ENSOscope

Guide: how to use ENSOscope

A short walkthrough, from "what is this" to "what do I do with it." No background needed.

ENSOscope in one picture

The platform follows one chain: forecast the ENSO state, map where it shifts weather, see your region's impacts, and act on the lead time.

1 · The forecast2 · Teleconnections 3 · Your region4 · Act how strong,months ahead where it shiftsweather far away rain, droughtand heat prepare beforethe season

Using it in four steps

  1. See what's coming

    Check the ENSO outlook: how strong an El Niño or La Niña is likely, and how many months ahead.

    Open the Forecast →

  2. Find your region's risk

    Map where the event shifts rainfall, drought and heat, and drill down to your country.

    Open Teleconnections →

  3. Weigh the confidence

    See how reliable the forecast is at that lead and season, verified against the observed record.

    Open Skill →

  4. Act on the lead time

    Pre-position supplies, brief teams and trigger anticipatory-action plans in the months of warning.

The four steps, made real: a hospital in Kenya

Imagine you run a health facility in Kenya and you hear a strong El Niño is forecast. Here is exactly what to do, in about five minutes, and why each step matters.

  1. Start with the forecast

    Open the Forecast tab. The top line tells you in plain words what is coming, for example a strong El Niño strengthening over the next few months, and the bars show how sure the models are. Why it matters: a big event is likely, so it is worth preparing now.

  2. Find Kenya on the map

    Open Teleconnections, drag the globe to East Africa, and click Kenya to zoom in. Leave the "Source" on its default, that simply means the map is built from real, observed rainfall records.

  3. Check the rain

    Keep Wet selected and choose the season that matters to you, SON (the short rains, September to November). Blue and green mean wetter than usual, brown and red mean drier. For you: in a strong El Niño the Kenyan short rains usually turn wetter, which raises the risk of flooding and the diseases that follow it, such as cholera, malaria and Rift Valley Fever.

  4. Check the heat

    Switch the hazard to Heat stress. This map uses WBGT, which is simply a "feels-like" heat number that combines temperature and humidity. A high value means dangerous heat for the body, which matters most for patients, the elderly and young children.

  5. Check for dry spells

    Switch to Drought / Dry. This shows the longest run of dry days, so you can see whether other seasons bring dry spells that strain water supply and health services.

  6. Ask: can I trust it?

    Open the Skill tab. The grid grades how well the model predicted ENSO in the past: greener and closer to 1.0 means more reliable. If your lead time sits in the reliable part, you can act with confidence.

  7. Act on the lead time

    You now know, months ahead, that wetter short rains and flood risk are likely. So you pre-position cholera and clean-water supplies, check drainage and access routes, brief your teams, and trigger your anticipatory-action plan before the season, not during it. That early warning is the whole point of the tool.

Swap "Kenya" and "short rains" for your own context: the same six clicks work for any country, season and hazard.

Reading the forecast

The Forecast page opens with a plain-language outlook line, then a table of probability bars, one row per lead time. Lead time is how many months ahead the forecast looks (L1 = this month, L6 = six months out). Each bar is split by colour into the seven ENSO classes (from extreme La Niña in deep blue to extreme El Niño in deep red); the width of a segment is the share of model members in that class, which is the probability. Two forecast centres are shown (ECMWF SEAS5 and Météo-France); when they agree, confidence is higher.

Reading the teleconnection maps

A teleconnection is how a shift in the tropical Pacific reaches regions far away:

1 · The Pacific shifts2 · The atmosphere reacts3 · Your region feels it El Niño warms it,La Niña cools it winds and stormtracks move rainfall, droughtand heat change

On the Teleconnections globe, pick a phase, season and hazard; the map shows how that indicator typically departs from normal. Colour tells you the direction:

wetter or cooler than usual drier or hotter than usual little change

"Anomaly" is the difference from ENSO-neutral years (it isolates the El Niño / La Niña effect); "absolute" is the raw value during that phase. Robustness dots mark pixels where fewer than 60% of events agree on the direction, so treat dotted areas with caution. Click a country to drill all the way down to it. Behind the maps, observations are combined with a large climate-model ensemble so the patterns are robust even though few strong events sit in the observed record.

Reading the skill (how much to trust it)

Skill is measured by replaying past forecasts and scoring how close they were:

1 · Replay past forecasts2 · Compare to reality3 · Score how close replay the model'spast hindcasts what actuallyhappened correlation,0 (none) to 1 (perfect)

The Skill page grades how well the model has predicted ENSO in the past. The heatmap shows the correlation for every start month and lead time: 1.0 is perfect, about 0.6 and up is useful, near 0 is no skill. Skill is highest at short lead and fades with lead time and across the boreal-spring barrier. Below it, "the actual track" shows the model line against observations year by year, and the intensity panel asks whether the model gets the strength of an event right, not just its sign.

The words you'll see, in plain English

Every technical term on the platform, explained in one line. You do not need any of these to use the tool.

El Niño / La Niña (ENSO)
The natural warming (El Niño) and cooling (La Niña) of the tropical Pacific Ocean. It shifts weather worldwide, which is why it is worth watching.
Teleconnection
The far-away knock-on effect: how that Pacific change reaches your region as more or less rain, drought or heat.
Climate model
A computer simulation of the atmosphere and ocean, a "what if" laboratory used to study how El Niño changes weather.
Ensemble (and "large ensemble")
Running the model many times from slightly different starts. The spread between runs is the uncertainty; a large ensemble is many runs, which gives lots of El Niño examples to average over.
CESM2
The large-ensemble climate model we use. Why: the real world has had only a few strong El Niños, too few to draw a clear map, so the model supplies hundreds of events and the pattern becomes reliable.
CHIRPS
A long record of observed rainfall, from satellites and rain gauges. It is what actually fell.
ERA5
A long record of observed weather (temperature, humidity, and more), used here for the heat maps.
Why observations and a model together?
Observations are real but short and noisy for rare events; the model fills the gap with many events. When the two agree, the pattern is trustworthy.
RX10day
The heaviest 10-day rainfall total, a flood-risk indicator.
CDD (consecutive dry days)
The longest run of days with no rain, a drought or dry-spell indicator.
WBGT
A "feels-like" heat number that combines temperature and humidity. A high value means dangerous heat for the body.
UTCI
A similar "feels-like" comfort index.
Anomaly
The difference from normal (from ENSO-neutral years), so it isolates the El Niño or La Niña effect.
Lead time
How many months ahead the forecast looks. L1 is this month, L6 is six months out.
Skill / correlation
How closely past forecasts matched what actually happened, from 0 (no skill) to 1 (perfect).

For the full methods and data sources, see the Methodology page.