Presentation on theme: "Arctic Ice Clouds and their Interactions with aerosols Éric Girard, UQAM Research interests and recent work My contribution to NETCARE What is currently."— Presentation transcript:
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 th 2013, U. of Toronto
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.
Ice and Snow layers Hypothesis Dehydration Greenhouse Feedback (DGF) Less H 2 O vapour Acid Aerosols * * * * * * * * * * * * * * * * * * * * * * * * * * * ** * * * * * * * * Low Acid Aerosols Hydrophilic warmercolder Reduction of the greenhouse effect 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 Small cooling rate by IR cooling or by weak ascent Thin Ice Clouds type 1 Thin Ice Clouds type 2 Cold Ice and Snow Surface
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)
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. ISDAC flights Observations: Analysis of ISDAC ice cloud cases and their relationship to aerosols Observations: Remote sensing and backtrajectory analysis
Figure 3: Averaged IWC (a), N ic (b) and R ei (c) versus RH Ice over each 2% period. And RH Ice versus T a over each 2.5°C period, with standard deviation associated for ice clouds defined in the Table 2. a)b)b) c)d)d) Jouan et al. (JGR,2012)
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. Figure 9 : Dardar Mask track section observed on March 31 th (a) at 13:48 UTC and on March 30 th (b) at 13:05, 2008 from of the synergistic Cloudsat radar and CALIPSO lidar. AL-1 CL-1 AL-2 Jouan et al. (ACPD, 2013)
Until recently, parameterizations of ice nucleation were based on limited field studies. Empirical relationships between the IN concentration and T and Si were derived. From Meyers et al. (1992) Objective: Implement more physically-based IN parameterizations based on aerosol physico-chemical properties. Eastwood et al. (2009) Modeling: Ice cloud simulations and parameterizations of ice nucleation (e.g. UBC lab studies)
Aerosol scenarios and simulated flights ScenarioAuthorsINContact angle NAT1Eastwood et al, 2008uncoatedθ = 12 o NAT2Eastwood et al, 2008uncoatedθ → P(θ) ACEastwood et al. 2009Acidicθ = 26 o ORIMeyer et al, # VolDateTimeLocationAir mass TIC F12April 5 th, :15: :34:05Barrow - ( ; )Pristine TIC-1 F13April 5 th, :35: :00:05Barrow – ( ; )Pristine TIC-1 F21April 15 th, :55: :17:24Barrow - ( ; )Pollué TIC-2 F29April 29 th, :08: :27:51Fairbanks - (208,329 ; )Pollué TIC-2 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.
Lab studies and modeling 10 Ni (simulated) vs Ni (obs): unpolluted air mass (F12 and F13) Bias: +32 L -1 Bias: -187 L -1 New parameterization Original parameterization Breau-Roussel and Girard (JGR, 2013)
Ni (simulated) vs Ni (obs): polluted air mass (F21 and F29) New parameterizationOriginal parameterization Bias: +9 L -1 Lab studies and modeling Breau-Roussel and Girard (JGR, 2013)
Acid coating on IN and its impact on the Arctic climate Girard et al. (Int. J. Clim., 2013) ~ -3K
Mixed-phase clouds observed during SHEBA Du et al. (Atmos. Res., 2011)
My contribution to NETCARE 1.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. 2.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. 3.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.
What is currently needed to go forward? 1.We need to relate the atmospheric IN chemical composition and their ice nucleation ability in both types of ice clouds. 2.Immersion of unactivated haze droplets and deposition nucleation are important to better understand for the simulation of ice clouds.
Sulphate emission and transport AMAP Assessment Report: Arctic Pollution Issues. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway. Xii+859 pp Arctic haze: the Arctic can be very polluted during winter L H