is unchanging,
due to the slow speed of ocean changes. But, when you consider longer-term phenomena like El
Niño, it is not enough to specify the SST; you also have to think about how
the ocean will evolve with the winds, and then how the altered ocean will
modify the winds, and so on, in many tricky and sensitive feedback loops. We
are just beginning to be able to see how these disturbances work, and then only
in very idealized cases. Remember that for a long time meteorologists only
talked to meteorologists, and oceanographers only to oceanographers. Now we are
really at the initial stages of being able to think about these coupled
Nevertheless, it seems to me that we are able to do a lot of good for society
even at our present stage of ignorance, since even without knowing what drives
El Niño, we can recognize it, and then know (largely from statistics of
past events) what the effects will be on regions far removed from the tropical
On one hand, no one doubts that the entire ocean-atmosphere system is
interconnected. Each El Niño event occurs against the background of
existing conditions, including the positions of the mid-latitude jetstreams. In
addition, new theories of the slow changes of the tropical ocean circulation
point to a key role for water masses that come from the subtropics or higher
latitudes. These water masses are part of a global-scale overturning
circulation, in which waters sink at high latitudes (due to evaporation or
winter cooling making them more dense), and travel through the depths of the sea
to the equator, where they well up to the surface. Then the waters flows back
poleward on the surface, warming under the sun to complete the cycle as they
replenish the subtropical sinking zones. The whole round trip can take decades.
Researchers have shown that the
sinking water masses can have different temperature and salinity properties,
which contribute to the longer-term dynamics of the system, and it's thought
that overlaps of these slow changes may be the reason why some periods have
many El Niños (like the 1990s) while others don't, or why some El
Niños are stronger than others.
On the other hand, simplified computer models of the equatorial
ocean-atmosphere system commonly develop multi-year climate cycles similar to El Niño.
This indicates that at least the basic phenomena are a natural rhythm of a wide
ocean spanning the equator, and theory bears this out. The prevailing
sentiment among climate researchers is that the mid-latitude influences
referred to above can change individual El Niños, but that basically,
some form of oscillation would occur regardless of influences. In short, El
Niño is an organic phenomenon.
However, at present we don't know how El Niños begin. Therefore the
tropical/extra-tropical debate cannot be said to be resolved. This topic is
the subject of much current research.
Statistical forecasts tie observed weather conditions with records of
conditions in other El Niños. Typically, sea surface temperature (SST)
in key regions of the equatorial Pacific is used to define "El Niño
periods." Alternatively an index known as the "Southern Oscillation Index"
(SOI) is used, based on the surface barometric pressure difference between
Tahiti and Darwin, Australia, on opposite sides of the Pacific. The advantage of the SOI is that records at those
two locations go back almost a century, while we have only a few decades of SST
observations in the mid-ocean. Finally, these records are indexed to, for
example, rainfall in California, allowing a statistical forecast of the likelihood of
reoccurrence of heavy rains in that region during an El Niño. These are
the most common types of forecast, the kind that you see in newspapers and TV
weather reports. In some places, such as the U.S. Gulf Coast, the correlations
are quite robust and the statistical forecast is fairly reliable. In others the
correlations are weak, and their predictive value is low.
The strength of statistical forecasts is that they are based on events that
actually did occur, but they can fail; because of the complexity of the
climate system, El Niño doesn't repeat itself. It is not very accurate
to isolate the specific effects of El Niño by taking the average of
previous events. (The average daytime high temperature for Chicago in July may
be 88 degrees, but what does that tell you about how warm it will be at 4:00 PM
on the next Fourth of July? Not much.) Anyway, different conditions every
year blur the statistics and reduce confidence in such a forecast.
