1. The Role of Aerosols in Cloud Growth, Suppression, and Precipitation: Yoram Kaufman and his Contributions  Aerosol optical & microphysical properties –Ground-based sunphotometer measurements Optical thickness Optical thickness Size distribution & absorption properties Size distribution & absorption properties –Aircraft remote sensing SCAR-B and field validation/prototyping SCAR-B and field validation/prototyping –Satellite remote sensing Dense dark vegetation Dense dark vegetation Spectral surface albedo characterization Spectral surface albedo characterization MODIS aerosol over land MODIS aerosol over land  Cloud-aerosol interaction – Relationship between absorbing and nonabsorbing aerosol & cloud formation, cloud cover, and optical properties Michael D. King NASA Goddard Space Flight Center

2. Surface Measurements of Sun/Sky Radiation (B. N. Holben, T. F. Eck, I. Slutsker et al. – NASA GSFC) AERONET  Automatic recording and transmitting sun/sky photometers  Data Base: Aerosol optical thickness, size distribution, phase function, optical properties, and precipitable water  Collaborative:NASA – instruments/sites and centralized calibration & database Non-NASA – instruments/sites Holben et al. (1998) 589 citations

3. Holben et al. (1998) AERONET-An Internationally Federated Network (B. N. Holben, T. F. Eck, O. Dubovik, A. Smirnov et al. – NASA GSFC)  Characterization of aerosol optical properties  Validation of satellite aerosol retrievals and model predictions  Near real-time acquisition; long term measurements – aeronet.gsfc.nasa.gov 589 citations

4. 256 citations Dubovik et al. (2002) Aerosol Climatology from AERONET ( O. Dubovik, B. N. Holben, T. F. Eck, A. Smirnov et al. - GSFC) Cooling Heating Hansen et al. (1997)

5. Difference between the Reflection Function and Surface Reflectance as a function of A g and  0 (Y. J. Kaufman and R. S. Fraser – NASA GSFC) Fraser and Kaufman (1985) 83 citations Retrieval of  a  Optical thickness increases with  a for dark surfaces  Optical thickness decreases with  a for bright surfaces  There is a critical A g where reflection function is insensitive to  a – depends on single scattering albedo

6. Aerosol Effects on Reflected Radiation over Land (M. D. King, Y. J. Kaufman, D. Tanr é, T. Nakajima – GSFC, Lille, Tokyo) Biomass burning Cuiabá, Brazil (August 25, 1995) 20 km 12 km R = 0.66 µm G = 0.55 µm B = 0.47 µm R = 1.6 µm G = 1.2 µm B = 2.1 µm King et al. (1999) 155 citations A g (2.1 µm) < 0.10 0.10 < A g (2.1 µm) < 0.15  0 = 36°

7.  Surface reflectance is high at 2.2 µm, moderate at 0.66 µm, and low at 0.49 µm  The aerosol effect on reflected solar radiation is small at 2.2 µm and large at 0.49 µm  MODIS operational algorithm over land assumes Surface Reflectance at Near-Infrared Wavelengths (Y. J. Kaufman, A. Wald, L. A. Remer et al. – NASA GSFC, U. Lille) A g (0.47 µm) = 0.5A g (0.66 µm) = 0.25A g (2.1 µm) Kaufman et al. (1997) 82 citations

8. Dynamic Aerosol Models (L. A. Remer, Y. J. Kaufman and B. N. Holben – NASA GSFC)  Accumulation mode particles (r < 0.3 µm) –mostly organic smoke particles or sulfates –depend on optical thickness  Aerosol-free troposphere plus stratospheric aerosol (0.3 µm < r < 0.8 µm)  Maritime salt particles in the mid-Atlantic region (0.8 µm < r < 2.5 µm)  Coarse particles (r > 2.5 µm) King et al. (1999) 155 citations

9. Chu et al. (1998) Remote Sensing of Aerosol over Land: SCAR-B (D. A. Chu, Y. J. Kaufman, L. A. Remer, B. N. Holben – NASA GSFC)  Spectral optical thickness derived from MAS  Intercomparison with ground-based AERONET  Dot-dashed lines are the retrieval error (  a = 0.05 ± 0.2  a ) anticipated using the MODIS aerosol optical thickness retrieval algorithm 24 citations Brazil (August-September 1995)

