External factors driving surface temperature changes above geothermal systems: answers from deep learning - Archive ouverte HAL
Article Dans Une Revue Frontiers in Earth Science Année : 2024

External factors driving surface temperature changes above geothermal systems: answers from deep learning

Résumé

The surface expression of enhanced geothermal heat fluxes above an active hydrothermal system causes a surface thermal anomaly (∆T). The thermal anomaly is expressed by the difference between the temperature within the heated zone (Th) and the temperature of non-heated surfaces (T0). Given that the resulting thermal anomaly at the surface is of extremely low magnitude (1–5 ◦C at Vulcano, Italy), it is extremely sensitive to overprinting by external factors, namely meteorological influences on surface temperature variation, such as solar heating, wind and rain. To test the sensitivity of the surface to external drivers, we installed two surface temperature measurement stations within the Vulcano’s Fossa crater, one inside the thermal anomaly and one outside (separation = 50 m), with a weather station co-located with the T0 station. Time series of Th and T0 were collected for 2020, when the Vulcano Fossa hydrothermal system was at a low and stable level of activity so that external drivers would have been the main influences on Th and T0, and hence also ∆T. To test for divergence from normality in terms of diurnal and seasonal variations in Th and T0, and the role of external factors in causing abnormality, we used the deep learning engine DITAN: a domain-agnostic framework to detect and interpret anomalies in time-series data. During the year, DITAN found 16 cases of two types of meteorological events: intense low-pressure systems and high-intensity rainstorms (cloudbursts). Passage of 13 abnormal low-pressure systems was de- tected (10 between February and May, and three in December), with three abnormal rainstorm events (all in December); all three being coincident with the low pressure events. We find just two abnormalities in the time series for of Th and T0, both of which coincide with passage of abnormal low-pressure systems, and neither of which coincide with abnormal rain events. We conclude that diurnal and annual heating and cooling cycles, subject to normal meteorological inputs and at a surface above a geothermal-heated source, are immune to anomalous behaviour to the external (meteorological) variations.
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hal-04593971 , version 1 (11-11-2024)

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Michail Giannoulis, Sophie Pailot-Bonnétat, Vincent Barra, Andrew Harris. External factors driving surface temperature changes above geothermal systems: answers from deep learning. Frontiers in Earth Science, 2024, 12, ⟨10.3389/feart.2024.1372621⟩. ⟨hal-04593971⟩
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