Another problem with statistical forecasts is that we do not have good,
long-term records of many of the important quantities of interest. Once you go
back further than the mid-1950s, the ocean records are sparse and ambiguous,
making it hard to determine which are strong El Niño years and which are
weak (or even whether or not there really was an El Niño at all). Using
only the good data, you see only a handful of events, and the statistics become
quite unreliable. (If you weighed three apples in a bushel, you'd probably
still not know the weight of the average apple very well.) Many of the
differences among statistical forecasts reported in the media are due to the
choice of different averaging periods, or in other words, thin records. Of
course, they don't usually tell you that.
Dynamical forecasts are based on computer models—equations, really—which are
especially useful because specific processes can be analyzed and dissected in
idealized and simplified terms. In other words, a good computer model focuses
on what's important, and ignores what's not. For a while during the 1980s it
appeared that much of the El Niño cycle was tied to "planetary waves"
bouncing around the Pacific, and these could be decently simulated in a simple
model. However, this theory failed to predict the series of El Niño
events during the 1990s, and it appears that we must simulate the full
complexity of ocean-atmosphere interaction. Remember Einstein's saying? "We
must strive to make the world as simple as possible, but not more simple."
Modeling El Niño and other climate fluctuations is a task of huge
difficulty. The hardest part is not
knowing what to include, but what to leave out.
Nevertheless, many feel that as computers become faster and as our
understanding of the physical processes of weather becomes better, we will rely
more and more on the dynamical forecasts. They have the tremendous advantage of
working forward from actual present conditions, and so avoid the problem of
statistically averaging a number of events that differ in important details. In
addition, for low-frequency events like El Niño, it might take centuries
to observe enough occurrences to really improve statistical confidence.
There is a strong El Niño in the tropical Pacific this year.
Such events often, but not always, lead to heavy winter rains in southern California.
The truth is we do not know very well what will happen in California. We can be
more confident about some areas (like the Gulf Coast), where the response to El
Niño is pretty steady from one El Niño to the next, but
California can go either way, so no forecast can be taken too seriously. There
definitely is a good possibility of flooding. That's more than a roll of the
dice, but less than a certainty. What action you take depends on how you would
be affected. It's similar to earthquake preparedness. It makes sense to have
your earthquake supplies up to date and handy, but you can't spend your whole
life preparing for disaster. One thing can be said reliably; if it's not this
El Niño that produces flooding in southern California, it will be
another one not too far off.
One of the best forecasts is what we call "persistence." That is, when a
pattern is established it tends to remain. If the winter begins rainy, then
probably it will continue as such. Lots of rain in November is a good
indication that this El Niño has set up the jetstream to direct moisture
to California (as opposed to further east), and it would then be more likely to
continue. There was above-normal rain in California this November, but not a
deluge, so that may tell you something about later in the winter.
One of the hardest things for the lay public to get good information on is
what's behind various forecasts. A lot of what you hear is based on statistics
of past events. But remember, there haven't been very many El Niños
since we started realizing it is a global phenomenon, and not just a bunch of
unconnected weirdness. There have been 10 since 1950 and only six since 1970.
That's not a very good basis for statistics, particularly when we observe that different events evolve in different ways. It's like measuring
five kids in a classroom. Would that give you a good estimate of the average
height of all the kids? Maybe you'd happen to get the five shortest. So
statistical forecasts (noting that El Niño "usually" brings rain to
California) are not on a good foundation. When you surf the Web sites looking
for information, you can easily find statistics telling you different things.
It doesn't mean they're wrong, or trying to mislead, it just means that we have
a very small sample of a highly variable phenomenon.
A final thing to remember is that El Niño is not the entire story. Many
other oscillations are going on at the same time, so whatever the effects of El
Niño, we see them all jumbled up with many other signals. Since we
really have only a relatively few years of decent observations, picking these
signals apart is partly a matter of guesswork.
How do models used to predict El Niño work? How accurate are they?
