How do I simulate an El Niño?

Open this page and use the live Search & Rescue Grid tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.

Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.

Can I use my own numbers?

Absolutely — every input is adjustable, and with data import you can drive an El Niño from your own measurements.

Use case · powered by Search & Rescue Grid

Search & Rescue Grid for an El Niño

Simulate an El Niño live in your browser. This runs the real Search & Rescue Grid solver — adjust the inputs, watch it respond instantly, and export the result. No install, no account.

For:Students Researchers Educators Engineers Hobbyists & Makers K-12 Students First Responders

Viewshed

open full solver →

Viewshed / Line of SightLive

what can you see from here?

Controls

Presets

Observer position

Observer height (m)

A viewshed marks every point visible from an observer, hidden behind intervening ridges. Scanning outward, a point is seen only if its angle above the horizontal exceeds every closer obstacle — so terrain shadows fall behind hills. Raising the observer reveals far more. It is essential for siting cell towers, wind turbines, scenic overlooks, and military positions.

▶ Run in Python

Data Inspector

Visible cells0

Coverage0%

Observer height10 m

Governing equation

d_{horizon} = 2 R h = 2 \cdot 6371 km \cdot 10 m \approx 11.3 km

Reading this result: At 10 m the observer sees over closer bumps but taller ridges still cast blind spots — coverage lands near 0%.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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Spatial Interpolation

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Spatial Interpolation (IDW)Live

filling the gaps between measurements

Controls

Presets

Power parameter

Given scattered measurements — rainfall gauges, soil samples, air-quality sensors — inverse-distance weighting estimates values everywhere in between. Each sample's influence falls off with distance raised to a power: a low power gives smooth, blended surfaces; a high power makes each sample dominate its neighborhood in sharp bull's-eyes. The workhorse of GIS mapping.

▶ Run in Python

Data Inspector

Samples8

Power p2.0

Characterbalanced

Governing equation

\overset{z}{^} (x) = \frac{\sum _{i} w _{i} z _{i}}{\sum _{i} w _{i}}, w_{i} = \frac{1}{d _{i}^{2.0}}

Reading this result: At power 2.0 nearby samples win but distant ones still contribute — a balanced surface between smooth and spiky.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

or unlock everything with Pro →

About this simulation

The full Search & Rescue Grid tool models an El Niño with the same numerics engineers and scientists use — running entirely client-side. Change any parameter and the result updates in real time, so you can build intuition, check a design, or teach the concept without spreadsheets or installs.

More you can do with Search & Rescue Grid

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Other ways to simulate an El Niño

Energy Balance for an El Niño Daisyworld for an El Niño Milankovitch Cycles for an El Niño Tsunami Propagation for an El Niño Carbon Cycle for an El Niño Earthquake Shaking for an El Niño

Frequently asked questions

How do I simulate an El Niño?: Open this page and use the live Search & Rescue Grid tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.
Is it free?: Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.
Can I use my own numbers?: Absolutely — every input is adjustable, and with data import you can drive an El Niño from your own measurements.