1. Arctic Ice Clouds and their Interactions with aerosols
Éric Girard, UQAM
Research interests and recent work
My contribution to NETCARE
What is currently needed to go forward?
NETCARE First Workshop, November 18-19th 2013, U. of Toronto

2. My research interests Modeling of ice clouds and mixed-phase clouds.
Interactions between highly acidic aerosols and Arctic clouds and radiation (dehydration-greenhouse feedback). Investigated using in-situ obs, remote sensing and modeling.

3. * * * * * * * * * * colder warmer Hypothesis
Dehydration Greenhouse Feedback (DGF)
Acidic coating on IN leads to the formation of fewer but largerice crystals (de-activation effect), which precipitate more efficiently. The airmass dehydrates and the greenhouse effect decreases
Thin Ice Clouds type 1
Thin Ice Clouds type 2
Reduction of the greenhouse effect
Small cooling rate by IR cooling or by weak ascent * * *
Low Acid Aerosols
Hydrophilic * *
Acid Aerosols * * * * * *
Less H2O vapour
colder
warmer
Cold Ice and Snow Surface
Ice and Snow layers

4. Recent work
Observations: Analysis of ISDAC ice cloud cases and their relationship to aerosols
Observations: Remote sensing and backtrajectory analysis
Modeling: Ice cloud simulations and parameterizations of ice nucleation (e.g. UBC lab studies)

5. Observations: Analysis of ISDAC ice cloud cases and their relationship to aerosols
Observations: Remote sensing and backtrajectory analysis
ISDAC flights
Table 2: Table of temporal and spatial coordinates of the profiles of ice clouds selected by the algorithm of table 1 and for which the cloud temperature drops below -30±0.5°C, during the ISDAC measurement campaign.

6. Jouan et al. (JGR,2012) a) b) c) d)
Figure 3: Averaged IWC (a), Nic (b) and Rei (c) versus RHIce over each 2% period. And RHIce versus Ta over each 2.5°C period, with standard deviation associated for ice clouds defined in the Table 2.
Jouan et al. (JGR,2012)

7. 31/03
13:50
30/03
13:12
B1 B2
Figure 8 : Calipso track sections (line) and FLEXPART air mass positions (*) along FLEXPART trajectories initialized in the boxes B1 and B2 of Figure 7. The color scale indicates the elapsed time in hours between the CALIPSO observation and the aircraft observation.
AL-1
CL-1
AL-2
Figure 9 : Dardar Mask track section observed on March 31th (a) at 13:48 UTC and on March 30th (b) at 13:05, 2008 from of the synergistic Cloudsat radar and CALIPSO lidar.
Jouan et al. (ACPD, 2013)

8. Modeling: Ice cloud simulations and parameterizations of ice nucleation (e.g. UBC lab studies)
Until recently, parameterizations of ice nucleation were based on limited field studies. Empirical relationships between the IN concentration and T and Si were derived.
Objective: Implement more physically-based IN parameterizations based on aerosol physico-chemical properties.
Eastwood et al. (2009)
From Meyers et al. (1992)

9. Aerosol scenarios and simulated flights
Authors IN
Contact angle
NAT1
Eastwood et al, 2008
uncoated
θ = 12o
NAT2
θ → P(θ) AC
Eastwood et al. 2009
Acidic
θ = 26o
ORI
Meyer et al, 1992
Meyers et al is an empirical relationship and does not account for solution coating.
AC, NAT1 and NAT2 are based on lab experiment. The contact angle is used to differentiate acid-coated and uncoated IN in the classical nucleation theory.
# Vol
Date
Time
Location
Air mass
TIC
F12
April 5th, 2008
01:15: :34:05
Barrow - ( ; )
Pristine
TIC-1
F13
20:35: :00:05
Barrow – ( ; )
F21
April 15th, 2008
00:55: :17:24
Barrow - ( ; )
Pollué
TIC-2
F29
April 29th, 2008
04:08: :27:51
Fairbanks - (208,329 ; )

10. Lab studies and modeling
Ni (simulated) vs Ni (obs): unpolluted air mass (F12 and F13)
Bias: +32 L-1
Bias: -187 L-1
Original parameterization
New parameterization
Breau-Roussel and Girard (JGR, 2013) 10

11. Lab studies and modeling
Ni (simulated) vs Ni (obs): polluted air mass (F21 and F29)
Bias: +9 L-1
Bias: +9 L-1
New parameterization
Original parameterization
Breau-Roussel and Girard (JGR, 2013)

12. ~ -3K
Acid coating on IN and its impact on the Arctic climate
Girard et al. (Int. J. Clim., 2013)

13. Mixed-phase clouds observed during SHEBA
Du et al. (Atmos. Res., 2011)

14. My contribution to NETCARE
Implement new ice nucleation parameterizations already existing or to be developed with NETCARE observations. In addition to the CNT approach, singular hypothesis will be tested. Other parameterizations from CFDC observations, aerosols collected in the field tested in lab and “pure” aerosols tested in lab will also be implemented. Test and validate these parameterizations against already available observations (e.g. ISDAC) and new observations from NETCARE.
Couple GEM to the ECMWF Aerosol Reanalysis (ECMWF-MACC) and test this new version with the new parameterizations. A comparison with the fully coupled version of GEM (GEM-MACH) and/or with GEM-CAM is also possible.
The new version of the model will be used to perform pan Arctic simulations of the effect of acid coating on Arctic clouds and radiation.

15. What is currently needed to go forward?
We need to relate the atmospheric IN chemical composition and their ice nucleation ability in both types of ice clouds.
Immersion of unactivated haze droplets and deposition nucleation are important to better understand for the simulation of ice clouds.

16. Sulphate emission and transport
Arctic haze: the Arctic can be very polluted during winter H L
AMAP Assessment Report: Arctic Pollution Issues. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway. Xii+859 pp