1. 1 NASA Ames Research Center Natural pollution events and their role in ice cloud formation Michal Segal-Rosenheimer, Patrick Hamill, S. Ramachandran ISSCP at 30 : What Do We Know and What Do We Still Need to Know? OR: What can we learn from such events on the interaction between aerosol and ice clouds?

2. 2 NASA Ames Research Center Introduction ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Potential effects: We know that increased IN concentration can cause mixed-phase clouds glaciation [e.g.; Seifert et al., 2011, JGR; Choi et al., 2010, PNAS], formation of new ice clouds [Sassen and Khvorostyanov 2008, Environ.Res.Let.] or a change of existing ice clouds microphysical properties (COT and D eff ) [e.g. Storelvmo et al., 2013, JGR] Volcanic DustBiomass burning

3. 3 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Dust, Ash, Soot are efficient IN, and have a wide range of Temperature and supersaturation “activation” values [Hoose and Möhler,2012] What do we know? Ground-based Lidar observations showed mixed-phase clouds glaciation [e.g. Seifert et al., 2011], and ice formation [e.g. Sassen and Khvorostyanov 2008] Global models (ECHAM; Hendricks et al., 2011 and CAM5; Liu et al., 2012] show that heterogeneous ice nucleation leads to fewer but larger crystals In-situ in-cloud sampling that measure IN amount under ambient conditions [e.g. DeMott et al., 2003] and residual chemical composition are used to derive model parameterizations for ice heterogeneous nucleation schemes. These IN are responsible for ice formation via Heterogeneous nucleation

4. 4 NASA Ames Research Center What do we still need to know? ISSCP at 30 : What Do We Know and What Do We Still Need to Know? While models can resolve concentrations, and ice properties in 3-D on a global scale; they only have sparse in-situ observations at specific locations to compare to [e.g. Hoose et al., 2010; Liu et al., 2012]. Various parameterization schemes predict different amounts of ice concentrations and relative effects of heterogeneous versus homogeneous nucleation [Liu et al., 2012] and show that results are very sensitive to parameterization assumptions [Hendricks et al., 2011] and aerosol characterization We still need better constraints on heterogeneous nucleation described in models

5. 5 NASA Ames Research Center How to bridge the gap? ISSCP at 30 : What Do We Know and What Do We Still Need to Know?

6. 6 NASA Ames Research Center Objectives and approach ISSCP at 30 : What Do We Know and What Do We Still Need to Know? To test whether heavy-aerosol events can serve as an “outdoor laboratory” that can improve our understanding on the connection between specific aerosol types and ice clouds incidence and their microphysical properties 1.To use heavy aerosol events – better spatial and temporal constrain to research domain. 2.To use spectral analysis, together with microphysical and state parameters from IR sounders to link aerosol-ice 3.Support observations with trajectory and dispersion/ chemical transformation analysis to constrain observed trends in ice cloud properties and amount that can be compared with specific model simulations.

7. 7 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? How does Heavy-Aerosol Events Affect Ice Cloud Formation? The Eyjafjallajokull 2010 Eruption case study

8. 8 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Constraining the case study domain – using Forward trajectory & literature [e.g. Petersen, 2010, Weather; Seifert et al., 2011, JGR]

9. 9 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Case study domain cloud related property distributions from AIRS – Eruption period

10. 10 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? (a 1 ) BTD pair values representative of ash from April 17 th (granule 133, 13:20UT), and the corresponding (a 2 ) MODIS-Aqua true color image granule (downloaded from EOSDIS Rapid Response website), which shows the ash plumes. Other panels (b-e) show zoomed-in areas for various pixels in (a), and their BT spectra (marked with different symbols) on the right of each row that further demonstrate the variety of spectral slopes for ice. Panels (f) show classification maps Symbols are the same as upper panels, and correspond to same BT spectra as above (for example, the diamond symbol was classified as ice containing ash). BTD relationships and thresholds are based on literature values (e.g. Francis et al., 2012; Clarisse et al. 2010, Gangale et al., 2010) And on local clear region thresholds.

11. 11 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Ice clouds Cloud Top Temperature bins Cloud top temperatures for the inherent AIRS FOV (15x15km) are taken from the Dual Regression (DR) algorithm package [Smith et al., 2012]

12. 12 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Cloud top Temperature distributions for each group

13. 13 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Ice fraction (percent in 0.5x0.5 o grid from total cloud) over pre and post-Eruption period using binned 15 min. data from SEVIRI Geostationary Cloud products

14. 14 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Cloud phase fraction over the whole domain – April 10-20 2010 SEVIRI (PATMOS-x retrieval L2B cloud product) Major eruption period

15. 15 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? 2-D distribution functions of Cloud Top Temp versus Cloud Height

16. 16 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? 2-D distribution functions of Cloud Top Temp versus Cloud Height

17. 17 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? a b c a b c Eruption Period

18. 18 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Eruption Period

19. 19 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Baseline Period a b c

20. 20 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Eruption Period

21. 21 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Baseline Period a b c

22. 22 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? 2-D distribution functions of R eff versus ice COT Ice COT

23. 23 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? 2-D distribution functions of R eff versus ice COT

24. 24 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Eruption Period a b c

25. 25 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Baseline Period a b c

26. 26 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? April 20, 2010, 4 days back-trajectory Ice cloud heights (4-6km) A B A B

27. 27 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Ice cloud heights (6-10km) April 20, 2010, 4 days back-trajectory A B A B

28. 28 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Specific case studies, when compared with simulations can aid in the decision of whether parameterization will be sufficient for the whole chemical group (e.g. dust) or whether it needs to be fine-tuned in the models for each region Case study results cover large regional areas, which are more proper to compare with Regional/global model simulations Int. Summary (work in progress…) It seem that heavy aerosol events can serve as a test-bed to identify cloud microphysics changes and processes via regional investigation such as the one demonstrated We have observed cloud formation in temperatures higher than the ones observed for Cleaner regions and baseline periods and between clear/polluted regions We see an increase in ice cloud amount (both relative to super-cooled phase and high clouds) relative to baseline periods We have observed R eff values increasing in mid-level clouds when comparing pre-eruption to post-eruption and baseline periods

29. 29 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Interact with global modeling groups (GEOS-Chem/CAM5) to investigate the specific Case studies and improve model parameterization (Pending proposal) Next steps (work in progress…) Create 2-D or higher dimensional PDF of cloud microphysical properties for several Pre-selected case studies designed to look at Ash, dust and Biomass-burning events. Combine aerosol fields vertical distributions using back-trajectory analysis and global Aerosol models (RAQMS/GOCART) to link properties to specific aerosol types Combine extracted cloud microphysical properties with aerosol properties derived Either from satellite products for Ash-Dust (IR hyperspectral sounders or CALIPSO) And for biomass-burning (MODIS or CALIPSO) Perform ice microphysical box modeling along back trajectories from cloud tops To better assess the conditions needed to form clean/polluted ice in case study regions

30. 30 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? © Michal Segal Acknowledgements: Andrew Heidinger and Mike Foster – Geostationary cloud products NASA Postdoctoral Program (NPP/ORAU) Weizmann Institute of Science, Israel

31. 31 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Case study domain cloud related property distributions from AIRS – Baseline period

32. 32 NASA Ames Research Center ISSCP at 30 : What Do We Know and What Do We Still Need to Know? Cloud phase fraction over the whole domain – April 10-20 2012