What is the nature of El Niño and how is it predicted?

What is the nature of El Niño and how is it predicted?
CLIM 101: Weather, Climate and Global Society What is the nature of El Niño and how is it predicted? Emilia Jin Lecture11: Sep 30, 2008

Contents What is El Niño and La Niña? Basics of El Niño
Impact of El Niño ENSO (El Niño and Southern Oscillation) Teleconnection Global and regional consequences Prediction of El Niño Benefits of El Niño Predicting Defining Monitoring Predicting

What is El Niño? (a) 1998 JFM SST [oC] (b) JFM SST Climatology [oC]
El Niño/La Nina events are in part characterized by warm temperature anomalies in the central to eastern equatorial Pacific. Ocean-Atmosphere Interaction Although El Niño and La Niña events are characterized by warmer or cooler than average sea surface temperatures in the tropical Pacific, they are also associated with changes in wind, pressure, and rainfall patterns. (a) Minus (b): 1998 JFM SST Anomaly [oC]

Marine ecosystem along the Ecuador and Peru coasts
What is El Niño/La Niña? In late 1800s, Fishermen coin the name El Niño to refer to the periodic warm waters that appear off the coasts of Peru and Ecuador around Christmas. El Niño was originally recognized by fisherman off the coast of South America as the appearance of unusually warm water in the Pacific ocean, occurring near the beginning of the year. El Niño means The Little Boy or Christ child in Spanish. This name was used for the tendency of the phenomenon to arrive around Christmas. La Niña means The Little Girl. La Niña is sometimes called El Viejo, anti-El Niño, or simply "a cold event" or "a cold episode". El Niño is often called "a warm event". These figures show the stark contrast between the marine ecosystem along the Ecuador and Peru coasts in normal (left) versus El Niño years (right). The warm, nutrient-poor surface waters brought by El Niños can sustain few phytoplankton, the tiny creatures that make up the base of the marine food web. As a result, fish, sea lions, and other sea animals must dive deeper in search of food. Sea birds scatter across the ocean, abandoning their young. Normal El Niño Marine ecosystem along the Ecuador and Peru coasts

What is El Niño/La Niña? La Nina (‘88.12) Normal (‘90.12)
El Niño/La Nina events are in part characterized by warm temperature anomalies in the central to eastern equatorial Pacific. Ocean-Atmosphere Interaction Although El Niño and La Niña events are characterized by warmer or cooler than average sea surface temperatures in the tropical Pacific, they are also associated with changes in wind, pressure, and rainfall patterns. El Nino (‘97.12)

Evolution of El Niño (1997-98 case)

Evolution of La Niña (1998-99 case)

Impact of El Niño ENSO (El Niño and Southern Oscillation) Teleconnection Global and regional consequences Prediction of El Niño Benefits of El Niño Predicting Defining Monitoring Predicting El Niño is an oscillation of the ocean-atmosphere system in the tropical Pacific having important consequences for weather around the globe.

Mean Tropical Pacific Ocean-Atmosphere Climatology (Normal Condition)
Wind effect 1: Net transport of trade winds in Pacific is nearly always from east to west. Hadely cell: The Intertropical Convergence Zone (ITCZ) is where the trade winds from the Northern and Southern Hemispheres converge into a narrow belt close to the equator, a result of the general Hadley circulation which dominates the tropics and subtropics. Walker cell: Westward at the surface and eastward in the upper troposphere  They cause a general westward motion of surface waters and warmest waters pile up at the western Pacific. The Intertropical Convergence Zone (ITCZ; General Circulation Lecture) is where the trade winds from the Northern and Southern Hemispheres converge into a narrow belt close to the equator, a result of the general Hadley circulation which dominates the tropics and subtropics. The winds have two main effects on the tropical Pacific ocean. They cause a general westward motion of surface waters and warmest waters pile up at the western Pacific. Net transport of trade winds in Pacific is nearly always from east to west.

The Intertropical Convergence Zone (ITCZ; General Circulation Lecture) is where the trade winds from the Northern and Southern Hemispheres converge into a narrow belt close to the equator, a result of the general Hadley circulation which dominates the tropics and subtropics. The winds have two main effects on the tropical Pacific ocean. They cause a general westward motion of surface waters and warmest waters pile up at the western Pacific. Net transport of trade winds in Pacific is nearly always from east to west.

Wind effect 2: Ekman Effect: Ekman upwelling due to wind divergence in the eastern tropical Pacific.

