How do I simulate an ice age?

Open this page and use the live Air Quality Model 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 ice age from your own measurements.

Use case · powered by Air Quality Model

Air Quality Model for an ice age

Simulate an ice age live in your browser. This runs the real Air Quality Model 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

Hazmat Plume

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Hazmat Plume DispersionLive

Gaussian plume · protective action

Controls

Presets

Release rate (g/s)

Wind speed (m/s)

Action level (mg/m³)

A Gaussian plume estimates how a gas or vapor release disperses downwind. Stability class (A unstable to F stable) sets how fast the plume spreads. The dashed line is the protective action distance where concentration falls below your action level. Screening estimate only — use ERG and monitors on scene.

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Data Inspector

Protective distance>20 km

StabilityD neutral

Wind4 m/s

Governing equation

C (x, y) = \frac{50}{2 π 4 σ _{y} σ _{z}} exp (- \frac{y ^{2}}{2 σ _{y}^{2}})

Reading this result: Concentration falls off as the wind stretches and vertical mixing thins the plume — stronger wind and less stable air pull the protective distance in toward the source.

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.

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About this simulation

The full Air Quality Model tool models an ice age 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 Air Quality Model

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Other ways to simulate an ice age

Energy Balance for an ice age Daisyworld for an ice age Milankovitch Cycles for an ice age Tsunami Propagation for an ice age Carbon Cycle for an ice age Earthquake Shaking for an ice age

Frequently asked questions

How do I simulate an ice age?: Open this page and use the live Air Quality Model 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 ice age from your own measurements.