Spaceborne Inferences of Cloud Microstructure and Precipitation Processes: Synthesis, Insights, and Implications

  • Daniel Rosenfeld
  • William L. Woodley
Part of the Meteorological Monographs book series (METEOR)

Abstract

Spaceborne inferences of cloud microstructure and precipitation-forming processes with height have been used to investigate the effect of ingested aerosols on clouds and to integrate the findings with past cloud physics research. The inferences were made with a method that analyzes data from National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA AVHRR) and Tropical Rainfall Measuring Mission Visible and Infrared Scanner (TRMM VIRS) sensors to determine the effective radius of cloud particles with height. In addition, the TRMM Precipitation Radar (PR) made it possible to measure the rainfall simultaneously with the microphysical retrievals, which were validated by aircraft cloud physics measurements under a wide range of conditions. For example, the satellite inferences suggest that vigorous convective clouds over many portions of the globe remain supercooled to near −38°C, the point of homogeneous nucleation. These inferences were then validated in Texas and Argentina by in situ measurements using a cloud physics jet aircraft.

This unique satellite vantage point has documented enormous variability of cloud conditions in space and time and the strong susceptibility of cloud microstructure and precipitation to the ingested aerosols. This is in agreement with past cloud physics research. In particular, it has been documented that smoke and air pollution can suppress both water and ice precipitation-forming processes over large areas. Measurements in Thailand of convective clouds suggest that the suppression of coalescence can decrease areal rainfall by as much as a factor of 2. It would appear, therefore, that pollution has the potential to alter the global climate by suppressing rainfall and decreasing the net latent heating to the atmosphere and/or forcing its redistribution. In addition, it appears that intense lightning activity, as documented by the TRMM Lightning Imaging Sensor (LIS), is usually associated with microphysically highly “continental” clouds having large concentrations of ingested aerosols, great cloud-base concentrations of tiny droplets, and high cloud water contents. Conversely, strongly “maritime” clouds, having intense coalescence, early fallout of the hydrometeors, and glaciation at warm temperatures, show little lightning activity. By extension these results suggest that pollution can enhance lightning activity.

The satellite inferences suggest that the effect of pollution on clouds is greater and on a much larger scale than any that have been documented for deliberate cloud seeding. They also provide insights for cloud seeding programs. Having documented the great variability in space and time of cloud structure, it is likely that the results of many cloud seeding efforts have been mixed and inconclusive, because both suitable and unsuitable clouds have been seeded and grouped together for evaluation. This can be addressed in the future by partitioning the cases based on the microphysical structure of the cloud field at seeding and then looking for seeding effects within each partition.

This study is built on the scientific foundation laid by many past investigators and its results can be viewed as a synthesis of the new satellite methodology with their findings. Especially noteworthy in this regard is Dr. Joanne Simpson, who has spent much of her career studying and modeling cumulus clouds and specifying their crucial role in driving the hurricane and the global atmospheric circulation. She also was a pioneer in early cloud seeding research in which she emphasized cloud dynamics rather than just microphysics in her seeding hypotheses and in her development and use of numerical models. It is appropriate, therefore, that this paper is offered to acknowledge Dr. Joanne Simpson and her many colleagues who paved the way for this research effort.

