ENSOscope

Methodology

How the forecasts, the ENSO classification, the skill verification, and the teleconnection composites are produced.

ENSO index & 7-class classification

For each ensemble member we compute area-weighted NINO sea-surface-temperature indices (NINO3.4, NINO3, NINO4) and the NINO3 precipitation anomaly. Each index is detrended for global warming by regression on a Berkeley Earth global warming index (GWI), so the classification reflects internal tropical-Pacific variability rather than the forced warming trend.

The standardized NINO3.4 index z is mapped to seven classes:

  • Neutral - |z| < 0.5
  • Moderate El Niño / La Niña - |z| ≥ 0.5
  • Strong - NINO3 (El Niño) / NINO4 (La Niña) |z| ≥ 1.25
  • Extreme - |z| ≥ 1.75 and, for El Niño, a NINO3 precipitation anomaly ≥ 5 mm/day

The precipitation requirement is deliberate: a truly extreme El Niño is distinguished not by SST alone but by the eastward shift of deep convection into the eastern Pacific, captured by the NINO3 rainfall response.

Bias & amplitude correction - no statistical calibration

Each member's index is corrected to the 1993-2016 common hindcast period with a variance-rescaling bias correction (after Merryfield & Lee): the hindcast mean is removed and the variance is rescaled to match observations,

z = (anomaly − μhindcast) / σhindcast  for each start month and lead time.

This removes both the mean bias and the model's ENSO amplitude bias - seasonal models typically over-amplify ENSO by ~40% (the cold-tongue bias). Probabilities are then the raw fraction of ensemble members in each class. No Platt or isotonic calibration is applied: the spread of the bias-corrected ensemble is the probability.

On the 1993-2016 hindcast this reproduces observed extreme-event frequencies (extreme El Niño 1.7% modelled vs 2.1% observed; extreme La Niña 10.5% vs 7.6%), which a calibration layer would otherwise obscure.

Skill verification

Skill is shown directly as the temporal correlation between the hindcast ensemble-mean NINO index and observations, as a function of start month and lead time, for each NINO region including NINO3 precipitation - the standard anomaly-correlation metric used in seasonal-forecast verification. Correlation falls at longer leads and across the boreal-spring predictability barrier. See the Skill tab.

Teleconnection composites

The Teleconnections maps composite climate-impact indicators (heat: UTCI, WBGT, heatwave days; precipitation extremes: RX10day, consecutive dry days) by ENSO phase, from ERA5/CHIRPS observations and a CESM2 large ensemble. Fields are detrended for global warming and standardized by the ENSO standard deviation over 1980-2014; anomalies are shown relative to the neutral composite.

Because the teleconnection composites use a long observational/ensemble baseline, they use a different normalization from the forecasts (which are constrained to the 1993-2016 hindcast period).

Data sources and references

Every dataset used here is open and freely available. Please cite the original sources below if you reuse this material.