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https://doi.org/10.5194/acp-2020-918
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-918
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  17 Sep 2020

17 Sep 2020

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This preprint is currently under review for the journal ACP.

Characterisation and surface radiative impact of Arctic low clouds from the IAOOS field experiment

Julia Maillard, François Ravetta, Jean-Christophe Raut, Vincent Mariage, and Jacques Pelon Julia Maillard et al.
  • LATMOS, Sorbonne Université

Abstract. The Ice, Atmosphere, Arctic Ocean Observing System (IAOOS) field experiment took place from 2014 to 2019. Over this period, more than 20 instrumented buoys were deployed at the North Pole. Once locked into the ice, the buoys drifted for periods of a month to more than a year. Some of these buoys were equipped with 808 nm wavelength lidars which acquired a total of 1805 profiles over the course of the campaign. This IAOOS lidar dataset is exploited to establish a novel statistic of cloud cover and of the geometrical and optical characteristics of the lowest cloud layer. Cloud frequency is globally at 75 %, and above 85 % from May to October. Single layers are thickest in October/November and thinnest in the summer. Meanwhile, their optical depth is maximum in October. On the whole, the cloud cover is very low, with the great majority of first layer bases beneath 120 m. In the shoulder seasons, surface temperatures are markedly warmer when the IAOOS profile contains at least one low cloud than when it does not. This temperature difference is statistically insignificant in the summer months. Indeed, summer clouds have a shortwave cooling effect which can reach −60 W m−2 and balance out their longwave warming effect.

Julia Maillard et al.

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Julia Maillard et al.

Julia Maillard et al.

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Latest update: 19 Oct 2020
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Short summary
Clouds remain a major source of uncertainty in understanding the Arctic climate, due in part to the lack of measurements over the sea ice. In this paper, we exploit a series of lidar profiles acquired from autonomous drifting buoys deployed in the Arctic Ocean and derive a statistic of low cloud frequency and macrophysical properties. We also show that louds contribute to warm the surface in the shoulder seasons but not significantly from May to September.
Clouds remain a major source of uncertainty in understanding the Arctic climate, due in part to...
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