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The El Niño/ Southern Oscillation (ENSO) Cycle

The El Niño/ Southern Oscillation (ENSO) Cycle. Michelle L’Heureux NOAA Climate Prediction Center (CPC) August 2013. (1) Brief Overview of the Ocean and Atmosphere (“Normal” vs. ENSO conditions) (2) The ENSO Cycle: A Coupled Ocean- Atmosphere System

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The El Niño/ Southern Oscillation (ENSO) Cycle

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  1. The El Niño/ Southern Oscillation (ENSO) Cycle Michelle L’HeureuxNOAA Climate Prediction Center (CPC) August 2013

  2. (1) Brief Overview of the Ocean and Atmosphere (“Normal” vs. ENSO conditions) (2) The ENSO Cycle: A Coupled Ocean- Atmosphere System (3) ENSO Teleconnections and Global Impacts (4) ENSO Monitoring and Prediction at NOAA Climate Prediction Center (CPC) Outline

  3. ENSO in a Nutshell • An irregular, naturally occurring cycle (every 2-7 years) of warm (El Niño) or cold (La Niña) conditions in the tropical Pacific Ocean. • Ocean changes occur alongside changes in the tropical atmosphere circulation & rainfall • On average, events last 9-12 months (La Niñas can persist longer) and peak in strength during N. Hemisphere winter Red colors: above average sea surface temps (SST) Blue colors: below average sea surface temps (SST) Niño 3.4 sea surface temperatures (SST): Primary ENSO index or time series

  4. “Normal” SST: Major Features Atlantic Warm Pool Pacific Warm Pool Cold Tongues

  5. “Normal” SST: Extremes in the Annual Cycle Equatorial SSTs are warmest in April Equatorial cold tongues are strongest in Jul.-Oct.

  6. Sea Surface Temperatures:El Niño vs. La Niña Equatorial cold tongue is stronger than average during La Niña, resulting in negative SST anomalies Equatorial cold tongue is weaker than average or absent during El Niño, resulting in positive SST anomalies

  7. Decadal Changes in Structure and Amplitude of El Niños 2009-2010 The stronger El Niño events in the 80s and 90s resembled EP El Niño Since ~2000, El Niño has often resembled CP El Niño Central Pacific (CP) El Niño = Warm Pool El Niño = El Niño Modoki = Date Line El Niño Eastern Pacific (EP) El Niño = Cold Tongue El Niño = Conventional or Canonical El Niño

  8. “Normal” Precipitation: Major Features Storm Tracks ITCZ SPCZ SACZ

  9. “Normal” Precipitation: Extremes in the Annual Cycle

  10. Precipitation:El Niño vs. La Niña Enhanced rainfall occurs over warmer-than-average waters during El Niño. Reduced rainfall occurs over colder-than-average waters during La Niña.

  11. Sea Level Pressure: “Southern Oscillation” El Niño: Positive SLP anomalies over the western tropical Pacific, Indonesia and Australia. Negative SLP anomalies over eastern tropical Pacific, middle and high latitudes of the North Pacific, and over U.S. Opposite pattern for La Niña. The pressure see-saw between the eastern and western tropical Pacific is known as the “Southern Oscillation.”

  12. Low-Level Winds & Thermocline Depth: El Niño vs. La Niña La Niña: stronger-than-average easterlies lead to a deeper (shallower)-than-average thermocline in the western (eastern) eq. Pacific. El Niño: weaker-than-average easterlies lead to a deeper (shallower)-than-average thermocline in the eastern (western) eq. Pacific.

  13. Animation of Subsurface Temperatures: 1996-1999

  14. (1) Brief Overview of the Ocean and Atmosphere (“Normal” vs. ENSO conditions) (2) The ENSO Cycle: A Coupled Ocean- Atmosphere System (3) ENSO Teleconnections and Global Impacts (4) ENSO Monitoring and Prediction at NOAA Climate Prediction Center (CPC) Outline

  15. ENSO depends on coupling between the ocean and the atmosphere over the tropical Pacific Ocean. The Bjerknes feedback is a positive feedback between the ocean and atmosphere over the equatorial Pacific Ocean. (1) Stronger SST gradients  stronger winds. COLD WARM wind Water that travels westward over the wide expanse of the Pacific, warms up due to solar insolation If surface water blows from east to west, cold water from the deep ocean upwells to the surface ocean to replace water upwelling (2) Stronger winds  stronger SST gradients

  16. What is “Normal?” (2) Warm water heats the atmosphere and makes it rise, so low-level trade winds blow towards warm water to fill the gap. Subsiding air occurs in the eastern basin. Warm Cold Winds and Sea Surface Temperature are COUPLED. The SSTs determine the winds and vice versa. (1) Easterly trade-winds help push warm water to the western Pacific and upwell cold water in the eastern Pacific Ocean. Warm Cold

