El Niño – Southern Oscillation (ENSO) Monitoring and Prediction atNOAA Climate Prediction Center (CPC) Michelle L’Heureux ENSO Team Lead NOAA Climate Prediction Center (CPC) March 2012
Outline• Monitoring and prediction products at NOAA CPC• Procedures on how we create and disseminate a forecast• Current skill of ENSO prediction models• How ENSO information is used in seasonal prediction
Mission of NOAA Climate Prediction Center We deliver climate prediction, monitoring, and diagnosticproducts for timescales from weeks to years to the Nation and the global community for the protection of life and property and enhancement of the economy.
What are the primary sources of skill in seasonal climate outlooks for the U.S.?• The El Niño-Southern Oscillation (ENSO)• Longer-term trends (use past 10-15 year average of temperatureand precipitation)• In general, boundary conditions like global sea surfacetemperatures (SST) and land surface variables (soil moisture, seaice, snow cover) are used
What datasets do we rely on to monitor and predict ENSO?• In situ observations: ships, TAO moored buoys, and drifting buoyslike Argo• Geostationary satellites like GOES and polar orbiting satellites likePOES and Suomi• Various gridded reconstructions of Sea Surface Temperature (SST)(e.g. ERSST, OISST)• Gridded Reanalysis products, which combine observations with afirst-guess model forecast to fill gaps (e.g. NCEP/NCAR, CFSR)• SST and reanalysis are run in “real-time.” For historical comparisons,homogeneity of the dataset is desired.
What products do we use to monitor ENSO? Weekly and monthly graphics of the tropical Pacific: * sea surface temperature (SST) * subsurface temperature * sea level pressure (i.e. SOI) * outgoing longwave radiation (OLR) * Various levels of winds (850/200-hPa) * velocity potential + streamfunction
What products do we use to predict ENSO?(1) Dynamical models: large number of observations, mathematical equations thatdescribe large-scale physical relationships, and parametrizations of smaller sub-gridfeatures (run on supercomputers)- NCEP Climate Forecast System (CFS): a tier-one coupled model (ocean andatmosphere interact freely)(2) Statistical models: uses a smaller number of observed variables (~1-3) and paststatistical relationships (run on a personal computer)- CPC Constructed Analog (CA), Canonical Correlation Analysis (CCA), and Markov(MKV)(3) Multi-model combinations: uses several dynamical and/or statistical models andcombining them through various statistical methods- CPC Consolidated Forecast Tool (“CON”): combines models using an ensembleregression based kernel distribution (see Unger et al., 2009)- IRI/CPC ENSO Prediction “Plume” which shows ~20+ dynamical and statisticalmodels and shows the dynamical and statistical model averages
Where are these products located?• ENSO products are on CPCs website (weekly + monthly updates):http://www.cpc.ncep.noaa.gov/products/precip/CWlink/MJO/enso.shtml•http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/enso_advisory/index.shtmlhttp://www.cpc.ncep.noaa.gov/data/indices/• NCEP Climate Forecast System ENSO prediction (daily update):http://www.cpc.ncep.noaa.gov/products/CFSv2/CFSv2seasonal.shtml• CPC “Consolidation (CON)” ENSO prediction (monthly update):http://www.cpc.ncep.noaa.gov/products/predictions/90day/tools/briefing/unger.pri.php• Ocean Monitoring products (+ monthly briefing):http://www.cpc.ncep.noaa.gov/products/GODAS/• Global Tropics Benefits/Hazards product for Week-1 and Week-2(weekly briefing):http://www.cpc.ncep.noaa.gov/products/precip/CWlink/ghazards/index.phphttp://www.cpc.ncep.noaa.gov/products/precip/CWlink/MJO/mjo.shtml
NOAAs Official ENSO Index:Oceanic Niño Index or “ONI” The ONI is a 3-month running average of SST anomalies in the Niño-3.4 region of the east-central equatorial Pacific Ocean. Retrospectively, we use 5 consecutive 3-month ONI > 0.5°C as an El Niño episode and ONI < -0.5°C as La Niña episode. Dataset: ERSSTv3b, which is a 2°x2° gridded SST reconstruction (Smith et al., 2008) using in situ data and statistical relationships to fill in gaps and create a continuous, homogeneous SST record. We only compute the ONI back to 1950 because data coverage is sparse prior to then.
The ENSO Alert System The ENSO Alert System provides the public with a succinct summary of the status of ENSO.An El Niño or La Niña Watch:Issued when the environment in the equatorial Pacific basin is favorable forthe development of El Niño or La Niña conditions within the next six (6)months.An El Niño or La Niña Advisory:Issued when El Niño or La Niña conditions in the equatorial Pacific basin areobserved and expected to continue.Final El Niño or La Niña Advisory: Issuedafter El Niño or La Niña conditions have ended.NA:The ENSO Alert System will not be active when El Niño or La Niñaconditions are not observed or expected to develop in the equatorial Pacificbasin.
