What can we see when looking at clouds?

Covariance is a central work within the vast project Raphaël Dallaporta undertook about the historical relations and theoretical links between photography, science and space research. Dallaporta (b. 1980, France) has been participating for the past three years in the “Creation and Spacial imagination” program organized by the French Space Observatory and the National Center for Spatial Studies (CNES). This work, which has been finalised during Dallaporta’s one-year residency at Villa Medici - French Academy in Rome (Italy), was realised in close collaboration with French mathematician Alexandre Brouste.

Covariance is a mural composition of 48 mathematical models. Each image, which resembles a fragment of cloud, has been computer-generated in the University of Maine’s laboratories (Le Mans, France) by exploiting a mathematical formula known as a probability algorithm or “covariance”. These calculations resulted in a large number of dots within a cube - each, when seen from above and depending on his position in the volume, would appear more or less dark. Moreover, the mural ensemble of 48 pieces is actually composed of twelve subgroups of 4 photographs each for which only one parameter of the mathematical formula would vary. Covariance is a work positioned halfway between the classification of an illusory object and the poetic variation on a theme.

Clouds are a historical photographic object. They are also objects that scientists could appropriate only very late, as French curator Luce Lebart recently revealed1. Raphaël Dallaporta,  who has been fascinated by the history of humans observing space, dedicated a monumental work to this singular motif in between photographic and scientific researches.

Using an ancient and rare process (each of the 48 pieces is a cyanotyped platinum and palladium print) and choosing the title Covariance, Raphaël Dallaporta also refers to Alfred Stieglitz’s historical series which title, Equivalent (1925-1931), suggested the metaphorical role of clouds.

Lastly, the entire Covariance project stands for a parable. Modern digital networks use algorithms to calculate probabilities based on large amounts of datas stored in “cloud” servers. What can we learn from close observations of clouds? Nothing more than illusions, Dallaporta would say.

Courtesy of the artist and Jean-Kenta Gauthier

1 in “Les Archives du Ciel : la photographie scientifique des nuages”, Etudes Photographiques n°1, Paris, November 1996