10. Spectral Variability of Urban Ecosystem (E. G. Moody, M. D. King, C. B. Schaaf, S. Platnick - GSFC, Boston U.) Moody et al. (2005) January - June

11. Tanr é et al. (1999) Remote Sensing of Aerosol over Ocean: TARFOX (D. Tanr é, L. A. Remer, Y. J. Kaufman et al. – U. Lille, NASA GSFC)  Spectral optical thickness derived from MAS using the MODIS at-launch algorithm  Aerosol optical thickness measured by the sunphotometer (AATS-6) aboard the University of Washington C-131A aircraft 38 citations Atlantic Ocean (July 1996)

12. Validation of Aerosol Retrievals over Ocean: TARFOX (D. Tanr é, L. A. Remer, Y. J. Kaufman et al. – U. Lille, NASA GSFC) Retrieval of  a  Spectral optical thickness derived from MAS using MODIS at- launch algorithm  Aerosol optical thickness measured by the sunphotometer (AATS-6) aboard the University of Washington C-131A aircraft King et al. (1999) 155 citations Tanr é et al. (1999) 38 citations

13. How well does Terra Represent the Daily Average? (Y. J. Kaufman, B. N. Holben, D. Tanré et al. - NASA GSFC, Univ. Lille) Kaufman et al. (2000) 32 citations AERONET analysis of  a  Scatter plot of the daily ratio of  a during Terra overpass time to the daily average – no systematic bias  No diurnal bias observed in Ångstr ö m exponent or column water vapor 0.0110.1100.001 1.5 0.5 1.0 0.5 Ratio of parameter for Terra/whole day Terra aerosol optical thickness (550 nm) 1.0 0.5 1.0 0.0 0.51.01.5

14. MODIS Aerosol Product (Y. J. Kaufman, L. A. Remer, D. Tanré - NASA GSFC, Univ. Lille)  Seven MODIS bands are utilized to derive aerosol properties –0.47, 0.55, 0.65, 0.86, 1.24, 1.64, and 2.13 µm –Ocean reflectance contrast between cloud-free atmosphere and ocean reflectance (dark) reflectance contrast between cloud-free atmosphere and ocean reflectance (dark) aerosol optical thickness (0.55-2.13 µm) aerosol optical thickness (0.55-2.13 µm) size distribution characteristics (fraction of aerosol optical thickness in the fine particle mode; effective radius) size distribution characteristics (fraction of aerosol optical thickness in the fine particle mode; effective radius) –Land dense dark vegetation and semi-arid regions determined where aerosol is most transparent (2.13 µm) dense dark vegetation and semi-arid regions determined where aerosol is most transparent (2.13 µm) contrast between Earth-atmosphere reflectance and that for dense dark vegetation surface (0.47 and 0.66 µm) contrast between Earth-atmosphere reflectance and that for dense dark vegetation surface (0.47 and 0.66 µm) aerosol optical thickness (0.47 and 0.66 µm) aerosol optical thickness (0.47 and 0.66 µm) fraction of aerosol optical thickness in the fine particle mode fraction of aerosol optical thickness in the fine particle mode Kaufman et al. (1997) 179 citations Tanr é et al. (1997) 190 citations

15. King et al. (2003) Terra/MODIS Aerosol Optical Thickness (Y. J. Kaufman, L. A. Remer, D. Tanré - NASA GSFC, Univ. Lille) True Color Composite (0.65, 0.56, 0.47) May 4, 2001 Aerosol Optical Thickness 0.40.80.00.20.61.0  a (0.56 µm) sunglint 97 citations

16. MODIS Monthly Mean Aerosol Optical Thickness (Y. J. Kaufman, D. Tanré, O. Boucher – NASA GSFC, U. Lille) Terra September 2000  Fine Mode –Industrial pollution US, Europe, China, India US, Europe, China, India –Smoke from biomass burning South America (Brazil, Bolivia) South America (Brazil, Bolivia) Southern Africa (Angola, Zambia) Southern Africa (Angola, Zambia) Australia, Borneo Australia, Borneo  Coarse Mode –Desert dust Sahara, Arabian Sea Sahara, Arabian Sea –Sea salt Southern ocean Southern ocean Kaufman et al. (2002) 195 citations

