Articles | Volume 24, issue 10
https://doi.org/10.5194/acp-24-6433-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-6433-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Investigating long-term changes in polar stratospheric clouds above Antarctica during past decades: a temperature-based approach using spaceborne lidar detections
Mathilde Leroux
CORRESPONDING AUTHOR
LAERO, Laboratoire d'Aérologie, Université Toulouse III Paul Sabatier, CNRS, Toulouse, 31400, France
Vincent Noel
LAERO, Laboratoire d'Aérologie, Université Toulouse III Paul Sabatier, CNRS, Toulouse, 31400, France
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EGUsphere, https://doi.org/10.5194/egusphere-2025-5018, https://doi.org/10.5194/egusphere-2025-5018, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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The shape of crystals in ice clouds drives their impact on the earth energy balance. These shapes are very variable and hard to categorize. In this paper, we use a recently developed method to put clouds in categories of crystal shape. We apply this method to 33 months of measurements from a lidar in space. We discuss how the importance of shape categories changes with the time of the day. These results could be useful for people who try to simulate clouds in atmospheric models.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
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The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Matthias Tesche and Vincent Noel
Atmos. Meas. Tech., 15, 4225–4240, https://doi.org/10.5194/amt-15-4225-2022, https://doi.org/10.5194/amt-15-4225-2022, 2022
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Mid-level and high clouds can be considered natural laboratories for studying cloud glaciation in the atmosphere. While they can be conveniently observed from ground with lidar, such measurements require a clear line of sight between the instrument and the target cloud. Here, observations of clouds with two spaceborne lidars are used to assess where ground-based lidar measurements of mid- and upper-level clouds are least affected by the light-attenuating effect of low-level clouds.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, Rodrigo Guzman, Cyprien Gindre, Po-Lun Ma, and Marjolaine Chiriaco
Atmos. Meas. Tech., 15, 1055–1074, https://doi.org/10.5194/amt-15-1055-2022, https://doi.org/10.5194/amt-15-1055-2022, 2022
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Space-borne lidars have been providing invaluable information of atmospheric optical properties since 2006, and new lidar missions are on the way to ensure continuous observations. In this work, we compare the clouds estimated from space-borne ALADIN and CALIOP lidar observations. The analysis of collocated data shows that the agreement between the retrieved clouds is good up to 3 km height. Above that, ALADIN detects 40 % less clouds than CALIOP, except for polar stratospheric clouds (PSCs).
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Short summary
This study investigates the long-term changes in the polar stratospheric cloud (PSC) season from 1980 to 2021 above Antarctica. We analyzed CALIOP observations from 2006 to 2020 to build a statistical temperature-based model. We applied our model to gridded reanalysis temperatures, leading to an integrated view of PSC occurrence that is free from sampling issues, allowing us to document the past evolution of the PSC season.
This study investigates the long-term changes in the polar stratospheric cloud (PSC) season from...
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