Python framework to produce music from weather data
- Generate music that is artistically valid on its own accord, not just as "representation" of data or as an "aural visualization". Its use is not just a direct "communication" of the data values. "Classic" visualisation is better for that.
- Music must create emotion. A sense of drama that relates to the same sense of drama created by weather.
- Emotions created by the music will be related to the emotions future weather will create in people.
- Music will forecast emotions.
- Music advances how you will feel in the future
- Will show a connection between the earth and the emotions
- Time travel?
- Following patterns of the Earth (eg day/night, rain/dry, cloudy/sunny, hot/warm)
- Granular synthesis. Waves vs particles
- Music that is unique for a moment. Disposable, ephemeral art. Fluxus, Beuys. No one should listen to the same piece twice as they always can access the latest.
- Music as Ephemera (3)
- Program music (4). In this case the "extramusical narrative" is the real life weather events
- Computer centred compositional techniques
- Weather makes us feel time, seasons are the reason for the first calendars. Feel the passing of time, different timescales. How can we apply these different timescales?
- The concepts of stable/unstable belong both in music and in meteorology
- Weather and behaviour (6). The psychology of weather
- Good vibrations
- Rain (Beatles)
- Winterreise
- Sunny Afternoon
- Paper about weather in music (2)
Ideas on how to map individual weather parameters to music and sound parameters
- Cloud Cover: Some kind of low-pass filter that opens as the cloud cover lifts?
- Precipitation: Harmonic stability? Key-related. But might be difficult to "establish key" though
- Wind Speed: Harmonic stability? Intra-chordal or root-related? From 8ths to 5ths to minor 2nds
- 2m Temperature: Grain of a granular synth. From sharper to rounder
- ???? Amplitude
- Uncertainty in all the prior? The uncertainty could be mapped so that it increases the musical complexity of the piece adding more instruments or adding wider variations. This would correlate with the many many musical pieces are laid out, developing themes and introducing variations as time moves forward.
- Deviation from climatological data. How unusual are those values for this particular place?
- What about rhythm? The grind between a 2-based and a 3,4,5,6,7.. Poly rhythms. Rhythmic tension between stable/unstable beats
- Use Shepard tones (5) to convey a send of continues ascent or descent
- Changes in modes could be useful as ways of conveying meaning? https://en.wikipedia.org/wiki/Mode_(music)
- What about quadraphonic sound to map not only wind intensity but direction. Wind could come from the right place in a 2D space
- Should we accept that some days are going to sound pretty boring? Veracity vs musical interest Or should we try all to sound interesting, even if the weather isn't. Probably not
- At some point we could consider including some Machine Learning scenarios, based in a number of presets.
- Antecedent-consequent (question-answer) phrase ideas could be mapped to unstable-stable. The more unstable the further to the tonic (antecedent at a further distance) the phrase could end on.
- Lagging-leading with the rhythm.
- matplotlib for debugging and showing off
- scipy
- Exploring how to do animations
- Csound for realtime playing or batch-mode (generate orchestra+score then render)?
- http://en.wikipedia.org/wiki/Sonification
- http://www.metlink.org/wp-content/uploads/2013/06/Brown_et_al-2015-Weather.pdf
- https://en.wikipedia.org/wiki/Ephemera
- https://en.wikipedia.org/wiki/Program_music
- https://en.wikipedia.org/wiki/Shepard_tone
- https://www.trevorharley.com/weather-and-behaviour.html