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-3.4region 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 regionand an expectation that the 3-month ONI threshold will be met.ANDAn atmospheric response typically associated with El Niño/ La Niña over the equatorialPacific Ocean.
ENSO Alert System is updated with the “ENSO Diagnostic Discussion” NOAAs monthly ENSO Diagnostic Discussion is used to update the ENSO Alert System status. Also gives a short ~3 paragraph summary of the current observations and prediction of ENSO. Can click on status to get detailed information on Alert System definitions http://www.cpc.noaa.gov/products/ analysis_monitoring/enso_advisory /ensodisc.html
How is the monthly ENSO Diagnostic Discussion put together?Step #1: Send out forecaster spreadsheets to the ENSO team (9people). They are given ~2.5 days to consider analysis and then givetheir individual forecast.Step #2: All team member forecasts are combined. We show theprobability of each ENSO category out to ~8 leads.Step #3: Lead author writes the initial draft and it is iterated on by theinternal ENSO team. Eventually the draft is sent for comments byexternal NOAA employees outside of CPC.– If a change in status, NOAA leadership and public affairs arenotified.Step #4: The discussion is finalized and translated into Spanish byweather forecast office in San Juan.
What do the ENSO forecasters examine?Each forecaster has expertise in different areas and tends to weight differentaspects of ENSO. In general, the forecasters rely on:(1) Various ENSO-related monitoring products(2) Dynamical and statistical models and multi-model combinations(3) Their knowledge and experience of previous ENSO episodes
How is the forecasters input synthesized?Each forecaster fills out a spreadsheet with probabilities of three categories (ElNiño – Neutral – La Niña). All forecasts are averaged to create theprobabilities. See example below:
How is the monthly ENSO Diagnostics Discussion distributed to the Public?• Discussion is posted to CPC website. There is also an email listserv which has10,000+ subscribers (includes technical experts, media, general public, etc.).• Within hours, NOAA posts a press release (if a noteworthy change in ENSO) andarticles will appear on media outlets (Reuters, Bloomberg, AP, etc.)• NOAA/NWS has several public affairs officials who are available to arrangeinterviews radio, TV, newspapers, blogs….
How well do models predict ENSO?• Recently, dynamical models have slightly edged statistical modelsin forecast skill (Barnston et al. BAMS, in press)• Models have trouble with transition timing and predictingamplitude of ENSO events.• Stronger ENSO events tend to be better predicted than weakerones.• From decade-to-decade, ENSO prediction skill can vary widely dueto natural internal variability (can overwhelm forecast modelimprovements).• “Spring prediction barrier:” historically, forecasts before theNorthern Hemisphere Spring have low skill.• Intraseasonal variability (i.e. MJO) is not captured in most of thesemodels and these phenomenon can have considerable impact onENSO evolution.
Anomaly Correlations of ENSO models from 2002-2011 Orange/Red Shading: Higher correlations (more skill) White/Blue: Lower correlations ( 0 < r < 0.5) Light Grey: Negative correlations (very poor skill!) Lead Time (0-8 months) is on Y-axis and Target Season is on the X-axis The orange box designates the statistical models (the rest are dynamical)From Barnston et al. (BAMS, in press) “Skill of Real-Time Seasonal ENSO Model Predictions during2002-2011– Is our Capability Increasing?”
Anomaly Correlations and Root Mean Squared Error (RMSE) of ENSO models (all months from 2002-2011) Correlation by Lead Time RMSE (standardized units) by Lead Time1 1.20 0 8 0 Lead (months) 0 Lead (months) 8• At 0-month lead, ENSO model • For lead times greater than 2 months, RMSE of skill ranges from 0.75 to 0.95. “persistence” is greater than all models.• At 6-month lead, ENSO model • In general, models with high correlation tend to skill ranges from 0.1 to 0.7. have low RMSE.
Anomaly Correlations by Lead Time 1Top Panel:May-Sept At 6-month lead: Target ENSO model skill ranges from below zero to 0.55 during 0 boreal summer 0 8 1 ENSO model skill ranges from 0.45 to 0.9 during boreal winterBottom Panel: Nov-Mar Target 0 0 Lead (months) 8
Top Panel: 3-year sliding Correlation based on Hindcasts (1981-2010) Bottom Panel: 3-year sliding standard deviation of Niño-3.4 ENSO model skill decreased during 2002-10 (and in early- mid 1990s) in part due to the observed ENSO variability (lower amplitude ENSO events and more transitions between phases)
Input from ENSO updates are incorporated into other CPCproducts and services: Seasonal and Monthly Outlooks, DroughtOutlook, Fire Potential conference call, U.S. and Global Hazards,etc.
Who benefits from these climate outlooks?A few examples:1. NOAA climate outlooks provide big picture context for the weather events.This gives local TV weather forecasters and the private sector increasedopportunity to add value to their forecasts, and to tell a better story.2. Electric power companies have used climate forecasts for decades to makedecisions relevant to energy trading.3. U.S. federal government agencies, including FEMA, Department of Interior,Department of State, Military use them for planning purposes and resourceallocation.4. Local and State governments use them to allocate resources, e.g., California hasused prediction of El Nino to maintain drainage canals.
