Weather is something we all experience, yet it’s often reduced to numbers on a chart or icons on a forecast. For this project I wanted to explore a different approach by translating decades of climate data from North West England and North Wales into an abstract woven composition.
Using Java and Processing, the artwork is generated from historical Met Office climate datasets covering rainfall, sunshine and maximum temperatures. Rather than plotting the information as a conventional graph, each data series influences a different visual characteristic, allowing the climate to emerge as a textile-like structure.
Rainfall is represented through dashed threads that build density and rhythm across the composition. Sunshine introduces bright yellow strands and small bead-like markers that punctuate the weave, creating moments of light amongst the darker fibres. Temperature is expressed as a flowing gradient, shifting from cool blues to warm reds, giving the piece an additional layer of movement and seasonal character.
One of the most striking patterns isn’t just that the summers are getting warmer, but that the warmth is lingering for longer, gradually stretching further into autumn and delaying the onset of winter.
One of the most enjoyable parts of the project was discovering how a simple woven structure could communicate such complex information. The result isn’t intended to be read as a chart. Instead, it encourages the viewer to experience the data first as an artwork before gradually recognising that every thread is responding to genuine climate records.
Developing the project also became an exercise in balancing aesthetics with information. Too much emphasis on the data and the composition lost its visual appeal; too much abstraction and the connection to the climate disappeared. Finding that middle ground became the focus of the design process.
The sketch is fully generative, meaning each composition is created programmatically while remaining rooted in historical weather observations. Features such as animated fibres, interactive colour modes and woven layering help transform static datasets into something that feels organic and alive.
This project continues my exploration of using code as a creative medium, where information becomes material rather than simply content. By treating climate data as texture, rhythm and structure instead of statistics, the work aims to reveal familiar weather patterns from an entirely different perspective.
Although this is an early iteration, there are plenty of directions to explore next. I’m interested in introducing more complex weaving behaviour, allowing threads to respond to long-term climatic trends, and experimenting with larger-format outputs where the fine details become even more immersive.
As with many of my Processing projects, the goal isn’t to create a digital chart or dashboard, but to build something that sits somewhere between data visualisation, generative art and printmaking—using code to uncover beauty hidden within everyday information.