Middle‐Atmosphere Dynamics Observed With a Portable Muon Detector

Autor: M. Tramontini, M. Rosas‐Carbajal, C. Nussbaum, D. Gibert, J. Marteau
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Earth and Space Science, Vol 6, Iss 10, Pp 1865-1876 (2019)
Druh dokumentu: article
ISSN: 2333-5084
DOI: 10.1029/2019EA000655
Popis: Abstract In the past years, large particle physics experiments have shown that muon rate variations detected in underground laboratories are sensitive to regional, middle‐atmosphere temperature variations. Potential applications include tracking short‐term atmosphere dynamics, such as Sudden Stratospheric Warmings. We report here that such sensitivity is not only limited to large surface detectors under high‐opacity conditions. We use a portable muon detector conceived for muon tomography for geophysical applications, and we study muon rate variations observed over 1 year of measurements at the Mont Terri Underground Rock Laboratory, Switzerland (opacity of ~700 meter water equivalent). We observe a direct correlation between middle‐atmosphere seasonal temperature variations and muon rate. Muon rate variations are also sensitive to the abnormal atmosphere heating in January–February 2017, associated to a Sudden Stratospheric Warming. Estimates of the effective temperature coefficient for our particular case agree with theoretical models and with those calculated from large neutrino experiments under comparable conditions. Thus, portable muon detectors may be useful to (1) study seasonal and short‐term middle‐atmosphere dynamics, especially in locations where data are lacking such as midlatitudes, and (2) improve the calibration of the effective temperature coefficient for different opacity conditions. Furthermore, we highlight the importance of assessing the impact of temperature on muon rate variations when considering geophysical applications. Depending on latitude and opacity conditions, this effect may be large enough to hide subsurface density variations due to changes in groundwater content and should therefore be removed from the time series.
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