The Application

An interactive visualisation of climate model data across time and space.


visualisation |

Sebastian Steinig

testing & deployment |

Tessa Alexander

contact |


This project is heavily inspired by and would not have been possible without previous work. I am particularly grateful to the following people and projects for sharing their ideas and/or code:

inspiration for the project |

earth by Cameron Beccario

time interpolation on the GPU |

WebGL weather globe by Miron Kursa

moving particles on the GPU |

How I built a wind map with WebGL by Vladimir Agafonkin

geologic timescale |

UW-Macrostrat/geo-timescale by UW-Madison Macrostrat, updated by Jules Blom and distributed under the MIT license

3D engine |


charts |


warming stripes |

Ed Hawkins

warming stripes in D3.js |

by xadilzeshan¥ distributed under the MIT license

layout |

Bootstrap, Hyper Theme

animations |


icons |


3D vegetation models are all licensed under the Creative Commons Attribution. They include "Polygon Tree Pack" by StreakByte, "Bush" by Artbake Graphics and "Low Poly Grass" by RM_Way. Land surface textures are created from "Blue Marble: Next Generation" images by NASA’s Earth Observatory.

The surface desert texture for the Dune planet Arrakis was made by d3cline and is shared under the Creative Commons Attribution-Share Alike 3.0 License. The smooth sand dunes texture by the 3rdSequence is licensed under a Creative Commons Attribution 4.0 International License. Additional royalty-free rocky terrain textures 'Age of the Canyon' and 'Martian Range' are used from Spiral Graphics.

Data Sources

Climate model data represents monthly or annual means and can be accessed either from the referenced publications or by contacting the linked author.

Phanerozoic model data |

description in Valdes et al. (2021)
access via BRIDGE group at the University of Bristol

Paleogeographies |

Scotese and Wright (2018)

Dune simulation |

Alex Farnsworth


Initial seed corn funding for the project has been provided by the Jean Golding Institute for data science and data-intensive research at the University of Bristol.

The COP26 visulisation of CMIP6 future projections was funded by the Cabot Institute for the Environment and the School of Geographical Sciences.