Spatiotemporal Large-Scale Networks Shaped by Air Mass Movements

• Published in: Frontiers in applied mathematics and statistics Vol. 6
• Main Authors: Choufany, M., Martinetti, D., Senoussi, R., Morris, C. E., Soubeyrand, S.
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 30.03.2021
• Subjects: aerobiology; air masses dynamics; Atmospheric and Oceanic Physics; Climatology; Computer Science; connectivity; Earth Sciences; Environmental Sciences; Modeling and Simulation; Physics; Sciences of the Universe; spatial network; spatiotemporal network; spatiotemporal network; connectivity; air masses dynamics; spatial network; aerobiology
• ISSN: 2297-4687; 2297-4687
• DOI: 10.3389/fams.2020.602621

The movement of atmospheric air masses can be seen as a continuous flow of gases and particles hovering over our planet, and it can be locally simplified by means of three-dimensional trajectories. These trajectories can hence be seen as a way of connecting distant areas of the globe during a given period of time. In this paper we present a mathematical formalism to construct spatial and spatiotemporal networks where the nodes represent the subsets of a partition of a geographical area and the links between them are inferred from sampled trajectories of air masses passing over and across them. We propose different estimators of the intensity of the links, relying on different bio-physical hypotheses and covering adjustable time periods. This construction leads to a new definition of spatiotemporal networks characterized by adjacency matrices giving, e.g., the probability of connection between distant areas during a chosen period of time. We applied our methodology to characterize tropospheric connectivity in two real geographical contexts: the watersheds of the French region Provence-Alpes-Côte d’Azur and the coastline of the Mediterranean Sea. The analysis of the constructed networks allowed identifying a marked seasonal pattern in air mass movements in the two study areas. If our methodology is applied to samples of air-mass trajectories, with potential implications in aerobiology and plant epidemiology, it could be applied to other types of trajectories, such as animal trajectories, to characterize connectivity between different components of the landscape hosting the animals.