Upwelling (Coastal Zone Color Scanner) This satellite image from the Coastal Zone Color Scanner represents average conditions over several years. It shows the concentration of chlorophyll in the upper layer of the ocean, with higher amounts indicated by the warmer colors. Chlorophyll is produced by phytoplankton, the lowest level of the food web in the marine ecosystem. Phytoplankton "bloom" in the cold, nutrient-rich water that rises from the deep ocean into the sunlight, where photosynthesis can take place. (Image courtesy of Gene Carl Feldman, NASA, Goddard Space Flight Center.)

The sea surface is about 1/2 meter higher at Indonesia than at Ecuador. The sea surface temperature is about 8 degrees C higher in the west, with cool temperatures off South America, due to an upwelling of cold water from deeper levels. This cold water is nutrient-rich, supporting high levels of primary productivity, diverse marine ecosystems, and major fisheries. Rainfall is found in rising air over the warmest water, and the east Pacific is relatively dry. The observations at 110 W (left diagram of 110 W conditions) show that the cool water (below about 17 degrees C, the black band in these plots) is within 50m of the surface. The sea surface is about 1/2 meter higher at Indonesia than at Ecuador. The sea surface temperature is about 8 degrees C higher in the west, with cool temperatures off South America, due to an upwelling of cold water from deeper levels. This cold water is nutrient-rich, supporting high levels of primary productivity, diverse marine ecosystems, and major fisheries. Rainfall is found in rising air over the warmest water, and the east Pacific is relatively dry.

How the ocean affects the winds? The oceans and the atmosphere carry on a continuous dialogue. Each listens to what the other is saying and responds. Up to now we have eavesdropped on one side of that conversation: how the winds along the equator influence the slope of the thermocline and the intensity of the upwelling. But the resulting changes in sea-surface temperature will, in turn, have an effect on the winds. When the easterlies are blowing at full strength, the upwelling of cold water along the equatorial Pacific chills the air above it, making it too dense to rise high enough for water vapor to condense to form clouds and raindrops. As a result, this strip of the ocean stays conspicuously free of clouds during normal years and the rain in the equatorial belt is largely confined to the extreme western Pacific, near

El Niño and La Niña Strengthening and weakening of the Hadley and Walker circulations play a crucial role in reinforcing El Niño/La Niña perturbations to the mean tropical Pacific ocean-atmosphere climatology La Niña Stronger than average trade winds tend to push the warm surface layer of the ocean (upper few 100 meters) towards the western end, creating a thick warm layer. It has higher than average precipitation in Australia, India & Indonesia. El Niño: Weaker trades relax pressure on surface ocean layer & it starts to move back across Pacific from west to east, raising SST in the eastern tropical water, including Peru, with the zone of heavy rains shifting out over the central Pacific islands.

Developing El Niño Images & text from NASA Goddard Space Flight Center

El Niño and La Niña Normal conditions :The warmest water is found in the western Pacific, as is the greatest rainfall. Winds near the ocean surface travel from east to west across the Pacific (these winds are called easterlies ). El Niño conditions: The easterlies weaken, warmer than average sea surface temperatures cover the central and eastern tropical Pacific, and the region of heaviest rainfall moves eastward as well. La Niña conditions:Could be thought of as an enhancement of normal conditions. During these events, the easterlies strengthen, colder than average ocean water extends westward to the central Pacific, and the warmer than average sea-surface temperatures in the western Pacific are accompanied by heavier than usual rainfall. Normal conditions (top-most figure below). The warmest water is found in the western Pacific, as is the greatest rainfall. Winds near the ocean surface travel from east to west across the Pacific (these winds are called easterlies ). El Niño conditions (lower-left figure). The easterlies weaken, warmer than average sea surface temperatures cover the central and eastern tropical Pacific, and the region of heaviest rainfall moves eastward as well. La Niña conditions (lower-right figure). Could be thought of as an enhancement of normal conditions. During these events, the easterlies strengthen, colder than average ocean water extends westward to the central Pacific, and the warmer than average sea-surface temperatures in the western Pacific are accompanied by heavier than usual rainfall.  It oscillates with a periodicity of 2-7 years

El Niño and La Niña in the tropics

Southern Oscillation During an El Niño, sea level pressure tends to be lower in the eastern Pacific and higher in the western Pacific while the opposite tends to occur during a La Niña. This see-saw in atmospheric pressure between the eastern and western tropical Pacific is called the Southern Oscillation, often abbreviated as simply the SO (Sir Gilbert Walter, 1928).

