A comprehensive in situ and remote sensing data set from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign

Ehrlich, André; Wendisch, Manfred; Lüpkes, Christof; Buschmann, Matthias; Bozem, Heiko; Chechin, Dmitri; Clemen, Hans-Christian; Dupuy, Régis; Eppers, Oliver; Hartmann, Jörg; Herber, Andreas; Jäkel, Evelyn; Järvinen, Emma; Jourdan, Olivier; Kästner, Udo; Kliesch, Leif-Leonard; Köllner, Franziska; Mech, Mario; Mertes, Stephan; Neuber, Roland; Ruiz-Donoso, Elena; Schnaiter, M.; Schneider, Johannes; Stapf, Johannes; Zanatta, Marco

doi:10.5194/essd-11-1853-2019

Cited by 67 publications

(66 citation statements)

References 75 publications

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“…Red (80 %) and light-blue (15 %) contours indicate the campaignaverage sea ice fraction from daily satellite-based sea ice data (Spreen et al, 2008). mined by dropsondes (Ehrlich et al, 2019a) and aircraft in situ observations (Hartmann et al, 2019) during ascents and descents in the vicinity of the low-level flight sections.…”

Section: Airborne Measurements and Instrumentationmentioning

confidence: 99%

Reassessment of shortwave surface cloud radiative forcing in the Arctic: consideration of surface-albedo–cloud interactions

et al. 2020

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Abstract. The concept of cloud radiative forcing (CRF) is commonly applied to quantify the impact of clouds on the surface radiative energy budget (REB). In the Arctic, specific radiative interactions between microphysical and macrophysical properties of clouds and the surface strongly modify the warming or cooling effect of clouds, complicating the estimate of CRF obtained from observations or models. Clouds tend to increase the broadband surface albedo over snow or sea ice surfaces compared to cloud-free conditions. However, this effect is not adequately considered in the derivation of CRF in the Arctic so far. Therefore, we have quantified the effects caused by surface-albedo–cloud interactions over highly reflective snow or sea ice surfaces on the CRF using radiative transfer simulations and below-cloud airborne observations above the heterogeneous springtime marginal sea ice zone (MIZ) during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign. The impact of a modified surface albedo in the presence of clouds, as compared to cloud-free conditions, and its dependence on cloud optical thickness is found to be relevant for the estimation of the shortwave CRF. A method is proposed to consider this surface albedo effect on CRF estimates by continuously retrieving the cloud-free surface albedo from observations under cloudy conditions, using an available snow and ice albedo parameterization. Using ACLOUD data reveals that the estimated average shortwave cooling by clouds almost doubles over snow- and ice-covered surfaces (−62 W m−2 instead of −32 W m−2), if surface-albedo–cloud interactions are considered. As a result, the observed total (shortwave plus longwave) CRF shifted from a warming effect to an almost neutral one. Concerning the seasonal cycle of the surface albedo, it is demonstrated that this effect enhances shortwave cooling in periods when snow dominates the surface and potentially weakens the cooling by optically thin clouds during the summertime melting season. These findings suggest that the surface-albedo–cloud interaction should be considered in global climate models and in long-term studies to obtain a realistic estimate of the shortwave CRF to quantify the role of clouds in Arctic amplification.

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Section: Airborne Measurements and Instrumentationmentioning

confidence: 99%

Reassessment of shortwave surface cloud radiative forcing in the Arctic: consideration of surface-albedo–cloud interactions

et al. 2020

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“…Initially, a separation of overcast, cloudless and broken cloud conditions was made from the all-sky camera observations on Polarstern. Due to the availability of observations with a cloud radar of type Mira-35, and multiwavelength polarization Raman lidar Polly-XT (Engelmann et al, 2016) during PASCAL (Wendisch et al, 2019;Macke and Flores, 2018), these were used in addition to identify the presence of multilayer clouds, a separation which has not been considered in previous studies (Madhavan et al, 2016(Madhavan et al, , 2017Lohmann et al, 2016;Lohmann and Monahan, 2018). Cirrus clouds and low, geometrically thin stratus clouds were also observed and have been considered together as thin clouds due to their low occurrence frequency to study their effects on ATg.…”

