11 The potential impact of mineral dust on cirrus (and other) cloud formation: a trajectory modeling perspective Aldona Wiącek * and Thomas Peter ETH, Zürich, Switzerland * Now at Dalhousie University, Halifax, Canada MOCA-09 Joint Assembly Montréal, Canada, July 24 th, 2009 Funded by a Marie Curie Incoming International Fellowship under FP6 and the Canadian Foundation for Climate and Atmospheric Science

22 Outline  Why mineral dust? Where/when is it found?  How does mineral dust affect clouds?  African and Asian dust emission trajectory case studies  Statistical studies of trajectories from Africa and Asia  Discussion and Summary

33 Why mineral dust?  Highest burden and emitted mass of all aerosols: ~17 Tg and ~1500 Tg/year [Satheesh & Moorthy, 2005]  Anthropogenic contribution estimated at 0-20% [IPCC, AR4]  Efficient ice nucleus (IN)  insoluble and contains mineral lattice defects  crystallographic and chemical bond similarities to ice  particle size > 0.1 μm  Modulates the ice phase of clouds and precipitation (much smaller effect on water clouds due to poor CCN ability)  Indirect radiative effects highly uncertain

44 How does mineral dust affect cirrus and mixed-phase clouds? Cirrus cloud radiative properties are very sensitive to  ice crystal number concentration and size These are influenced by the ice formation mechanism  homogeneous nucleation on, e.g. H 2 SO 4 solution droplets  heterogeneous nucleation on, e.g. on dust IN Similarly, mineral dust will alter the radiative properties and lifetime of mixed-phase clouds Vast majority of atmospheric dust mass remains confined to altitudes < 7 km, but a little dust can go a long way to modify cirrus and mixed-phase clouds

55 Where does mineral dust come from?

66 Percentage of model grid box that is a preferential dust source, calculated from the extent of potential lake areas, excluding areas of actual lakes [Tegen et al., 2003, Quat. Sci. Rev]. Location of preferential dust sources W. African Bodélé Taklamakan Gobi

77 Case studies from regions of high OMI AI Calculated ~ day forward trajectories from each the following regions (1)West Sahara, 15 July % of trajectories ascended from 700 to 450 hPa (2) Taklimakan, 20 May % of trajectories ascended from 700 to 450 hPa Why so different? pressure [hPa]

88 Unusual Asian topography encourages lifting (but only in the Taklimakan, not in the Gobi) Topography [m]

99 Why so different? (1) Potential temperature (θ surf ) as high in Asia as in Africa (due to higher dust source elevation in Asia) (2) Altitude corresponding to θ surf higher in Asia θ surf  320 K

10 Statistical trajectory study setup 7-day forward trajectories: 4 times per day (00, 06, 12, 18) 365 days in points covering the Tarim basin at 1° 61,320 trajectories (1,778,280 saved points) High-resolution ECMWF fields (T799 – 25 km) Traced p, T, Q Calculated RH water, RH ice using Q (t=0) 10 km 5 km 0 6 km 4 km 2 km 0

11 Same procedure for other dust sources Gobi desert divided into East and West but results very similar (peak activity MAM) Bodélé depression (Africa, active all year) West Africa (peak activity JJA) 42 starting points roughly span each region at 1° resolution

12 avgdrywet RH ice [%] Liquid water cloud MPC MPC’ “Warm thin cirrus” “Cold thin cirrus” “Classical cirrus” Mixed-phase clouds Classical cirrus’ Cloud formation processes Temperature [K] # saturating trajectories [K -1 ] Distribution of trajectories from Taklamakan Wiacek & Peter [2009, GRL, in press]

13 Results by region (% of ~ 1.8 million points originating from each region) TaklimakanGobiWest AfricaBodélé Crashed Clear sky Oscillatory Clear Sky Cloudy Oscillatory Cloudy Wiacek et al., [to be submitted to ACPD]

14 Breakdown of cloudy points only % of all trajectory points (1.8 Mio in each region) No effect on “cold thin cirrus” Do “warm thin cirrus” exist at all? Dust gets into “classical cirrus” only via MPC Potentially big effect here Unlikely to play a big role Wiacek et al., [to be submitted to ACPD] invisible

15 Wiacek et al., [to be submitted to ACPD] Details of Temperature for selected cloud types

16 Some lab measurements of ice nucleation, old and new (1)AIDA chamber experiments: Arizona test dust [Möhler et al., 2006]. (2)AIDA chamber experiments: Saharan and Taklimakan dust [Möhler et al., 2006]. (3)AIDA warm measurements: Saharan and Asian dust [Field et al., 2006]. (4)CFDC measurements: kaolinite (white squares), montmorillonite (white diamonds) [Salam et al., 2006]. (5)Thermal diffusion chamber: kaolinite (upper blue curve), Denver local soil (center blue curve), silver iodide (lower blue curve) [Schaller & Fukuta, 1979]. (6)Microscope cold stage: Montmorillonite (upper horizontal white line: unprocessed; lower horizontal white line: preactivated [Roberts & Hallett, 1968]. (7)SEM cold stage: illite and kaolinite [Zimmermann et al., 2008]

17 Summary  The availability of bare ice nuclei for ‘classical’ cold cirrus is negligible from both African and Asian source regions  Mineral dust unlikely competitor to homogeneous nucleation  The availability of bare ice nuclei for ‘warm thin cirrus’ could be significant as a dehydration pathway, and is higher from Asian deserts, however, their existence remains speculative given the lack of field measurements  The greatest influence of mineral dust is found to be on mixed-phase clouds (0°C < T < -40°C), especially from Asian deserts