0000000000759244
AUTHOR
Mario Mech
Synoptic development during the ACLOUD/PASCAL field campaign near Svalbard in spring 2017
Abstract. The two concerted field campaigns Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL) took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL), as well as surface-based stations, a tethered balloon, and satellites. Here, we present the synoptic development during the 35 day period of the campaigns, using classical near-surface and upper-air meteorological observations, as well as operational satellite and model data. Over the ca…
The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multiplatform Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification
A consortium of polar scientists combined observational forces in a field campaign of unprecedented complexity to uncover the secrets of clouds and their role in Arctic amplification. Two research aircraft, an icebreaker research vessel, an ice-floe camp including an instrumented tethered balloon, and a permanent ground-based measurement station were employed in this endeavour. Clouds play an important role in Arctic amplification. This term represents the recently observed enhanced warming of the Arctic relative to the global increase of near-surface air temperature. However, there are still important knowledge gaps regarding the interplay between Arctic clouds and aerosol particles, surfa…
A comprehensive in situ and remote sensing data set from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign
The Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign was carried out north-west of Svalbard (Norway) between 23 May and 6 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 radiative energy fluxes. In addition, on Polar 5 active and passive remote sensing instruments were installed, while Polar 6 …
Meteorological conditions during the ACLOUD/PASCAL field campaign near Svalbard in early summer 2017
Abstract. The two concerted field campaigns, Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL), took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL) and a tethered balloon, as well as ground-based stations. Here, we present the synoptic development during the 35-day period of the campaigns, using near-surface and upper-air meteorological observations, as well as operational satellite, analysis, and reanalysis data. Over the campaign…
Cloud top altitude retrieved from Lidar measurements during ACLOUD at 1 second resolution
During the ACLOUD aircraft campaign (23.5.2017 - 26.6.2017) the AMALi Lidar was installed mostly nadir pointing. This dataset contains the cloud top altitude from those measurements (altitudes with a strong signal increase) as well as a cloud mask, derived from the optical depth of the column at 1 second resolution. The majority of the data was collected northwest of the Svalbard archipelago. More details on the campaign can be found in Wendisch 2018 and Ehrlich 2019 and here (https://home.uni-leipzig.de/~ehrlich/ACLOUD_wiki_doku). Please check the data documentation (https://download.pangaea.de/reference/108729/attachments/readme_documentation_AMALi_cloudtop.pdf) before using this dataset.