Presentation on theme: "Arctic Ice Clouds and their Interactions with aerosols"— Presentation transcript:
1Arctic Ice Clouds and their Interactions with aerosols Éric Girard, UQAMResearch interests and recent workMy contribution to NETCAREWhat is currently needed to go forward?NETCARE First Workshop, November 18-19th 2013, U. of Toronto
2My 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 decreasesThin Ice Clouds type 1Thin Ice Clouds type 2Reduction of the greenhouse effectSmall cooling rate by IR cooling or by weak ascent***Low Acid AerosolsHydrophilic**Acid Aerosols******Less H2O vapourcolderwarmerCold Ice and Snow SurfaceIce and Snow layers
4Recent workObservations: Analysis of ISDAC ice cloud cases and their relationship to aerosolsObservations: Remote sensing and backtrajectory analysisModeling: Ice cloud simulations and parameterizations of ice nucleation (e.g. UBC lab studies)
5Observations: Analysis of ISDAC ice cloud cases and their relationship to aerosols Observations: Remote sensing and backtrajectory analysisISDAC flightsTable 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.
6Jouan 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)
731/0313:5030/0313:12B1 B2Figure 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-1CL-1AL-2Figure 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)
8Modeling: 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)
9Aerosol scenarios and simulated flights AuthorsINContact angleNAT1Eastwood et al, 2008uncoatedθ = 12oNAT2θ → P(θ)ACEastwood et al. 2009Acidicθ = 26oORIMeyer et al, 1992Meyers 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.# VolDateTimeLocationAir massTICF12April 5th, 200801:15: :34:05Barrow - ( ; )PristineTIC-1F1320:35: :00:05Barrow – ( ; )F21April 15th, 200800:55: :17:24Barrow - ( ; )PolluéTIC-2F29April 29th, 200804:08: :27:51Fairbanks - (208,329 ; )
10Lab studies and modeling Ni (simulated) vs Ni (obs): unpolluted air mass (F12 and F13)Bias: +32 L-1Bias: -187 L-1Original parameterizationNew parameterizationBreau-Roussel and Girard (JGR, 2013)10
11Lab studies and modeling Ni (simulated) vs Ni (obs): polluted air mass (F21 and F29)Bias: +9 L-1Bias: +9 L-1New parameterizationOriginal parameterizationBreau-Roussel and Girard (JGR, 2013)
12~ -3KAcid coating on IN and its impact on the Arctic climateGirard et al. (Int. J. Clim., 2013)
13Mixed-phase clouds observed during SHEBA Du et al. (Atmos. Res., 2011)
14My 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.
15What 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.
16Sulphate emission and transport Arctic haze: the Arctic can be very polluted during winterHLAMAP Assessment Report: Arctic Pollution Issues. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway. Xii+859 pp