1. 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

2. 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.

3. 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
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

4. Turbulent flux system
Doppler lidar
Microwave radiometer

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

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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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.