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References

  1. Arking, A., and J. D. Childs, 1985: Retrieval of cloud cover parameters from multispectral satellite images. J. Climate Appl. Meteor., 24 (4), 322–333.CrossRefGoogle Scholar
  2. Bigg, E. K., 1953: The formation of atmospheric ice crystals by the freezing of droplets. Quart. J. Roy. Meteor. Soc., 79, 510–519.CrossRefGoogle Scholar
  3. Biswas, K. R., and A. S. Dennis, 1971: Formation of rain shower by salt seeding. J. Appl. Meteor., 10, 780–784.CrossRefGoogle Scholar
  4. Bowen, E. G., 1952: A new method of stimulating convective clouds to produce rain and hail. Quart. J. Roy. Meteor. Soc., 78, 37–45.Google Scholar
  5. Braham, R. R., Jr., 1964: What is the role of ice in summer rain showers? J. Atmos. Sci., 21, 640–645.CrossRefGoogle Scholar
  6. Braham, R. R., 1981: Summary of urban effects on clouds and rain. METROMEX: A Review and Summary, Meteor. Monogr., No. 40, Amer. Meteor. Soc., 141–152.Google Scholar
  7. Cerveny, R. S., and R. C. Balling Jr., 1998: Weekly cycles of air pollutants, precipitation and tropical storm intensity in the coastal NW Atlantic region (Letter to Nature). Nature, 394, 561–563.CrossRefGoogle Scholar
  8. Coakley, J. A., R. L. Bernstein, and P. R. Durkee, 1987: Effects of ship-stack effluents on cloud reflectivity. Science, 237, 1020–1022.CrossRefGoogle Scholar
  9. Cooper, W. A., R. T. Bruintjes, and G. K. Mather, 1997: Calculations pertaining to hygroscopic seeding with flares. J. Appl. Meteor., 36, 1449–1469.CrossRefGoogle Scholar
  10. Cotton, W. R., 1982: Modification of precipitation from warm clouds—A review. Bull. Amer. Meteor. Soc., 63, 146–160.CrossRefGoogle Scholar
  11. Eagen, R. C., P. V. Hobbs, and L. F. Radke, 1974: Particle emissions from a large Kraft paper mill and their effects on the micro- structure of warm clouds. J. Appl. Meteor., 13, 535–552.CrossRefGoogle Scholar
  12. Gatz, D. F., 1979: Investigation of pollutant source strength rainfall relationships at St. Louis. J. Appl. Meteor., 18, 1245–1251.CrossRefGoogle Scholar
  13. Gerber, H., 1996: Microphysics of marine stratocumulus clouds with two drizzle modes. J. Atmos. Sci., 53, 1649–1662.CrossRefGoogle Scholar
  14. Gribbin, J., 1995: Rain moves north in the global greenhouse. New Sci., 18.Google Scholar
  15. Gunn, R., and B. B. Phillips, 1957: An experimental investigation of the effect of air pollution on the initiation of rain. J. Meteor., 14, 272–280.CrossRefGoogle Scholar
  16. Houghton, J. T., L. G. Meira Filho, J. Bruce, Hoesung Lee, B. A. Callander, E. Haites, N. Harris, and K. Maskell, 1994: Climate Change 1994—Radiative forcing of climate change and an Evaluation of the IPCCIS92 Emission Scenarios. Reports of Working Groups I and II of the Intergovernmental Panel on Climate Change.Cambridge University Press, 339 pp.Google Scholar
  17. Johnson, D. B., 1982: Role of giant and ultragiant aerosol particles in warm rain initiation. J. Atmos. Sci., 39, 448–460.CrossRefGoogle Scholar
  18. Johnson, D. B., 1987: On the relative efficiency of coalescence and riming. J. Atmos. Sci., 44, 1671–1680.CrossRefGoogle Scholar
  19. Kaufman, Y. J., and R. S. Fraser, 1997: The effect of smoke particles on clouds and climate forcing. Science, 277, 1636–1638.CrossRefGoogle Scholar
  20. Lensky, I. M., and D. Rosenfeld, 1997: Estimation of precipitation area and rain intensity based on the microphisical properties retrieved from NOAA AVHRR data. J. Appl. Meteor., 36, 234–242.Google Scholar
  21. Mather, G. K., D. E. Terblanche, F. E. Steffens, and L. Fletcher, 1997: Results of the South African cloud seeding experiments using hygroscopic flares. J. Appl. Meteor., 36, 1433–1447.CrossRefGoogle Scholar
  22. McCollum, J. A., A. Gruber, and M. B. Ba, 2000: Discrepancy between gauges and satellite estimates of rainfall in equatorial Africa. J. Appl. Meteor., 39, 666–679.CrossRefGoogle Scholar
  23. Nakajima, T., and M. D. King, 1990: Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. Part I: Theory. J. Atmos. Sci., 47, 1878–1893.CrossRefGoogle Scholar
  24. Orville, H. D., 1996: A review of cloud modeling in weather modification. Bull. Amer. Meteor. Soc., 77, 1535–1555.CrossRefGoogle Scholar
  25. Pinsky, M. B., A. P. Khain, D. Rosenfeld, and A. Pokrovsky, 1998: Comparison of collision velocity differences of drops and grau- pel particles in a very turbulent cloud. Atmos. Res., 49, 99–113.CrossRefGoogle Scholar