El Nino/Southern Oscillation
3 month moving average NINO 3 Index = SSTA (5°N-5°S, 150°W-90°) SO Index =Standardized TAHITI SLPA - Standardized DARWIN SLPA NINO 3 Index SO Index Note these episodes were NOT spaced uniformly in time with a transition period of constant length from one to the other; thus the oscillator process clearly is complicated Over the past century, approximately 25% of the years could be classified as being in each of the two extreme ENSO states, assuming the six month mean value of SOI (June - November) diverged from the long-term mean by more than 0.5 standard deviation units.  The El Niño-Southern Oscillation, or ENSO for short. Often the term ENSO Warm Phase is used to describe El Niño and ENSO Cold Phase to describe La Niña. Center of Ocean-Land-Atmosphere studies

Global Impact Dense tropical rainclouds distort the air flow aloft (5-10 miles above sea level) but on a horizontal scale of thousands of miles. The waves in the air flow, in turn, determine the positions of the monsoons, and the storm tracks and belts of strong winds aloft (commonly referred to as jet streams) which separate warm and cold regions at the Earth's surface.

Rainfall Anomaly (a) 1997/8 DJF (b) DJF Rainfall Climatology
Minus (b): 1997/8 DJF Rainfall Anomaly

Global Impact Teleconnection
Teleconnections: physical relationships that result from the dynamics of atmospheric and oceanic waves.

Global Impact Northward Propagating Rossby-Wave Train
Tropical Convection (Trenberth, et al. 1998)

Global Impact PNA (Pacific/North America) Pattern 97-98 El Nino

Global Impact Jet Strem
Winds at the jetstream level (small arrows), five to fifteen miles above sea level, change their course between normal (above) and El Niño (below) winters. A ridge of high pressure over North America's west coast during El Niño winters keeps temperatures above normal in the orange region and steers storms that would otherwise pass through Washington and Oregon northward toward the coast of Alaska as indicated by the heavy arrow. El Niño also creates a favorable environment for storms to develop in the Gulf of Mexico, bringing heavy rains to much of the southern United States. An analogous strengthening of the westerlies in the Southern Hemisphere during its winter season brings heavy precipitation to parts of southern Brazil and northern Chile and Argentina (not pictured).

Global Consequences of El Niño
This schematic shows areas that have a consistent change in precipitation pattern linked to the first year of an El Niño event. The months in which the effect is seen are grouped by their first initials (e.g., OND is "October-November-December").

Global Consequences of El Niño

Global Consequences of El Niño/La Niña

Impacts of 1982/83 El Nino episode One of the two largest amplitude El Nino of this century. Most recent ( ) El Niño was comparably large as well. Droughts in Australia, India, Southern Africa. Floods in Peru, Ecuador, USA Gulf of Mexico states, & Colorado River basin. Collapse of coastal fishery in Peru (largest average annual catch of marine fish in world).

Impacts of 1982/83 El Nino episode The widespread impact of the El Niño is evident in this portrayal of extreme temperature events from 1982 to Months are grouped by their first initials (for instance, JJA is "June-July-August"). SST denotes sea-surface temperature.

Damage caused by1982/83 El Nino episode

Impacts of 1997/98 El Nino episode

Impacts of 1997/98 El Nino episode China: drought USA: Flood Peru: Flood Africa: drought

Regional Consequences of El Niño (United States)
Hurricanes: Below normal number of tropical storms/hurricanes in the Atlantic, although this does not imply any limits on the strength or location of any given tropical system. Monsoons: A drier-than-normal North American Monsoon, especially for Mexico, Arizona and New Mexico. Drought: A drier-than-normal fall and winter in the U.S. Pacific Northwest. Wintertime Storms: A wetter-than-normal winter in the Gulf Coast states from Louisiana to Florida, and in central and southern California if El Niño is strong (Gulf states cooler and wetter. California can be wetter or drier). Warmer Temperatures: A warmer than normal late fall and winter in the northern Great Plains and upper Midwest (Warmer winters across the northern US ) Pacific salmon and other fisheries disrupted

Regional Consequences of El Niño (United States)
In the El Niño winter, most El Niño winters are mild over western Canada and parts of the northern United States, and wet over the southern United States from Texas to Florida. El Niño affects temperate climates in other seasons as well. But even during wintertime, El Niño is only one of a number of factors that influence temperate climates. El Niño years, therefore, are not always marked by "typical" El Niño conditions the way they are in parts of the tropics.

