How does the bird-flocking simulation work?

It implements Craig Reynolds' Boids algorithm: each agent applies three simple steering rules — separation (avoid crowding), alignment (steer toward neighbours' heading), and cohesion (move toward the average position). Complex flocking behaviour emerges with no global coordination.

What equations govern the predator-prey simulation?

The Fox & Rabbits simulation solves the Lotka-Volterra differential equations: dx/dt = αx − βxy and dy/dt = δxy − γy, where x is prey population and y is predator population. The phase-space orbit is a closed ellipse for the original linear model.

How is the climate/weather modelled?

Atmosphere and ocean simulations use simplified Navier-Stokes equations on a 2D grid, with temperature gradients driving convection cells. These are the same equations — at much lower resolution — that power operational weather forecast models.

Nature & Climate — 3D Simulations

About Nature & Climate Simulations

Oceans, atmosphere, terrain, and weather — simulated from first principles

Nature and climate simulations model the physical processes that shape our planet. Gerstner wave equations recreate realistic ocean surfaces; Mie and Rayleigh scattering produce accurate atmospheric colours including rainbows and sky gradients; a cellular-automaton erosion model sculpts procedural mountain terrain; and snowflake crystallisation grows fractal ice crystals one hexagonal lattice step at a time.

Each simulation exposes a different layer of Earth-system science — fluid dynamics, thermodynamics, optics, and geology — through interactive controls. Adjust wave height, atmospheric density, particle count, or precipitation rate and watch emergent patterns arise from simple physical rules. These are the same computational methods used in climate models, weather forecasting, and visual-effects pipelines.

Nature simulations reveal a profound principle: complex, lifelike behaviour can emerge from a handful of simple local rules. Boids flock without a leader, ant colonies find shortest paths without maps, and forest fires spread via nearest-neighbour ignition. This emergent complexity is not just beautiful — it underpins real ecological models, climate projections, and epidemiological forecasting used by governments and research institutions worldwide.

Key Concepts

Topics and algorithms you'll explore in this category

Boids AlgorithmThree rules: separation, alignment, cohesion

Predator-Prey (Lotka-Volterra)Population oscillation equations

Cellular AutomataLocal rules producing global emergent patterns

Fluid DynamicsNavier-Stokes applied to ocean and atmosphere

SIR ModelEpidemiological compartment model

Reaction-DiffusionTuring patterns from activator-inhibitor chemistry

Frequently Asked Questions

Common questions about this simulation category

How does the bird-flocking simulation work?: It implements Craig Reynolds' Boids algorithm: each agent applies three simple steering rules — separation (avoid crowding), alignment (steer toward neighbours' heading), and cohesion (move toward the average position). Complex flocking behaviour emerges with no global coordination.
What equations govern the predator-prey simulation?: The Fox & Rabbits simulation solves the Lotka-Volterra differential equations: dx/dt = αx − βxy and dy/dt = δxy − γy, where x is prey population and y is predator population. The phase-space orbit is a closed ellipse for the original linear model.
How is the climate/weather modelled?: Atmosphere and ocean simulations use simplified Navier-Stokes equations on a 2D grid, with temperature gradients driving convection cells. These are the same equations — at much lower resolution — that power operational weather forecast models.

Nature & Climate

Category Simulations

Learning Resources

About Nature & Climate Simulations

Key Concepts

Frequently Asked Questions

Other Categories