  26. Radke, L. F., J. A. Coakley, and M. D. King, 1989: Direct and remote sensing observations of the effects of ships on clouds. Science, 246, 1146–1149.CrossRefGoogle Scholar
  27. Reisin, T., S. Tzivion, and Z. Levin, 1996: Seeding convective clouds with ice nuclei or hygroscopic particles: A numerical study using a model with detailed microphysics. J. Appl. Meteor., 35, 1416–1434.CrossRefGoogle Scholar
  28. Rosenfeld, D., 1999: TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall. Geophys. Res. Lett., 26, 3105.CrossRefGoogle Scholar
  29. Rosenfeld, D., 2000: Suppression of rain and snow by urban and industrial air pollution. Science, 287, 1793–1796.CrossRefGoogle Scholar
  30. Rosenfeld, D., and W. L. Woodley, 1993: Effects of cloud seeding in west Texas: Additional results and new insights. J. Appl. Meteor., 32, 1848–1866.CrossRefGoogle Scholar
  31. Rosenfeld, D., and G. Gutman, 1994: Retrieving microphysical properties near the tops of potential rain clouds by multispectral analysis of AVHRR data. J. Atmos. Res., 34, 259–283.CrossRefGoogle Scholar
  32. Rosenfeld, D., and M. I. Lensky, 1998: Space-borne based insights into precipitation formation processes in continental and maritime convective clouds. Bull. Amer. Meteor. Soc., 79, 2457–2476.CrossRefGoogle Scholar
  33. Rosenfeld, D., and W. L. Woodley, 2000: Convective clouds with sustained highly supercooled liquid water down to -37.5°C. Nature, 405, 440–442.CrossRefGoogle Scholar
  34. Rosenfeld, D., D. B. Wolff, and D. Atlas, 1993: General probability-matched relations between radar reflectivity and rain rate. J. Appl. Meteor., 32, 50–72.CrossRefGoogle Scholar
  35. Rosenfeld, D., W. L. Woodley, and T. Krauss, 2001: Satellite Observations of the microstructure of natural and seeded severe hailstorms in Argentina and Alberta. Preprints, 15th Conf. on Planned and Inadvertent Weather Modification, Albuquerque, NM, Amer. Meteor. Soc., 68–74.Google Scholar
  36. Schickel, K. P., H. E. Hoffmann, and K. T. Kriebel, 1994: Identification of icing water clouds by NOAA AVHRR satellite data. Atmos. Res., 34 (1–4), 177–183.CrossRefGoogle Scholar
  37. Simpson, J., 1980: Downdraft as linkages in dynamic cumulus seeding effects. J. Appl. Meteor., 19, 477–487.CrossRefGoogle Scholar
  38. Simpson, J., and W. L. Woodley, 1971: Seeding cumulus in Florida: New 1970 results. Science, 173, 117–126.CrossRefGoogle Scholar
  39. Simpson, J., G. W. Brier, and R. H. Simpson, 1967: Stormfury cumulus seeding experiment 1965: Statistical analysis and main results. J. Atmos. Sci., 24, 508–521.CrossRefGoogle Scholar
  40. Squires, P., 1958: The microstructure and colloidal stability of warm clouds. Tellus, 10, 256–271.CrossRefGoogle Scholar
  41. Twomey, S., R. Gall, and M. Leuthold, 1987: Pollution and cloud reflectance. Bound.-Layer Meteor., 41, 335–348.CrossRefGoogle Scholar
  42. Witt, G., and J. Malkus, 1959: The evolution of a convective element: A numerical calculation. The Atmosphere and the Sea in Motion, R. Bolin, Ed., Oxford University Press, 425–439.Google Scholar
  43. Woodley, W., and A. Herndon, 1970: A raingauge evaluation of the Miami reflectivity-rainfall rate relation. J. Appl. Meteor., 9,258–264.Google Scholar
  44. Woodley, W., J. Jordan, J. Simpson, R. Biondini, J. A. Flueck, and A. Barnston, 1982: Rainfall results of the Florida Area Cumulus Experiment. J. Appl. Meteor., 21, 139–164.CrossRefGoogle Scholar
  45. Woodley, W., A. G. Barnston, J. A. Flueck, and R. Biondini, 1983: The Florida Area Cumulus Experiment’s second phase (FACE-2). Part II: Replicated and confirmatory analyses. J. Appl. Meteor., 22, 1529–1540.CrossRefGoogle Scholar
  46. Woodley, W., D. Rosenfeld, and A. Strautins, 2000: Identification of a seeding signature in Texas using multi-spectral satellite imagery. J. Wea. Mod., 32, 37–51.Google Scholar
  47. Zipser, J. E., and K. R. Lutz, 1994: The vertical profile of radar reflectivity of convective cells: A strong indicator of storm intensity and lightning probability? Mon. Wea. Rev., 122, 1751–1759.Google Scholar

Copyright information

© American Meteorological Society 2003

Authors and Affiliations

  • Daniel Rosenfeld
    • 1
  • William L. Woodley
    • 2
  1. 1.Hebrew University of JerusalemJerusalemIsrael
  2. 2.Woodley Weather ConsultantsLittletonUSA

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