Computer models of the climate system let us examine the results of ideas that
are too complicated for the human mind to crunch through. For an (overly
simple) example, we know that the sun heats ocean surface water during the day
and cools off at night. Say the amount of heating is determined just by the
length of the day. That means the water would heat up in the summer, since
the days are long and the nights short, and cool off more during the winter. We
could write these ideas down in equations, specify the values of heating due to
various amounts of sunlight, use a computer to solve the equations, and get
a plot of what the predicted water temperature would be at any time in the
future. We might have one calculation for each square kilometer of ocean, or if
we're really being precise, one for every square hectare (1000 square meters,
about 2.5 acres). The ocean is huge, so that is going to be millions and
millions of equations. A computer can do millions of such calculations in a
second; I can manage about one a minute. Computers have changed the way we
study weather for just this reason.
In reality, of course, we have much more complicated ideas of how the climate
system works. For example, there are clouds, and the clouds not only block the
sun during the day, cooling off the water, but also tend to insulate it at
night, preventing cooling. Do these balance out? Depends on how the amounts of
cooling and insulating are specified. Numbers that describe these relationships
have to be estimated from observations, then programmed into the model. In
addition, clouds are not independent of the water temperature; for example very
warm water tends to produce a lot of evaporation, leading to tropical
rainstorms. But if there is wind, the clouds may be blown somewhere other than
where they were formed. So the pattern of where clouds occur can quickly become
extremely complicated. Since we have already specified in our model that the
clouds affect the water temperature, that, in turn, means the pattern of water
temperature gets more complicated, which feeds back on the cloud pattern, and
Things continue to get more complicated. When air rises over warm water, other
air must flow in from the sides to make up the deficit. Therefore if water
temperatures are not uniform, there will be wind. When there is wind, this
causes ocean currents, which moves water of various temperatures around. If the
winds are such as to move the surface water away from some region, colder water
from below may be pulled up. Cold water weighs more than warm water and the
difference in density also causes currents to flow.
So you can see that computer models of the climate system may start with some
fairly simple ideas, but quickly become extremely complicated in practice. We
use the world's biggest computers in this field, and still they're not fast
enough. As we get more observations, we learn more about the system, and
modelers are constantly struggling to represent these processes more
accurately. One of the main difficulties is that while we know pretty well how
the system will change over a short time (like a day or so), once we ask for
longer predictions we come up against the problem that we don't know the
initial state perfectly. Therefore there will be some error in the forecast
since it won't be starting from exactly where the real system starts from. For
a one-day forecast, the error probably won't be too great; perhaps some clouds
in the wrong place. If we run the model further into the future, soon those
wrong clouds will produce erroneous water temperatures, which will produce an
even worse cloud pattern, and pretty soon the whole solution is garbage. Because we
can never know the exact state of every bit of air and water,
there is an inherent limit to the predictability of a system as complicated as
the ocean-atmosphere system.
In general, I don't take forecasts seriously more than a few months in advance.
For example, right now most of the models are suggesting that El Niño
will wind down by early summer 1998, and next winter will be a strong La
Niña (the opposite phase, in which it is abnormally cold in the tropical
Pacific and many of the effects of El Niño are reversed). Frankly, I
don't have much confidence in a forecast that far ahead. However, the
scientists who make these forecasts do it publicly as a means of "ante-ing up"
to the forecast competition. Believe me, this is a real competition. Everyone
wants to be the first to develop a successful El Niño model. And you
can't not publish a forecast and then claim later that you had it right.
So you see a lot of long-range forecasts, but that doesn't mean that anyone,
including the authors, necessarily has much confidence in them. Unfortunately,
with the media frenzy about El Niño this past year, many of these
experimental forecasts were trumpeted around the newspapers and TV shows as if
they were truth.
Why can't I find any information about links between El Niño and
The reason you won't find much information connecting El Niño and global
warming is that we (meaning the mainstream scientific community) don't really
have too much useful to say about it at this point. While we know that El
Niño occurs on the background of the large-scale climate, and assume
that as the background changes that some aspects of El Niño might also
change, we are nowhere near the ability to say what those changes might be. So
rather than speculate about such a politically charged subject, we usually keep
our mouths shut.