How is ENSO used in seasonal temperature and precipitation outlooks?First, some quick background on ourseasonal outlooks:Seasonal outlooks are probabilistic (given in %chance) reflecting the fact that confidence islower than a deterministic weather forecast.Precipitation and Temperature (P&T) outlooksare given for three (“tercile”) categories: aboveaverage/median – near average/median – belowaverage/medianProbabilities either reflect a “tilt in the odds” or“favoring” of a certain category or “EqualChances (EC)” which means no category isfavored (33.3% – 33.3% – 33.3%).
Some desired quantities of a seasonal outlook (or a probabilistic climate forecast, in general)“Reliable”: Over a long enough time period, the forecast probability reflects how often thatcategory actually occurred. – given a forecast for a 60% chance of above-averagetemperatures, one would expect above average temperatures to occur 60% of the time.“Sharpness:” a high probability issued for the correct observed category“Discrimination:” If outcomes are different, are the forecasts different? The probability ofa forecasted category should increase when that observed category occurs (probabilityshould decrease when the category occurs less)– If forecast is always the same regardless of actual observation, then no discrimination“Resolution:” If forecasts are different, are the outcomes different? The probability of aforecasted category should be different when the observed outcome is different.– If the outcome is always the same regardless of the forecasts, then there is no resolution.– Even if the forecast is always wrong, it has high resolution if it can distinguish betweenoutcomes.Great verification reference: http://www.cawcr.gov.au/projects/verification/
How is ENSO used in seasonal temperature and precipitation outlooks?ENSO impacts are already captured in dynamical climate model forecasts,like the NCEP Climate Forecast System (CFS) and the new National Multi-Model Ensemble (NMME).However, several statistical tools (that are not conditioned on ENSO phase)do not resolve ENSO impacts over the U.S.Some tools like Optimal Climate Normal (OCN), which captures thelonger-term trends, do not incorporate ENSO impacts at all.Thus, the seasonal forecaster will often weight the dynamical models more(over the statistical models) in the outlook during ENSO periods.During ENSO periods, the forecaster often uses historical ENSOcomposites and boxplots in association with the model guidance.
ENSO Composites and Boxplots for the U.S.http://www.cpc.ncep.noaa.gov/products/precip/CWlink/MJO/enso.shtml#composite Central Florida Precipitation (DJF)
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)
The IRI provides global seasonal climate outlooks outside of the United Stateshttp://portal.iri.columbia.edu/Recently, the IRI has become a close partner on NOAAs ENSO prediction team,assisting in the creation and dissemination of the ENSO outlooks.http://iri.columbia.edu/climate/ENSO/currentinfo/QuickLook.html
Summary• NOAA CPC provides routine monitoring and prediction products for ENSO, which are available on our website.• Once a month, the ENSO team determines the probabilities for each ENSO category, which provides the ENSO prediction for the upcoming ~8 seasons.• A variety of ENSO models (statistical and dynamical) are considered to create the forecast. Over the past 10 years, dynamical models are slightly more skillful than statistical models.• The ENSO outlook is incorporated (implicitly and explicitly) into CPC’ s monthly/seasonal temperature and precipitation outlooks and other products.
Since 1995, what has been the performance of U.S. Seasonal Temperature and Precipitation Outlooks? Temperature HSS Precipitation HSSMean = 22.3, Coverage = 50.9% Mean = 10.9, Coverage = 31.4% Hedike Skill Score (HSS) is the percent improvement over random chance. No skill forecast = 0 Perfect forecast = 100 Worse than random chance < 0
Other climate phenomenon impacting Peru?• On a shorter, “subseasonal” timescale (i.e. weekly forecasts out to ~1month): the Madden Julian Oscillation (MJO) Nov-Mar Precipitation Anomalies May- Sept Precipitation Anomalies
Timeline for Weekly ENSO UpdateUpdated each Monday (Tuesday if holiday):6:30am: Many graphics are produced using NCEP data via anautomated “cron” job7 – 8:30am: Put together ENSO powerpoint (edit text, reformatsome figures)8:30 – 10am: Reviewed by ~3 other CPC employees10 – 11am: Incorporate feedbackBy 11am EST: Finalize and upload to the CPC web (Powerpointand PDF)
Timeline for Monthly ENSO Diagnostics Discussion Released on the Thursday between the 4th-10th of the month at 9am EST/EDT. Mon. Tues. Wed. Thurs. Fri. Email Forecaster Initial Draft is Draft isWeek forecaster spreadsheets completed reviewed bybefore the spreadsheets due ENSO teamRelease Draft is Feedback Discussion is ENSO Discussion is emailed to from Outside finalized. released Outside Collaborators Spanish Email listservWeek of the Collaborators translation isRelease (Press Release if Spanish finalized by applicable) translation WFO San begins Juan