The Climate Symphony

The Climate Symphony, by Marty Quinn, is a multimedia performance that uses climate data from the last 110000 years. It tracks the climatological evolution over these years, sonifying several datastreams simultaneously. The music is played together with a spoken word performance by Quinn, explaining the climate evolution. Quinn developed custom software for the Climate Symphony and has developed several other sonification projects such as Shakespeare texts, the 9/11 attacks, solar images, et cetera.


The Climate Symphony [1] uses data extracted from a 3053-meter ice core drilled up in Greenland. Through the chemical composition of the ice-core one is able to analyse the climatological evolution. Quinn uses the top 2960 meters of the ice core which amounts to 110000 years of climate history. Out of eight chemical time series, three were extracted through principal component analysis [2]. Series 1, the „Polar Circulation Index” describes the atmospheric circulation response to the growth and decay of the continental ice sheets while series 2 and 3 describe the biological response of the changing climate. The patterns that are present in the data offer a great opportunity for a composition. Quinn superposes the various patterns and maps them to different instruments (played by a synthesiser). The data are read with a speed of 150 years per second for the first 20000 years and 350 years per second for the latter 90000 years. As such, 110000 years of climate evolution is compressed into a 7-minute composition.
The mapping is done as follows:
a) the 550-year solar intensity cycle is mapped onto a scale of melodic patterns played on a vibraphone. The hotter the sun, the higher the melodies and vice versa.
b) the ebb and flow of the ice sheets happen in 6300-year cycles. These movements are mapped onto 3 rhythmic patterns of cowbells for expansion and 3 rhythmic patterns of tom-toms and conga for contraction. Which of the patterns is played depends on the amount of expansion/contraction.
c) Volcanic activity is sonified through cymbal crashes and timpani whose volume depends on the intensity of the eruption. The pitch of the timpani gets lower with a higher intensity as well.
d) The earth’s wobble causes some summers to be hotter and some colder. Quinn maps this influence on the lower two octaves of the organ; the bigger the influence, the higher the pitch, the lower the influence, the lower the pitch
e) The earth’s tilt is sonified through a 3-note arpeggio where the notes are higher if the tilt is bigger. The instrumentation (clarinet, trumpet or muted trumpet) is chosen according to the 1450 year ocean cycle.
f) The slight change in the elliptical orbit around the sun transposes all music up or down up to seven steps depending on the increase7decrease of the elliptical shape of the orbit.

Quinn creates a multidimensional structure where 5 datastreams are sonified and a seventh one manipulates those streams through transposition.

You can listen to a sample on Quinn’s project site:
Update 30/05/2017: the site seems to be down at the moment. 

About Marty Quinn

Marty Quinn is a computer scientist, composer, drummer and has founded the Design Rhythmics Sonification Research Lab, which specialises in sonification research. He frequently works together with scientists and research institutes such as the Venice Marine Institute, the Climate Change Research Center and Space Plasma Group of the University of New Hampshire, and the Lunar and Planetary Lab at the University of Arizona. He has won three NASA grants to develop sonification projects and together with his partner, Wendy Quinn, he produces new exhibits, dance and theatre.

Here is a video of a presentation by Quinn, talking about sonification at the Locus Sonus sonification symposium in 2010.


[1] Quinn, M., & Meeker, L. D. (2001). Research set to music: The climate symphony and other sonifications of ice core, radar, DNA, seismic and solar wind data (pp. 56–61). Presented at the Proceedings of the 2001 International Conference on Auditory Display, Espoo.

[2] Principal component analysis is a method to describe a multivariate dataset using relevant parts of the data.

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