I made "this weather" in Pure Data to sonify and visualise the weather station data online at the University of York's website (http://weather.elec.york.ac.uk/). I wanted to give the data a sonic/visual narrative that could be easily understood.
Wind: White noise is the basis for the wind. Speed determines the value of a lowpass filter & gust speed determines the amplitude of the output. Direction is represented by the white noise's pan position.
Rain/hail: The amount of rain & hail that has fallen since midnight is used to control a the frequency of a sawtooth wave. The faster it oscillates, the more rain that has fallen. Rain is heard in the left audio channel, whilst hail is heard in the right.
Pressure: The air pressure controls the frequency of a sine wave generator. The low frequency is scaled to be audible to human ears.
Humidity/Dew Point: This data controls the duty cycle of a pulse wave. If humidity is very high, it will produce a thin and raspy tone and if it is low it will produce are 'fuller' sound. Dew point & humidity are closely related. Here, it affects the amplitude modulation of the pulse wave. The higher the dew point, the faster the modulation.
Temperature: Simple FM synthesis is used to represent temperature information. The overall temperature controls the pitch of the carrier wave, wind chill controls the modulator and wind speed controls the modulation amount.
Once the language of the sound and visuals are understood, you can understand the weather conditions very quickly through sensory perception; possibly quicker than if you were to read the information.
(Please note: the weather information on the University of York's website is updated every minute. Therefore sonic and visual changes happen at a glacial pace, particularly on fairly pleasant days)