The above cautionary note does NOT, however, mean that one should discount the
possibility. Since we see that El Niños in different years vary greatly
in their strength it appears the process may be quite sensitive to changes in
the background state.
Much of the uncertainty in the question of whether greenhouse warming is
affecting the ENSO cycle revolves around the problem of how one would measure
the statistical significance of changes in recent El Niños. Some say
that the string of warm El Niño events during the 1990s are evidence that a general
warming trend is starting to change the weather; others say that these
variations are within normal limits. The fact is we have only a few events to
talk about, which means there is no statistical rigor to any argument for or
against this idea. It is simply shooting the breeze. We won't have good
statistics about El Niño for another hundred years or so (perhaps even
longer if it is truly chaotic), so I don't bother with such arguments at all.
To me the interesting stuff is the dynamics and thermodynamics anyway, and on
that front we stand a chance of making progress in my lifetime.
Is there a scale for the intensity of El Niño, like the Richter scale
or the typhoon classification?
The most widely used scale is known as the Southern Oscillation Index (SOI),
which based on the surface (atmospheric) pressure difference between Tahiti and
Darwin, Australia, on opposite sides of the Pacific. It was noted as far back as the 1920s that these two
stations were anticorrelated, so that when Tahiti pressure is high, Darwin
pressure is low. This reflects the very large scale of the phenomena, since one
would not usually expect such a close relation between such faraway places.
When Tahiti pressure is high, it indicates that winds are blowing towards the
west (normal tradewinds), and when it is low, that winds are blowing to the
east (El Niño). A major advantage of the SOI is that time series at
these two locations extend back to the 1880s, so we can see the distribution of
El Niño events back much further than we can see in records of ocean
temperatures. The SOI is given in normalized units of standard deviation, a way
of judging the distribution ("bell-shaped curve") of all the recorded
intensities. This can be used as an intensity scale. For example, SOI values
for the 1982-83 El Niño were about 3.5 standard deviations, so by this
measure that event was roughly twice as strong as the 1991-92 El Niño,
which measured only about 1.75 in SOI units. By this standard, the present El
Niño is about as strong as 1991-92. However, the sea surface temperature
anomaly is larger than in 1982-83, and some say that is a more important
measure. This shows that there is no single number that summarizes the
intensity of events.
Anomalies mean the normal temperatures in each location have been subtracted
from the observed values at the time of the plot. (When you put your hand on
your forehead, thinking you might have a fever, you are checking for an anomaly.) An
anomaly plot therefore shows whether the water is warmer or cooler than its
normal state, and the normal state is different in different places. For
example, if on some (very unusual!) day the temperature was 20°C
(68°F) everywhere in the ocean, that would be normal along the coast of
Baja California, but anomalously warm in Seattle, and anomalously cold in the
Philippines. An anomaly map for this hypothetical flat 20°C day would show
positive values in mid latitudes and negative values in the tropics.
In the tropical Pacific, normal sea surface temperatures (SSTs) are much colder
in the east than in the central/western Pacific (say 23°C (73.4°F) in
the east vs. 29°C (84.2°F) in the west. Further, the cold water in the
east is concentrated in a band along the equator. That may sound strange, since
we usually think of the equator as warm, but upwelling of deeper, and hence
colder, water occurs on the equator in the east, resulting in the cool water
During El Niño, water of about 28°C is found to stretch across the
Pacific along the equator from Indonesia to Peru. This is a near normal temperature
in the central and western Pacific, but it gets progressively
more anomalous along the equator to the east, because it's usually colder
there. That's why there appears to be a wedge.
What have been the major new developments in instruments for measuring the
temperature of the ocean?
