Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8906214 | Aeolian Research | 2018 | 11 Pages |
Abstract
We report a May-June 2015 survey of dust devil activity on a Nevada desert playa using an inexpensive digital timelapse camera. We discuss techniques for exploiting the large volume of data (â¼32,700 images, made publicly-available) generated in these observations, similar to imaging from Mars landers and rovers, noting the diurnal image filesize variations as a useful quick-look metric of weather conditions. We present results from a semi-automated image classification: this classification is available to other workers, for example for benchmarking automated procedures. The acquisition of images at 1/min for some 36â¯days permits study of the diurnal variation of dust devil activity (e.g. 85% of the dust devil images [i.e. those images manually classified as showing dust devils] occur between 12:00 and 17:00; during the period of peak activity 13:00-15:00 about 7% of images contain well-defined dust devils of several meters diameter or larger). The data also permit the dependence of dust devil characteristics on ambient conditions. We construct a simple two-state Markov model for the occurrence and persistence of dust devils (a few per cent chance that new dust devil activity appears in the next image; and a â¼45% chance that activity stops) which may help inform strategies for acquiring and interpreting field observations.
Keywords
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Atmospheric Science
Authors
Ralph D. Lorenz, Brian K. Jackson, Peter D. Lanagan,