2021
DOI: 10.5194/acp-2021-97
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Ice and Mixed-Phase Cloud Statistics on Antarctic Plateau

Abstract: Abstract. Statistics on the occurrence of clear skies, ice and mixed-phase clouds over the Concordia station, in the Antarctic Plateau, are provided for multiple time scales and analysed in relation to simultaneous meteorological parameters measured at the surface. Results are obtained by applying a machine learning cloud identification and classification code (named CIC) to 4 years of measurements between 2012–2105 of down-welling high spectral resolution radiances, measured by the Radiation Explorer in the F… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
3

Citation Types

0
7
0

Year Published

2021
2021
2022
2022

Publication Types

Select...
3
1
1

Relationship

1
4

Authors

Journals

citations
Cited by 5 publications
(7 citation statements)
references
References 16 publications
0
7
0
Order By: Relevance
“…Recent studies have investigated the use of high spectral resolution far‐IR radiances for cloud phase classification (i.e., Cossich et al., 2021; Maestri, Arosio, et al., 2019; Maestri, Cossich, & Sbrolli, 2019; Sgheri et al., 2021) based on observed downwelling radiances and synthetic satellite observations. These studies utilize numerous spectral channels across the far‐IR and mid‐IR for the radiance inputs to a principal component analysis‐based machine learning algorithm for cloud identification.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Recent studies have investigated the use of high spectral resolution far‐IR radiances for cloud phase classification (i.e., Cossich et al., 2021; Maestri, Arosio, et al., 2019; Maestri, Cossich, & Sbrolli, 2019; Sgheri et al., 2021) based on observed downwelling radiances and synthetic satellite observations. These studies utilize numerous spectral channels across the far‐IR and mid‐IR for the radiance inputs to a principal component analysis‐based machine learning algorithm for cloud identification.…”
Section: Introductionmentioning
confidence: 99%
“…The spectral variation of ice cloud scattering also varies across the far‐IR and can be larger in the far‐IR compared to the mid‐IR, which can potentially provide additional information to help discriminate different cloud phases using a bi‐spectral approach. Furthermore, it is possible that a far‐IR BTD cloud phase algorithm can supplement or improve the conventional mid‐IR BTD approach, as multiple studies have indicated that the far‐IR and mid‐IR can be used synergistically for cloud phase determination (e.g., Cossich et al., 2021; Rathke et al., 2002; Rowe et al., 2019; Turner, 2005). It has also been shown that the prominent far‐IR scattering can be used synergistically with the mid‐IR for ice cloud property retrievals (Libois & Blanchet, 2017; Merrelli & Turner, 2013; Saito et al., 2020).…”
Section: Introductionmentioning
confidence: 99%
“…Within this temperature regime, clouds can occur as liquid only (supercooled water) as well as in the mixed phase, in which ice crystals coexist with water droplets, and also as purely ice. Mixed-phase clouds are very common in polar regions, both in the Arctic and Antarctica (Cossich et al, 2021), but they can also be widely found at mid-latitudes, so much so that Costa et al (2017) show that out of 16 measurement flights of the COALESC (Combined Observation of the Atmospheric boundary Layer to study the Evolution of StratoCumulus) campaign performed with aircraft at mid-latitudes, 14 observations provided the presence of clouds in the mixed-phase regime.…”
Section: Introductionmentioning
confidence: 99%
“…Recently, some authors (such as Maestri et al, 2019a;Saito et al, 2020;Di Natale et al, 2020) have shown the potentialities of exploiting FIR spectrally resolved radiances to refine ice clouds microphysical and optical properties. Maestri et al (2019b) and Cossich et al (2021) also showed the benefit of using FIR channels in combination with MIR ones to largely improve the performances of cloud identification and classification (i.e. between ice and liquid water phase) algorithms.…”
mentioning
confidence: 99%