There have been two major developments. First, satellite coverage has gotten
way better. Second, we've developed a simple, inexpensive design for buoys that
can be deployed in mid-ocean and remain active for a year or more. The Pacific
Marine Environmental Laboratory in Seattle maintains the TAO (Tropical
Atmosphere Ocean) buoy array across the equatorial Pacific that measures sea
surface temperatures, surface winds, air temperature and humidity, and
subsurface temperature (sometimes currents, too) in the upper 500 meters of the
ocean, at about 70 locations from Galapagos to Australia. Together, all the
buoys constitute a HUGE instrument, and it lets us see things we never saw
The buoys transmit data daily (in some cases, hourly) to orbiting satellites,
which feed the data to the weather forecast network, and also to users on the
Internet, for research and prediction. The big advantage of moored buoys is
their high temporal resolution...that is, their ability to show us what is
happening while it's happening. Also, knowledge of subsurface conditions is
critical to understanding how the sea surface temperature is likely to change
over the next few weeks and months.
By combining satellite and buoy data, we get a better calibration of both. For
the first time, we are now visualizing on graphic displays what's going on,
rather than trying to make sense of reams of numbers on computer paper. Which
is, if you think about it, a very natural way for humans to make sense of
Do volcanoes or sea floor venting cause El Niño?
The idea that volcanoes cause El Niño events originally gained prominence
because of the eruption of Mt. Chichon in Mexico in February 1982
(preceding the El Niño of 1982-83), and the eruption of Mt. Pinatubo in the
Philippines in June 1991 (preceding the El Niño of 1991-92). However, when
the incidence of El Niños is compared to the incidence of volcanic
eruptions it becomes clear that the relationship is coincidental. There
have been numerous large volcanic eruptions around the world and almost as
many El Niños, and there's almost always an eruption at some time preceding
any El Niño. Scientists are now convinced that this relation is
Certain experiments bear this out. For example, several computer models
predicted the onset of the 1991-92 event as early as January 1991, based on
observations of the ocean and atmosphere, well before Pinatubo. That
indicates that the ocean-atmosphere system was already generating the El
Niño, and Pinatubo occurred coincidentally. Computer models integrating the
equations of fluid motion and the flow of heat routinely produce El
Niño-like variability completely on their own. This shows that El Niño is a
natural variability mode of the ocean-atmosphere system, rather like a
thunderstorm is. Experiments to examine the modes of variability of the
climate system suggest that it's prone to instabilities, ranging from storm
systems lasting a few hours or days, to El Niño, with a cycle of several or
more years, to longer-term fluctuations that we are just beginning to
explore, measured in decades on up to thousands of years.. There is no need
to invoke volcanoes.
None of this is to say that volcanoes don't affect the climate. They most
certainly do, and since El Niños occur against the background existing
climate, there is little doubt that volcanic eruptions that eject large
amounts of dust into the stratosphere can modify the El Niños, possibly in
important ways. (There is a big distinction between "modify" and "cause" El
As far as deep-ocean vents modifying the ocean temperatures, researchers
now think that this source of heat does contribute to the long-term
evolution of the ocean state. We can trace the chemical signatures of sea
floor venting carried for quite a distance in the deep currents. Those
traces are useful for estimating the deep flows, which are difficult and
expensive to measure directly since they are so slow. However, we observe
that the heating due to deep venting becomes diluted in the vast reaches of
the abyssal ocean and therefore does not make quick changes in the ocean
state. These affects are felt over decades or centuries, not on the
relatively rapid time scale of El Niño.
It is indeed tempting to look for simple causes of complex oscillations
like the El Niño cycle. Unfortunately (or perhaps fortunately for those of
us who like scientific challenges), it seems that the ocean-atmosphere
system is well capable of generating these oscillations on its own, and the
task now is to understand how this happens. Volcanoes and sea floor venting
are part of the slowly changing background state to which phenomena like El
Niño are added, and they increase the complexity of the task.
Come back February 10 to find out more about how scientists are visually
mapping El Niño.