These sonifications were created with atmospheric carbon records from the Mauna Loa Observatory: C. D. Keeling, S. C. Piper, R. B. Bacastow, M. Wahlen, T. P. Whorf, M. Heimann, and H. A. Meijer, Exchanges of atmospheric CO2 and 13CO2 with the terrestrial biosphere and oceans from 1978 to 2000. I. Global aspects, SIO Reference Series, No. 01-06, Scripps Institution of Oceanography, San Diego, 88 pages, 2001. http://escholarship.org/uc/item/09v319r9 In Situ data was processed and converted to MIDI notes using Python, and sonified using Supercollider. The data is mapped to a 12-tone equal-temperament scale spanning three octaves, with 340 ppm and 420 ppm as the lower and upper limits of the data range. In this mapping, 340 ppm is sonified as 130.81 Hz, and 420 ppm is sonified as 1046.50Hz. For these pieces, I wanted the sonic familiarity of an equal-temperament scale, so I chose a 12-tone scale to maximize the number of frequency bins (36 in total) within a relatively narrow range. The start years 1988 and 2014 were chosen because those are the years when CO2 reached 350 and 400 ppm, respectively. 1988 is also the year when NASA scientist James Hansen briefed Congress on the dangers of the rampant rise in CO2, and warned, controversially, that global warming could already be detected in temperature records. Each of these pieces sonifies five years of data at three different overlapping resolutions: weekly, monthly, and yearly. The choice to map from ppm to a 12-tone scale reduces the resolution of the data and creates more repetitive pitches, which creates a more rhythmic effect. Five years of the historical record, which is used in these pieces, is enough to hear the rise in CO2 if paying close attention, but it requires concentrated effort. The main effect is to hear the interplay between weekly and monthly carbon fluctuations. I also wanted the pieces to be one or two minutes long – the shortest duration of the whole collection – and to be played one right after the other. I experimented with tempos and found that a tempo of one monthly data point per every 1.2 seconds moved at a pace that felt unrushed but fast enough for the seasonal cycle to be recognizable. Each of the three timescales of data are sonified by a unique instrument. Since the motivation of these pieces is to hear the relationship between the three different timescales, I chose simple percussive sounds to accentuate the rhythm of the temporal ratios. The beat represents one month, and there are four or five weeks per month. A long-reverberation bell sound represents the annual data, as a background sound. The synth playing this annual CO2 was modeled after a recording of a Tibetan prayer bell. It consists of a bank of twelve frequency resonators excited by an input frequency and low-pass filtered pink noise. The input frequency is the mapped annual CO2 value, shifted down one octave. The synth playing the monthly and weekly CO2 is modeled after a mallet. It's also composed of a bank of eight frequency resonators that are excited by pink noise. The fundamental frequency is given by the mapped CO2 value. The difference in sound between the weekly and monthly values is determined by the decay length of the ring times for the resonators. The decay length of the monthly values is twice as long as the decay length for the weekly values. The choice of percussive instruments modeled after a bell and mallet was to create a minimalist sound that lets the listener hear how different the carbon record sounds when we pay attention at weekly, monthly, annual, and decadal timescales.

These two pieces are part of a collection of sound compositions called Timescales, which sonifies datasets spanning different time scales of the atmospheric carbon record. Sonification is analogous to visualization. In visualizations, data is mapped to an image; in sonification data is mapped to sound. In Situ 1988 and In Situ 2014 both sonify five years of atmospheric carbon data from the Mauna Loa Observatory, commonly known as the Keeling Curve. The pieces present the carbon record at weekly, monthly, and yearly timescales with a musical scale and translate historical time to musical time. Unlike standard graphical presentations of data, these sound compositions allow the listener to hear the data as physical resonance over time.

This is a stereo wav file and can be played through any digital music player.