Observations of the Arctic boundary layer clouds during ACSE 2014 School of Earth and Environment Faculty of Environment Observations of the Arctic boundary layer clouds during ACSE 2014 Peggy Achtert, Georgia Sotiropoulou, Michael Tjernström, Joseph Sedlar, Barbara J. Brooks, Ian M. Brooks, P. Ola G. Persson, John Prytherch, Dominic J. Salisbury, Matthew D. Shupe, Paul E. Johnston, Dan Wolfe

Arctic Cloud Summer Experiment (ACSE)...a part of... Swedish-Russian-US Arctic Ocean investigation of Climate-Cryosphere-Carbon Interactions (SWERUS-C3) Ice melt during summer increases; there will be more ice-free summers and more spring and autumn with “marginal ice”. Satellite observations provide evidence that the cloud fraction during spring and autumn is correlated with the amount of open water; changes in Arctic climate reflected in changes in atmospheric/cloud conditions. The impact of changes in surface conditions on cloud and boundary layer properties have to be understood for properly representing the changing Arctic in models. Models currently do a rather (very) poor job of representing Arctic boundary layer clouds.

Arctic Cloud Summer Experiment (ACSE)...a part of... Swedish-Russian-US Arctic Ocean investigation of Climate-Cryosphere-Carbon Interactions (SWERUS-C3) Cruise July 3 – Oct 5 2014 Leg 1: Ocean sampling Leg 2: Sediment coring ACSE runs for whole cruise Surface fluxes Cloud radar Lidar (wind + depolarization) Ceilometer Scanning microwave radiometer 6-hourly radiosondes Wave spectra ACSE aims to look at properties of BL clouds as well as BL structure and processes as a function of surface conditions

Turbulent flux system Doppler lidar Microwave radiometer

Campaign overview: Temperature Blob of Death, Tjernström et al., GRL, 2015 Seasons defined by change in circulation rather then insulation summer autumn

Campaign overview: Cloud heights, inversion strength Example leg1, low clouds + fog Example leg2, mixed-phase clouds Fog top Cloud top Inversion base

Doppler lidar depolarization ratio Ceilometer signal Doppler lidar signal Example leg1, low clouds + fog Doppler lidar depolarization ratio Doppler lidar vertical wind 5 10 15 20

Doppler lidar depolarization ratio Ceilometer signal Doppler lidar signal Example leg2, mixed-phase clouds Doppler lidar depolarization ratio Doppler lidar vertical wind 5 10 15 20

Inversion statistics: Lowest inversion over ice in summer; no preferred height over ice in autumn Inversion thickness is strongest over ice in summer Inversion thickness over water decreases slightly from summer to autumn Inversion strength is similar for all cases except summer over ice

Cloud height statistics: Lower cloud base during summer, particularly over ice Clouds over water in autumn are shifted upwards in height Clouds over ice in summer are thinnest

Flux statistics: Little difference in scaled friction velocity Larger sensible heat flux over water; larger sensible heat flux in autumn Strong change in latent heat flux over ice between summer and autumn; little change over water

Relative frequency distributions of wind speed and temperature: Scaled profiles: surface = -1; jet core = 0; jet top = 1 Wind normalized to jet core wind speed Temperature surface corrected and normalized to temperature at top of turbulent layer Similar median wind profiles; speed at jet core 65% - 100% higher then above Summer: neutral PBL halfway up to jet core height, capped by temperature inversion

Conclusion and next steps Summer: surface-based inversion over ice; elevated inversion over water No difference in autumn Fog and stratus clouds more frequent over summer sea ice during episodes of warm-air advection and strong surface inversion (turbulent heat flux to the surface) Liquid clouds dominate over open water conditions in summer Mixed-phase clouds dominantly occurred in autumn (in contrast to previous ASCOS cruises) Apply CloudNet and Shupe algorithm to investigate the occurrence of different cloud types (liquid, mixed-phase, and ice) Investigate properties of heterogeneous ice formation and seeding in the Arctic Tjernström et al. (2015): Warm‐air advection, air mass transformation and fog causes rapid ice melt Sotiropoulou et al., in preparation: Arctic Clouds in Summer Experiment (ACSE): Boundary layer and cloud characteristics over ice and open-water, during the melt and freeze-up seasons.