Benefits of El Niño Prediction
Subtle changes in the interplay of wind and water in the tropical Pacific can affect local ecosystems and human lives in far flung regions of the globe. The Influence of ENSO on Climate Once developed, El Niño and La Niña events typically persist for about a year and so the shifted rainfall patterns associated with them typically persist for several seasons as well. This can have a significant impact on people living in areas of the tropical Pacific since the usual precipitation patterns can be greatly disrupted by either excessively wet or dry conditions. Even before we know when or how a particular El Niño or La Niña is going to evolve, we can say something about the regional and global effects it is likely to have due to teleconnections. Various flavors of ENSO on Climate In several parts of the tropics, and some areas outside of the tropics, these seasonal shifts are fairly consistent from one El Niño and La Niña event to the next. It is important to remember, however, that no two El Niño or La Niña events are identical and that the seasonal shifts in temperature and precipitation patterns associated with them can vary from one event to the next. Thus, when an El Niño or La Niña develops, it does not guarantee that regions which are typically affected by them will be affected, only that there is enhanced probability that this will be the case. In other locations, the impact of El Niño can have two or more different "flavors." For instance, California can experience very wet conditions (such as in , , and ) or drought ( and ), depending on how far east the ENSO-related rainfall extends in the tropical Pacific. Predicting which flavor will dominate for a given event is difficult, because very small changes in SSTs can become magnified to produce large differences in rainfall patterns outside the tropics. Precipitation in California is clearly connected to ENSO, but it may vary greatly from one El Niño to the next.

ENSO, Climate, and Society
Simple Picture The More Realistic Picture

Benefits of El Niño Prediction
Seasonal climate forecasts made possible The persistence of tropical sea surface temperature (and rainfall) patterns (such as those associated El Niño and La Niña) plays a fundamental role in making seasonal (3-month) climate forecasts possible. In the absence of El Niño and La Niña, seasonal climate forecasts are still possible because unusually warm or cold sea surface temperatures in other parts of the tropics can still occur. Other influences on seasonal climate While ENSO is the largest known source of year-to-year climate variability, there are other known causes of seasonal climate variability that have nothing to do with ENSO: Tropical Oceans (Atlantic Ocean, Indian Ocean), snow cover and soil wetness, etc. For example, unusually warm or cold sea surface temperatures in the tropical Atlantic or Indian ocean (not related to ENSO) can cause major shifts in seasonal climate in nearby continents. For example, the sea surface temperature in the western Indian Ocean has a strong effect on the precipitation in tropical eastern Africa, and ocean conditions in the tropical Atlantic affect rainfall in northeast Brazil. When snow cover is above average for a given season and region, it has a greater cooling influence on the air than usual. Soil wetness, which comes into play most strongly during the warm time of the year, also has a cooling influence. These two factors, while noticeable in their influence on climate, do not have as strong an effect as the tropical oceans do.

Effects of SST Anomaly

Global Impact Northward Propagating Rossby-Wave Train
Tropical Convection (Trenberth, et al. 1998)

The “Charney” Diagram Observations Theory Modeling

El Niño prediction depends on observed data and numerical models.
Reliable data on existing conditions and realistic numerical models that project this picture forward in time are at the crux of researchers continuing efforts, not only to understand El Nino, but also to predict when future events will arise and what their impacts will be.

ENSO Predictability and Prediction
ENSO phenomena: Walker (1924), Bjerknes (1969), Wyrtki (1975), Rasmussen and Wallace (1983) ENSO theory: Philander, Yamagata and Pacanowski (1984); Schopf & Suarez (1988), Battisti & Hirst (1989) ENSO simulation: MacCreary (1976), Busalacchi and O’Brien (1981), Philander and Seigel (1985) ENSO prediction: Cane et al. (1986), Zebiak and Cane (1987)

ENSO Prediction Encouraged by the progress of the past decade, scientists and governments in many countries are working together to design and build a global system for observing the tropical oceans, predicting El Niño and other irregular climate rhythms, making routine climate predictions readily available to those who have need of them for planning purposes, much as weather forecasts are made available to the public today. Scientists are now taking our understanding of El Niños a step further by incorporating the descriptions of these events into numerical prediction models (computer programs designed to represent, in terms of equations, processes that occur in nature). The results thus far, though by no means perfect, give a better indication of the climatic conditions that will prevail during the next one or two seasons than simply assuming that rainfall and temperature will be "normal."

