1. ACCACIA – Science Overview FAAM Pre-campaign Briefing

2. ACCACIA Objectives
Understand the microphysical properties of Arctic clouds and their dependence on aerosol properties
Determine the natural and anthropogenic sources of aerosol within the Arctic boundary layer
Determine boundary layer structure and turbulent mixing properties
Quantify the feedbacks between clouds, aerosol, sea ice and the wider climate system
WP1 – Aircraft measurements
WP1.1: BL structure, dynamics, surface fluxes
WP1.2: Aerosol & cloud microphysics
WP1.3: cloud radiative processes
WP2 – Surface measurements
WP2.1: ship-based in-situ measurements of aerosol & precursor gases
WP2.2: laboratory bubble tank experiments of organic aerosol production
WP2.3: DMS concentrations & fluxes

3. ACCACIA Objectives
1. Understand the microphysical properties of Arctic clouds and their dependence on aerosol properties:
What are the microphysical properties of remote Arctic stratus & their relationship with different aerosol sources?
How do aerosol and cloud properties vary with the extent of sea-ice cover?
Develop and test new process models and parameterizations specific to the Arctic for cloud microphysics, aerosol processes
2. Determine the natural and anthropogenic sources of aerosol within the Arctic boundary layer:
Quantify Arctic surface sources of aerosol and precursor gases
Develop parameterizations of aerosol surface sources dependent upon ice fraction and season
Estimate entrainment fluxes of aerosol from above the BL
3. Determine boundary layer structure and turbulent mixing properties:
Determine the relationships between cloud microphysics and radiatively driven turbulent dynamics
Develop and test parameterizations of turbulent dynamics for shallow/stable Arctic boundary layers and surface-atmosphere exchange over sea ice
4. Quantify the feedbacks between clouds, aerosol, sea ice and the wider climate system:
Improve the aerosol-chemistry sub-model of HadGEM3 (UKCA)
Adapt the state of the art climate model HadGEM3 to include new cloud physics
Implement new turbulent exchange parameterizations in HadGEM3 based on (3)
Conduct future simulations to determine the impact of the new physics on climate change and consequent evolution of cloud properties

4. Measurements FAAM focus is on: BAS MASIN aircraft will also by flying
Cloud microphysical properties
Aerosol properties above/in/below cloud
Turbulence structure of BL
BAS MASIN aircraft will also by flying
Greater emphasis on near surface aerosol and fluxes
BUT has more stable IR radiative flux sensors – should do an above cloud leg over low-level legs
Surface measurements from icebreaker RV Lance
Manchester & York

5. Current ice conditions (19 Feb 2013)
Retreat north of Svalbard is worse than last year – beyond operational range of FAAM.
BUT...ice edge is closer to Svalbard to west. Can expect ~2.5 hours on task here after refuel at Longyearbyen

6. Nominal ship track

7. Flight Plan A1 (the ideal)
profile down from transit cruise altitude to minimum safe altitude to give deep profile OR initial dropsonde for wind/thermodynamic profile and aircraft descent to s
stacks of horizontal legs (ideally oriented across-wind) – each successive stack moved upwind over: open ocean, ice edge, MIZ, solid ice
‘surface flux’ leg at 100’ (optional – MASIN will do extensive flux runs – need to coordinate)
Below cloud
Multiple legs in cloud,
Above cloud top
Time constraints may limit number of stacks, or necessitate legs along-wind to maximise sampling efficiency. Some aerosol/cloud microphysics measurements require long run-lengths to acquire sufficient data – details TBC, but may require prioritising specific legs when time is limited.
Deep profile up from minimum safe altitude to cruising altitude
transit back may include a line of dropsondes

8. Deep profile up from minimum safe altitude to cruising altitude
Flight Plan A2
As A1
Profile to moderate altitude and transit back with sawtooth profiles through cloud
Flight Plan A3
In absence of cloud a similar flight pattern to A1 just above boundary layer top, with focus on aerosol properties and boundary-layer structure.
Flight Plan A4
profile down from transit cruise altitude to minimum safe altitude to give deep profile
stacks of horizontal legs – working downwind over: solid ice, MIZ, ice edge, open ocean.
Time leg lengths and flight pattern to be pseudo-Lagrangian, i.e. following an air parcel downstream (see figure, but with box location over ice edge or MIZ)
Deep profile up from minimum safe altitude to cruising altitude
transit to include dropsondes

9. Suggested modifed plan for operation to west of Svalbard with wind north/south:
Stacks of legs over open water/MIZ/ice with long fetch over respective surfaces – either 2/3 stacks along wind, or single stack across wind with longer legs.
1 deep profile + shallow profiles for BL structure over water/MIZ/ice
wind

10. Alternative Science Any conditions: Ship overflight
On task location: In vicinity of the research vessel – comparison of aerosol measurements
Aims: Flight overpasses at several altitudes, (including MSA), perhaps in an L shape around the R/V, to map out the local boundary-layer structure, air-sea interaction, cloud microphysics (if clouds) and aerosol properties.
Synoptic Situation C: Frontal systems 
With a low pressure centred close to Svalbard preference would be to work in sector with flow that has spent longest over sea ice.
Synoptic Situation D: Strong winds in the vicinity of Svalbard
On task location: Coasts around Svalbard.
Aims: Observe the well-defined low-level orographic jets that are known to occur around Svalbard mountains, e.g. tip jets, gap winds, and barrier flows. Examine the boundary-layer structure of these and associated air-sea fluxes and clouds.

11. Aerosol plume trajectories
Forecast products
Met Office
Standard UM forecast
Possibly 4km & interactive aerosol
Norwegian Met Service
WRF forecasts at Leeds
Aerosol plume trajectories
Most (all?) forecast products set up for viewing on Google Earth – viewable on laptops in flight.
Satellite imagery via NEODAAS
MODIS/AVHRR visible, IR
SST (data & image)
Chlorophyll (data & image)

12. Sea ice

13. Sea ice + cloud from Norwegian Met Service