Updated Climatology of Mesospheric Temperature Inversions Detected by Rayleigh Lidar above Observatoire de Haute Provence, France, Using a K-Mean Clustering Technique - INSU - Institut national des sciences de l'Univers Access content directly
Journal Articles Atmosphere Year : 2022

Updated Climatology of Mesospheric Temperature Inversions Detected by Rayleigh Lidar above Observatoire de Haute Provence, France, Using a K-Mean Clustering Technique

Maryam Ardalan
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Philippe Keckhut
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  • PersonId : 918122
Alain Hauchecorne
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  • PersonId : 914935
Robin Wing
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Mustapha Meftah
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  • PersonId : 937806

Abstract

A climatology of Mesospheric Inversion Layers (MIL) has been created using the Rayleigh lidar located in the south of France at L’Observatoire de Haute Provence (OHP). Using criteria based on lidar measurement uncertainties and climatological mean gravity wave amplitudes, we have selected significant large temperature anomalies that can be associated with MILs. We have tested a novel approach for classifying MILs based on a k-mean clustering technique. We supplied different parameters such as the MIL amplitudes, altitudes, vertical extension, and lapse rate and allowed the computer to classify each individual MIL into one of three clusters or classes. For this first proof of concept study, we selected k = 3 and arrived at three distinct MIL clusters, each of which can be associated with different processes generating MILs in different regimes. All clusters of MIL exhibit a strong seasonal cycle with the largest occurrence in winter. The four decades of measurements do not reveal any long-term changes that can be associated with climate changes and only show an inter-annual variability with a quasi-decadal oscillation.
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insu-03671474 , version 1 (18-05-2022)

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Maryam Ardalan, Philippe Keckhut, Alain Hauchecorne, Robin Wing, Mustapha Meftah, et al.. Updated Climatology of Mesospheric Temperature Inversions Detected by Rayleigh Lidar above Observatoire de Haute Provence, France, Using a K-Mean Clustering Technique. Atmosphere, 2022, 13 (5), pp.814. ⟨10.3390/atmos13050814⟩. ⟨insu-03671474⟩
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