Operational ENSO Observing System
Long term operational support for Pacific Ocean observations that are the foundation of skillful ENSO forecasts. Shown here are some of the components of the ocean observing system that are being deployed in support of El Niño prediction. The red dots are automatic tide gage stations. The yellow squares and diamonds show the locations of moored buoys, which monitor surface wind and other weather elements, as well as water temperatures at several levels below the ocean surface. They operate continuously for months at a time without human intervention. The pink arrows depict the tracks of drifting buoys which measure water temperature and reveal the motion of the surface water. The blue lines represent the tracks of merchant ships that take ocean soundings. Many of these observations are sent directly to weather prediction centers around the world via satellite.

ENSO Observing Experiment
A vast array of ships, aircraft, and buoys collected oceanographic and atmospheric data throughout the western tropical Pacific as part of the Tropical Ocean and Global Atmosphere Program's Coupled Ocean - Atmosphere Response Experiment (TOGA-COARE) from November 1992 through February Shown is one of the 70 TAO instrument buoys being deployed as part of TOGA. (NOAA image.)

Defining ENSO The NINO Regions
Indices based on sea surface temperature (or, more often, its departure from the long-term average) are those obtained by simply taking the average value over some specified region of the ocean. There are several regions of the tropical Pacific Ocean that have been highlighted as being important for monitoring and identifying El Niño and La Niña. The most common ones are the NINO regions:

Defining ENSO NINO1+2 (0-10S, 80-90W). The region that typically warms first when an El Niño event develops. NINO3 (5S-5N; 150W-90W). The region of the tropical Pacific that has the largest variability in sea-surface temperature on El Niño time scales. NINO3.4 (5S-5N; 170W-120W). The region that has large variability on El Niño time scales, and that is closer (than NINO3) to the region where changes in local sea-surface temperature are important for shifting the large region of rainfall typically located in the far western Pacific. NINO4 (5S-5N: 160E-150W). The region where changes of sea-surface temperature lead to total values around 27.5C, which is thought to be an important threshold in producing rainfall .

Defining ENSO

Defining ENSO For widespread global climate variability, NINO3.4 is generally preferred, because the sea surface temperature variability in this region has the strongest effect on shifting rainfall in the western Pacific. And in turn, shifting the location of rainfall from the western to central Pacific modifies greatly where the location of the heating that drives the majority of the global atmospheric circulation. Conventional definition of El Niño : “as a phenomenon in the equatorial Pacific Ocean characterized by a positive sea surface temperature departure form normal in the NINO 3.4 region greater than or equal in magnitude to 0.5C averaged over three consecutive months” (NOAA).

Table 1. El Niño and La Niña Years
Defining ENSO El Niño Year La Niña 1 1951 2 1953 3 4 5 6 7 8 9 10 11 12 13 1993 14 15

Predicting ENSO Types of models for predicting ENSO
The prediction of ENSO is based on models that predict sea-surface temperatures in the equatorial Pacific Ocean. There are two general types of these models. The first type is called a "dynamical model“(numerical model) which consists of a series of mathematical expressions that represent the physical laws that govern how the ocean and atmosphere behave. To make a forecast, dynamical models are given the current conditions in the ocean and atmosphere and then a computer "does the math" to determine what the future conditions (out to six months or more in advance) will be. The second general type of model is a "statistical model". These models use observations of the past to make predictions of the future. To make a forecast with a statistical model requires a long history of observations by as much as 30 to 50 years. This long record of observations is used to identify key features of the ocean and atmosphere that often occurred prior to subsequent changes in sea surface temperatures in the tropical Pacific.