  17. Enhanced “La Niña” • Convection becomes stronger over the far western Pacific Ocean/ Indonesia and more suppressed in the central Pacific. More Convection Stronger Stronger Upwelling Warm Cold Cold becomes more shallow • Easterly trade winds strengthen • Thermocline becomes more shallow and the cold water upwelling increases in the eastern Pacific. Warm Cold

  18. NOTE: Location of the warmest SSTs (>28°C) determines where tropical convection will be located. “El Niño” • Convection shifts eastward over the central and/or eastern Pacific Ocean. Convection becomes suppressed over the far western Pacific/ Indonesia. Warm Warm Cold • Easterly trade winds weaken • Thermocline deepens and the cold water upwelling decreases in the eastern Pacific. Warm Cold

  19. Features of the ENSO Cycle • Irregular cycle with periods of warm (El Niño) and cold (La Niña) conditions • Events tend to occur every 2-7 years • Generally episodes form during the spring or summer, peak during the winter, and decay the following spring. • La Niña episodes can last multiple years (1-3 years). Less common for El Niño, which last up to ~18months. • Often stronger El Niño events are followed by La Niña • Larger SST departures with strong El Niño episodes (relative to strong La Niñas).

  20. Different Theories of ENSO (1) ENSO is a stable, or damped, mode that requires stochastic (“weather”) forcing in order to occur. - why ENSO events are so different from event to event. - ENSO may have strict predictability limits because successful prediction would require skillful forecasts of the short-term atmospheric trigger - implies a key role for shorter-term phenomenon such as the Madden Julian Oscillation (MJO). MJOs are often associated with “westerly wind bursts” that help drive the system forward. (2) ENSO is an unstable, naturally oscillatory mode that is self-sustained. - Helps explain why ENSO has a 2-7 year period. ENSO is “made irregular” by weather perturbing this oscillation. - implies that ENSO is predictable at longer lead times. Explains why models may be able to predict ENSO onset many months in advance.

  21. (1) Brief Overview of the Ocean and Atmosphere (“Normal” vs. ENSO conditions) (2) The ENSO Cycle: A Coupled Ocean- Atmosphere System (3) ENSO Teleconnections and Global Impacts (4) ENSO Monitoring and Prediction at NOAA Climate Prediction Center (CPC) Outline

  22. ENSO Teleconnections Tropical convection/heating can lead to “wavetrains” that can influence the global circulation. EXAMPLE: Eastward expansion of warm sea surface temperatures during El Niño can result in an anomalous eastward shift of convection. Enhanced thunderstorm activity in the central Pacific will perturb the upper-level flow resulting in an anticyclonic “couplet” straddling the equator. Poleward of the ridge, an anomalous trough forms in the central North Pacific Ocean. Schematic from Horel and Wallace (1981)

  23. Global El Niño Impacts Impacts are generally more extensive during the northern winter.

  24. Global La Niña Impacts Mid-latitude impacts generally occur during the winter season (NH – DJF; SH- JJA).

  25. Global ENSO Regression and Correlation Maps http://www.cpc.ncep.noaa.gov/products/precip/CWlink/MJO/enso.shtml#composite • Gridded temperature anomalies (CPC GHCN) and precipitation anomalies (CPC Unified Precipitation) associated with the standardized Niño-3.4 index from 1948-2010. • Assuming linearity so regression anomalies showing sign of El Niño (reverse for La Niña)

  26. (1) Brief Overview of the Ocean and Atmosphere (“Normal” vs. ENSO conditions) (2) The ENSO Cycle: A Coupled Ocean- Atmosphere System ENSO Teleconnections and Global Impacts (4) ENSO Monitoring and Prediction at NOAA Climate Prediction Center (CPC) Outline

  27. ENSO Monitoring and Prediction at NOAA Climate Prediction Center (CPC) • NOAA CPC definitions for ENSO • ENSO Alert System • Forecasting ENSO and Model Skill • Climate Change and ENSO

  28. Evolution since 1950 El Niño neutral La Niña

  29. Creation of the NOAA ENSO Outlook • CPC provides weekly (every Monday) + monthly monitoring and prediction products for ENSO, which are available on our website: • http://www.cpc.ncep.noaa.gov/products/precip/CWlink/MJO/enso.shtml • Indices: http://www.cpc.ncep.noaa.gov/data/indices/ • The ENSO Diagnostics Discussion is released on the Thursday between the 4-10th of each month. Concurrent with that release, the “ENSO Alert System” and the official outlook is updated. El Niño or La Niña Watch: Favorable for development of ENSO within the next six (6) months. El Niño or La Niña Advisory: conditions are observed and expected to continue. Final El Niño or La Niña Advisory: conditions have ended. NA: Not Active To receive monthly notification: ncep.list.enso-update@noaa.gov

