Recent Advances in Arctic Cloud and Climate Research

Kay, J. E.; L’Ecuyer, Tristan; Chepfer, Hélène; Loeb, Norman G.; Morrison, Ariel L.; Cesana, G

doi:10.1007/s40641-016-0051-9

Cited by 156 publications

(137 citation statements)

References 71 publications

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“…Overall, CESM can capture general Arctic cloud, radiation, and sea ice features (Barton et al, 2012;Kay et al, 2012;Hurrell et al, 2013). When compared appropriately using a cloud simulator, the seasonal cycle of simulated CF is in better agreement with observed one (Kay et al, 2012(Kay et al, , 2016. Particularly, Community Atmosphere Model version 5 simulated Arctic CF is biased about twice as much winter cloud as the CALIPSO observations.…”

Section: Data Model and Methodsmentioning

confidence: 76%

Thicker Clouds and Accelerated Arctic Sea Ice Decline: The Atmosphere‐Sea Ice Interactions in Spring

Huang

Dong

Bailey

et al. 2019

Geophysical Research Letters

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Observations show that increased Arctic cloud cover in the spring is linked with sea ice decline. As the atmosphere and sea ice can influence each other, which one plays the leading role in spring remains unclear. Here we demonstrate, through observational data diagnosis and numerical modeling, that there is active coupling between the atmosphere and sea ice in early spring. Sea ice melting and thus the presence of more open water lead to stronger evaporation and promote cloud formation that increases downward longwave flux, leading to even more ice melt. Spring clouds are a driving force in the disappearance of sea ice and displacing the mechanism of atmosphere‐sea ice coupling from April to June. These results suggest the need to accurately model interactions of Arctic clouds and radiation in Earth System Models in order to improve projections of the future of the Arctic.

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Section: Data Model and Methodsmentioning

confidence: 76%

Thicker Clouds and Accelerated Arctic Sea Ice Decline: The Atmosphere‐Sea Ice Interactions in Spring

Huang

Dong

Bailey

et al. 2019

Geophysical Research Letters

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“…A recent series of papers expressing similar conclusions indicates no summertime cloud response to sea ice loss that would offset, even partially, the sea ice albedo feedback [13,17,221,222]. Conversely, a fall and early-winter cloud response exists where slower sea ice growth (i.e., larger-than-average and longer-lasting areas of open water) contributes to enhanced LH flux, which moistens the lower troposphere [46,223], and results in increased cloud amount, cloud base height, and cloud water content [12,13,17,39,217,222]. Kurita [224] found that local sources are the dominant atmospheric water vapor supply for the formation of Arctic low clouds in late autumn and early winter.…”

Section: Cloudsmentioning

confidence: 75%

On the Increasing Importance of Air-Sea Exchanges in a Thawing Arctic: A Review

et al. 2018

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Forty years ago, climate scientists predicted the Arctic to be one of Earth's most sensitive climate regions and thus extremely vulnerable to increased CO 2 . The rapid and unprecedented changes observed in the Arctic confirm this prediction. Especially significant, observed sea ice loss is altering the exchange of mass, energy, and momentum between the Arctic Ocean and atmosphere.As an important component of air-sea exchange, surface turbulent fluxes are controlled by vertical gradients of temperature and humidity between the surface and atmosphere, wind speed, and surface roughness, indicating that they respond to other forcing mechanisms such as atmospheric advection, ocean mixing, and radiative flux changes. The exchange of energy between the atmosphere and surface via surface turbulent fluxes in turn feeds back on the Arctic surface energy budget, sea ice, clouds, boundary layer temperature and humidity, and atmospheric and oceanic circulations. Understanding and attributing variability and trends in surface turbulent fluxes is important because they influence the magnitude of Arctic climate change, sea ice cover variability, and the atmospheric circulation response to increased CO 2 . This paper reviews current knowledge of Arctic Ocean surface turbulent fluxes and their effects on climate. We conclude that Arctic Ocean surface turbulent fluxes are having an increasingly consequential influence on Arctic climate variability in response to strong regional trends in the air-surface temperature contrast related to the changing character of the Arctic sea ice cover. Arctic Ocean surface turbulent energy exchanges are not smooth and steady but rather irregular and episodic, and consideration of the episodic nature of surface turbulent fluxes is essential for improving Arctic climate projections.

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“…The advent of new satellite observations promises to transform cloud-climate studies [1], especially in the polar regions [2]. Satellite observations are currently exploited to improve cloud parameterization in climate models [3], to measure cloud occurrence and persistence [4], and to study cloud-surface interactions [5].…”

Section: Introductionmentioning

confidence: 99%

“…The radiation balance in the polar regions is yet to be understood due to the lack of accurate cloud climatology [7][8][9]. This is mostly because of the difficulty in detecting clouds by passive satellite sensors over snow and ice surfaces, where it is difficult to distinguish between the reflectance and temperature of clouds and those of the underlying surface [2,10]. A further difficulty in polar regions is the false identification of clouds due to polar atmospheric temperature inversions, which causes clouds to be even warmer than the underlying snow or ice surface.…”

Section: Introductionmentioning

confidence: 99%

The Role of Emissivity in the Detection of Arctic Night Clouds

et al. 2017

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Detection of clouds over polar areas from satellite radiometric measurements in the visible and IR atmospheric window region is rather difficult because of the high albedo of snow, possible ice covered surfaces, very low humidity, and the usual presence of atmospheric temperature inversion. Cold and highly reflective polar surfaces provide little thermal and visible contrast between clouds and the background surface. Moreover, due to the presence of temperature inversion, clouds are not always identifiable as being colder than the background. In addition, low humidity often causes polar clouds to be optically thin. Finally, polar clouds are usually composed of a mixture of ice and water, which leads to an unclear spectral signature. Single and bi-spectral threshold methods are sometimes inappropriate due to a large variability of surface emissivity and cloud conditions. The objective of this study is to demonstrate the crucial role played by surface emissivity in the detection of polar winter clouds and the potential improvement offered by infrared hyperspectral observations, such as from the Infrared Atmospheric Sounding Interferometer (IASI). In this paper a new approach for cloud detection is proposed and validated exploiting active measurements from satellite sensors, i.e., the CloudSat cloud profiling radar (CPR) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). For a homogenous IASI field of view (FOVs), the proposed cloud detection scheme tallies with the combined CPR and CALIOP product in classifying 98.11% of the FOVs as cloudy and also classifies 97.54% of the FOVs as clear. The Hansen Kuipers discriminant reaches 0.95.

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Recent Advances in Arctic Cloud and Climate Research

Cited by 156 publications

References 71 publications

Thicker Clouds and Accelerated Arctic Sea Ice Decline: The Atmosphere‐Sea Ice Interactions in Spring

Thicker Clouds and Accelerated Arctic Sea Ice Decline: The Atmosphere‐Sea Ice Interactions in Spring

On the Increasing Importance of Air-Sea Exchanges in a Thawing Arctic: A Review

The Role of Emissivity in the Detection of Arctic Night Clouds

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