ENSO Prediction Past Recent Tropical SST Anomaly Forced Rossby wave
Anomalous Tropical Convection Extratropical Circulation Subtropical Jet change Improvement of physical parameterization : PBL, Convection. Transient activity change Advances in the computing power : High resolution Eddy Streamfunction Transient vorticity forcing Past Recent

Intermediate Couple Model
ENSO Prediction Intermediate Couple Model SST Atmosphere Ocean

Intermediate Couple Model
ENSO Prediction Intermediate Couple Model

Climate System Modeling Atmospheric General Circulation Model
Physical processes Basic Equations Dynamics

Climate System Modeling
Cloud resolving cumulus convection scheme Extremely high resolution Couple model Advenced Super computer : CRAY X1, X1E : 18Tflops : half power of the Earth simulator Parallel programming based on MPI Advanced supercomputing Parallel programming Atmospheric GCM Integrated Climate and Environment Model Environmental Model Oceanic GCM

ENSO Forecasts for Dynamic Models
Jun 2005 – March 2007 Center of Ocean-Land-Atmosphere studies

JFM Warm (83&98) minus Cold (89&99) Composite
NCEP Reanalysis SST (shaded) and U200 (contours) 850 hPa band-passed (2-10 d) V’T’ CGCM Forecast 10-member Ensembles (1 Dec ICs)

Predicting ENSO Advantages and disadvantages of prediction models
Dynamical models are usually thought to be more scientific, because they explicitly use the physical equations and thereby attempt to accurately capture events in terms of their physical causes and effects. Dynamical models are able to handle unprecedented climate events, since the basic physics would apply equally well to novel situations as to familiar situations. Statistical models can only see new situations as extrapolations of historically observed ones, and run the risk of missing any new "rules of the game" that may come about only in the new situation. Dynamical models require much greater computer power than statistical models, because the physical equations are more complex than statistical equations. (We are talking about the difference between a PC and a supercomputer!) While many oceanographers and atmospheric scientists expect dynamical models to prove superior as computer power increases and more is learned about ENSO physics, this has not yet been clearly demonstrated.

Forecast Skill of NINO3.4 Index
Remarkably, MME forecasts have better skill than individual models The correlation skill of the tier-1 multi-model ensemble (MME) forecast of NINO3.4 SST anomalies reaches 0.86 at the 6-month lead. It beats the performance of both persistence and the dynamic-statistical model. The forecast skill depends strongly on season, ENSO phase, and ENSO intensity. In this plot, we can see that February and May initial conditions have a relatively fast drop of skill compared with August and November cases with some suggestion of a ‘spring prediction barrier’

Current Limit of Predictability of ENSO (Nino3.4)
Potential Limit of Predictability of ENSO 20 Years: 4 Times per Year: Jan., Apr., Jul., Oct. 6 Member Ensembles Kirtman, 2003

Anatomy of ENSO Irregularity: El Niño and La Niña events tend to alternate about every three to seven years. However, the time from one event to the next can vary from one to ten years. The strength of the events, as judged by the pressure anomaly, varies greatly from case to case. The strongest El Niños in this record occurred in and Nonlinearity: Sometimes El Niño and La Niña events are separated not by their counterparts, but by rather normal conditions.  El Niño (or La Niña) years, therefore, are not always marked by "typical" El Niño conditions the way they are in parts of the tropics.

THANK YOU! ANY QUESTIONS?

CHRONOLOGY OF EVENTS IN THE HISTORY OF UNDERSTANDING EL NIÑO AND LA NIÑA
Late 1800s: Fishermen coin the name El Niño to refer to the periodic warm waters that appear off the coasts of Peru and Ecuador around Christmas. 1928: Sir Walter Gilbert describes the Southern Oscillation, the seesaw pattern of atmospheric pressure between the eastern and western Pacific Ocean. 1957: Scientists learn that El Niño affects the entire Pacific Ocean. 1969: Jacob Bjorknes, of the University of California, Los Angeles, links the Southern Oscillation to El Niño. 1975: Klaus Wyriki, of the University of Hawaii, establishes that an eastward flow of warm surface waters from the western Pacific causes sea surface temperatures to rise in the eastern Pacific. 1976: Researchers use a computer model to demonstrate that winds over the far western equatorial Pacific can cause sea surface temperature changes off Peru. 1982: A severe El Niño develops in an unexpected manner but its evolution is recorded in detail with newly deployed ocean buoys. 1985: Several nations launch the Tropical Ocean-Global Atmosphere (TOGA) program, a 10-year study of tropical oceans and the global atmosphere. 1986: Researchers design the first coupled model of ocean and atmosphere that accurately predicts an El Niño event in 1986. 1988: Researchers explain how the lag between a change in the winds and the response of the ocean influences termination of El Niño and the onset of La Niña. : The array of instruments monitoring the Pacific, plus coupled ocean-atmosphere models, enable scientists to warn the public of an impending El Niño.

What is the nature of El Niño and how is it predicted?

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