17. Terra/MODIS Global Aerosol Optical Properties (Y. J. Kaufman, L. A. Remer, and D. Tanré – NASA GSFC, U. Lille) Aerosol Optical Thickness August 30, 2001 Fine Mode vs Coarse Mode Aerosol 90 -90 Latitude 0 -45 45 Longitude 0 1.0 0.0 0.00.250.5 Aerosol Optical Thickness Fine Aerosol Fraction

18. Monthly Mean Aerosol Optical Properties (L. A. Remer, Y. J. Kaufman, and D. Tanr é et al. – GSFC, U. Lille) April 2005 (Collection 5) Aqua

19. Zonal Mean Aerosol Optical Thickness (L. A. Remer, Y. J. Kaufman, and D. Tanr é et al. – GSFC, U. Lille) April 2005 (Collection 5 vs Collection 4) Aqua

20. Zonal Mean Aerosol Fine Mode Fraction (L. A. Remer, Y. J. Kaufman, and D. Tanr é et al. – GSFC, U. Lille) April 2005 (Collection 5) Aqua

21. Effect of Smoke and Dust on Shallow Clouds (Y. J. Kaufman, I. Koren, L. A. Remer, D. Rosenfeld, Y. Rudich – GSFC, Hebrew U., Weizmann Inst.)  Aerosols Kaufman et al. (2005) 22 citations dust smoke pollution sea salt stratiform mixed convective Dust and sea salt  a (fine mode)/  a (total) < 0.50 Pollution and smoke  a (fine mode)/  a (total) > 0.50  Clouds Deep convective clouds p c < 300 hPa Mixed 640 hPa < p c < 300 hPa Low-level stratiform clouds p c > 640 hPa

22. Effect of Smoke and Dust on Shallow Clouds (Y. J. Kaufman, I. Koren, L. A. Remer, D. Rosenfeld, Y. Rudich – GSFC, Hebrew U., Weizmann Inst.) June - August 2002 Kaufman et al. (2005) Aerosol indirect effects  Increase in stratiform cloud cover with an increase in aerosol concentration  Lower concentration of aerosols associated with larger effective radius – Assessed the impact of meteorology and how it varies as opposed to aerosol properties  The aerosol forcing corresponding to the increase in cloud cover is ~ 6 W/m 2 in the June-Aug period over the Atlantic Ocean 22 citations 5°-30°N 20°S-5°N 5°-30°N 20°S-5°N

23. Publications on ‘MODIS’ AND ‘Aerosol’ (Y. J. Kaufman – NASA GSFC) Year Publications on ‘MODIS’ AND ‘Aerosol’

24.  Aerosol properties & their impact on climate pioneered by Yoram Kaufman –Atmospheric correction and calibration of satellite sensors –Dense dark vegetation and retrievals of aerosol optical properties over land –Visionary in establishing a multiyear spectral aerosol climatology, later supplanted by worldwide AERONET ground-based sun/sky radiometers –Aerosol effect on negating influence of CO 2 increases in Earth’s atmosphere –Satellite algorithms for aerosol optical thickness and fine mode fraction –Effects of aerosols on cloud suppression, optical properties, and precipitation  K ey publications that have had a long and influential role in aerosol science –Holben, B. N. et al., 1998: AERONET—A federated network. Remote Sens. Environ., 66, 1-16[591 citations] –Holben, B. N. et al., 1998: AERONET—A federated network. Remote Sens. Environ., 66, 1-16. [591 citations] –King, M. D., Y. J. Kaufman, W. P. Menzel, and D. Tanr é, 1992: Remote sensing of cloud, aerosol, and water vapor properties from MODIS. IEEE Trans. Geosci. Remote Sens., 30, 2-27[245 citations] –King, M. D., Y. J. Kaufman, W. P. Menzel, and D. Tanr é, 1992: Remote sensing of cloud, aerosol, and water vapor properties from MODIS. IEEE Trans. Geosci. Remote Sens., 30, 2-27. [245 citations] –Kaufman, Y. J., D. Tanr é, and O. Boucher, 1978: A satellite view of aerosols in the climate system. Nature, 419, 16971-16988[192 citations] –Kaufman, Y. J., D. Tanr é, and O. Boucher, 1978: A satellite view of aerosols in the climate system. Nature, 419, 16971-16988. [192 citations]  Published over 200 papers with over 7500 citations  412 different co-authors Summary and Conclusions

25. Dr. Yoram J. Kaufman Radiative transfer, aerosol remote sensing, aerosol-cloud interactions, colleague and friend