Section: Sky Classificationmentioning

confidence: 99%

Spatiotemporal variability of solar radiation introduced by clouds over Arctic sea ice

et al. 2020

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Abstract. The role of clouds in recent Arctic warming is not fully understood, including their effects on the solar radiation and the surface energy budget. To investigate relevant small-scale processes in detail, the intensive Physical feedbacks of Arctic planetary boundary layer, Sea ice, Cloud and AerosoL (PASCAL) drifting ice floe station field campaign was conducted during early summer in the central arctic. During this campaign, the small-scale spatiotemporal variability of global irradiance was observed for the first time on an ice floe with a dense network of autonomous pyranometers. A total of 15 stations were deployed covering an area of 0.83 km×1.59 km from 4–16 June 2017. This unique, open-access dataset is described here, and an analysis of the spatiotemporal variability deduced from this dataset is presented for different synoptic conditions. Based on additional observations, five typical sky conditions were identified and used to determine the values of the mean and variance of atmospheric global transmittance for these conditions. Overcast conditions were observed 39.6 % of the time predominantly during the first week, with an overall mean transmittance of 0.47. The second most frequent conditions corresponded to multilayer clouds (32.4 %), which prevailed in particular during the second week, with a mean transmittance of 0.43. Broken clouds had a mean transmittance of 0.61 and a frequency of occurrence of 22.1 %. Finally, the least frequent sky conditions were thin clouds and cloudless conditions, which both had a mean transmittance of 0.76 and occurrence frequencies of 3.5 % and 2.4 %, respectively. For overcast conditions, lower global irradiance was observed for stations closer to the ice edge, likely attributable to the low surface albedo of dark open water and a resulting reduction of multiple reflections between the surface and cloud base. Using a wavelet-based multi-resolution analysis, power spectra of the time series of atmospheric transmittance were compared for single-station and spatially averaged observations and for different sky conditions. It is shown that both the absolute magnitude and the scale dependence of variability contains characteristic features for the different sky conditions.

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“…All data listed and described here are published in the World Data Center PANGAEA (Ehrlich et al, 2019b, https://doi.org/ 10.1594/PANGAEA.902603). Table 5 links each instrument to individual data sets and references.…”

Section: Data Availabilitymentioning

confidence: 99%

“…calibrated, and validated data are published in the world data center PANGAEA as instrument-separated data subsets (Ehrlich et al, 2019b, https://doi.org/10.1594/PANGAEA.902603).…”

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confidence: 99%

A comprehensive in situ and remote sensing data set from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign

Ehrlich¹,

Wendisch²,

Lüpkes³

et al. 2019

Preprint

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Abstract. The Arctic Cloud Observations Using Airborne Measurements during Polar Day (ACLOUD) campaign was carried out North-West of Svalbard (Norway) between 23 May–26 June 2017. The objective of ACLOUD was to study Arctic boundary layer and mid-level clouds and their role in Arctic Amplification. Two research aircraft (Polar 5 and 6) jointly performed 22 research flights over the transition zone between open ocean and closed sea ice. Both aircraft were equipped with identical instrumentation for measurements of basic meteorological parameters, as well as for turbulent and and radiative energy fluxes. In addition, on Polar 5 active and passive remote sensing instruments were installed, while Polar 6 operated in situ instruments to characterize cloud and aerosol particles as well as trace gases. A detailed overview of the specifications, data processing, and data quality is provided here. It is shown, that the scientific analysis of the ACLOUD data benefits from the coordinated operation of both aircraft. By combining the cloud remote sensing techniques operated on Polar 5, the synergy of multiinstrument cloud retrieval is illustrated. The remote sensing methods are validated using truly collocated in situ and remote sensing observations. The data of identical instruments operated on both aircraft are merged to extend the spatial coverage of mean atmospheric quantities and turbulent and radiative flux measurement. Therefore, the data set of the ACLOUD campaign provides comprehensive in situ and remote sensing observations characterizing the cloudy Arctic atmosphere. All processed, 1 calibrated, and validated data are published in the world data center PANGAEA as instrument-separated data subsets (Ehrlich et al., 2019b, https://doi.org/10.1594/PANGAEA.902603).

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A comprehensive in situ and remote sensing data set from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign

Cited by 67 publications

References 75 publications

Reassessment of shortwave surface cloud radiative forcing in the Arctic: consideration of surface-albedo–cloud interactions

Reassessment of shortwave surface cloud radiative forcing in the Arctic: consideration of surface-albedo–cloud interactions

Spatiotemporal variability of solar radiation introduced by clouds over Arctic sea ice

A comprehensive in situ and remote sensing data set from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign

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