  30. What is the criteria for an ENSO Advisory? The ENSO Alert System is based on El Niño and La Niña “conditions” that allows the NOAA to be able to issue watches/ advisories in real-time. The value of the ONI is to define episodes retrospectively. El Niño conditions: one-month positive SST anomaly of +0.5 or greater in the Niño-3.4 region and an expectation that the 3-month ONI threshold will be met. La Niña conditions: one-month negative SST anomaly of −0.5 or less in the Niño-3.4 region and an expectation that the 3-month ONI threshold will be met. AND An atmospheric response typically associated with El Niño/ La Niña over the equatorial Pacific Ocean.

  31. Forecasting ENSO • ENSO Forecasters rely on: • (1) Real-time data from the equatorial Pacific Ocean (collected from buoys, satellites, etc) and their knowledge of previous ENSO episodes • (2) Dynamical models: mathematical equations combined with current observations and run on a computer • NCEP Climate Forecast System (CFS): a “coupled” computer model (ocean and atmosphere interact) • (3) Statistical models: use observations of the past to make predictions of the future • Consolidated Forecast Tool (“CON”): statistically combines different models to take advantage of independent information provided by each model

  32. How is the probability of ENSO determined? Each forecaster individually provides probabilities of three categories (El Niño – Neutral – La Niña). Individual forecasts are averaged to create the “Consensus” probabilities and form the basis for the diagnostics discussion.

  33. Primary features of ENSO model performance • Recently, dynamical models have slightly edged statistical models in forecast skill (see Barnston et al. BAMS, 2012) • Models have trouble with transition timing and predicting amplitude of ENSO events. • The transition to stronger ENSO events tends to be better predicted than transitions to weaker ones. • “Spring prediction barrier:” historically, forecasts before the Northern Hemisphere Spring have low skill.

  34. Prediction of Niño-3.4 Index by NCEP CFS from 2002-2011 (Post-processing/statistical corrections applied to model data after 2009) Orange/Red Shading: Higher correlations (more skill) White/Blue: Lower correlations ( 0 < r < 0.5) Light Grey: Negative correlations (very poor skill!) 8 Lead Time (mths) • Model skill is reduced during the N. Hemisphere spring when ENSO often emerges or decays • CFS prediction improves to ~0.8 to 0.9 correlation for prediction of the N. Hemisphere winter (after ~June) • RMSE (amount of error in amplitude) is ~0.5°C to 1.0°C in Niño-3.4 4 0 Target (season you are predicting) From Barnston et al. (BAMS, 2012)

  35. Anomaly Correlations of ENSO models from 2002-2011 (from the IRI/CPC ENSO Prediction Plume) The orange box designates the statistical models (the rest are dynamical) • Skill for mid-year targets: Dynamical Models > Statistical models • -- Dynamical models have better initial conditions and ability to detect changes on shorter timescales than statistical models (often trained on monthly or seasonal data) • For NH winter target, statistical and dynamical models are comparable. From Barnston et al. (BAMS, 2012)

  36. Can other climate patterns overrule ENSO impacts? • Short answer: Absolutely. There is uncertainty associated with seasonal forecasts even during strong ENSO episodes. • This is why it is important to emphasize that the existence of ENSO means a “tilt in the odds” toward particular temperature/precipitation anomalies. These anomalies are never guaranteed, which is why climate outlooks are always probabilistic. 2-meter Temperature anomalies from Reanalysis data for Oct. and Dec. 2009 (during a moderate-strong El Niño). This circulation and temperature pattern was reflective of a very strong negative Arctic Oscillation (AO) pattern. L’Heureux et al. (2010, GRL)

  37. Will ENSO change due to Climate Change? Models don’t agree on how ENSO changes. ENSO feedbacks will likely change with warming, but hard to say which terms will dominate or cancel out. IPCC-AR4: “No consistent indication at this time of discernible changes in projected ENSO amplitude or frequency in the 21st century.” Continued ENSO variability in the future even with anthropogenic climate change See Ref. Collins et al. (2010), Vecchi and Wittenberg (2010), Guilyardi et al., (2009)

  38. Summary • ENSO is a naturally occurring coupled ocean-atmosphere phenomenon that has global impacts • Equatorial Pacific fluctuates between warmer-than-average (El Niño) and colder-than-average (La Niña) conditions • The changes in SSTs affect the distribution of tropical rainfall and atmospheric circulation features (Southern Oscillation) • Changes in intensity and position of jet streams and storm activity occur at higher latitudes • Monitoring and predicting ENSO is a key part of CPC’s monthly/seasonal temperature and precipitation outlooks • Models do not agree on how ENSO will change with anthropogenic climate change.

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