Abstract

Studying fog requires a good understanding of both its horizontal and vertical distributions. Among these two, the vertical one is the most challenging to observe. Different methods have been adopted for observing this variable, among which the most commonly used are satellite datasets, together with airborne and meteorological surface observations. Yet, all these techniques present significant limitations as for spatial and temporal resolution when describing the vertical fog structure. In this manuscript, we introduce the Ground Optical Fog Observation System (GOFOS), a new method to describe the advective fog’s frequency and vertical distribution. This tool is based on in-situ optical observations, taking advantage of the topography of the Atacama Desert coastal mountains, where advective fog is frequent. During 2017, the GOFOS reported a fog presence <10% during summer and of ~50% during winter. Also, the GOFOS shows a diurnal variability of fog presence that decreases around noon and increases again starting from the afternoon. The vertical structure observed by the GOFOS shows a cloud depth of ~250 m, subject to diurnal and seasonal variabilities. By analyzing GOFOS results through a comparison with the ones obtained by standard observations, a ~93% agreement was found between the fog frequencies detected by the GOFOS and GOES. Also, we found a ~80% consistency between GOFOS fog frequency values and marine boundary layer regimes related to fog formation. Moreover, we observed that the cloud base height estimated by the GOFOS is correlated with the Iquique Airport ceilometer measurements (r = +0.6). Finally, the mean cloud top height estimated by the GOFOS differs by 8% from the Antofagasta Airport radio-soundings measurements. These results provide useful information for the selection of optimal sites for fog harvesting and for getting a better understanding of the interactions between fog and its ecosystem. In conclusion, through this study the GOFOS demonstrated its potential as a simple, reliable, and affordable method for systematic fog monitoring that might also be adapted to different topographic conditions.