A Case for Exponential Cloud Fields?

I. Astin NERC Environmental Systems Science Centre, University of Reading, Whiteknights, Reading, United Kingdom

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B. G. Latter NERC Environmental Systems Science Centre, University of Reading, Whiteknights, Reading, United Kingdom

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Abstract

In a large number of satellite infrared images the proportion of randomly spaced intervals of length p satellite pixels (width, one pixel) that are registered as completely cloudy falls exponentially with increasing interval length. This is exactly to be expected for a one-dimensional exponential cloud field. Further, for rectangular intervals there is also an exponential falloff, as the size of the rectangle increases, in the proportion of completely cloudy intervals. However, the rate of falloff is dependent on the perimeter of the rectangle rather than its area. It is suggested that this can be explained if the length and width of clouds are both exponentially distributed and independent. If this is the case, then the mean horizontal aspect ratio for clouds, defined as the ratio of its semimajor to semiminor axis, is undefined (infinite) even though the ratio of semiminor to semimajor axis has mean 2 ln(2) (≈0.38).

* Current affiliation: Department of Meteorology, University of Reading, Whiteknights, Reading, United Kingdom.

Corresponding author address: Dr. Ivan Astin, NERC/ESSC, University of Reading, Whiteknights, Reading RG6 6AL, United Kingdom.

Abstract

In a large number of satellite infrared images the proportion of randomly spaced intervals of length p satellite pixels (width, one pixel) that are registered as completely cloudy falls exponentially with increasing interval length. This is exactly to be expected for a one-dimensional exponential cloud field. Further, for rectangular intervals there is also an exponential falloff, as the size of the rectangle increases, in the proportion of completely cloudy intervals. However, the rate of falloff is dependent on the perimeter of the rectangle rather than its area. It is suggested that this can be explained if the length and width of clouds are both exponentially distributed and independent. If this is the case, then the mean horizontal aspect ratio for clouds, defined as the ratio of its semimajor to semiminor axis, is undefined (infinite) even though the ratio of semiminor to semimajor axis has mean 2 ln(2) (≈0.38).

* Current affiliation: Department of Meteorology, University of Reading, Whiteknights, Reading, United Kingdom.

Corresponding author address: Dr. Ivan Astin, NERC/ESSC, University of Reading, Whiteknights, Reading RG6 6AL, United Kingdom.

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  • Aida, M., 1977: Scatter of solar radiation as a function of cloud dimensions and orientations. J. Quant. Spectros. Radiat. Transfer,17, 303–310.

  • Astin, I., 1997a: A survey of studies into errors in large-scale space–time averages of rainfall, cloud cover and sea surface processes as derived from low Earth orbit satellite instruments because of their incomplete temporal and spatial coverage. Surv. Geophys.,18, 385–403.

  • ——, 1997b: Sampling errors and bias in satellite-derived fractional cloud cover estimates from exponential and deterministic cloud fields as a consequence of instrument pixel size and number. J. Atmos. Oceanic Technol.,14, 1146–1156.

  • Breon, F.-M., 1992: Reflectance of broken cloud fields: Simulation and parameterization. J. Atmos. Sci.,49, 1221–1232.

  • Cahalan, R. F., and J. H. Joseph, 1989: Fractal statistics of cloud fields. Mon. Wea. Rev.,117, 261–272.

  • Charlock, T., F. Rose, S.-K. Yang, T. Alberta, and G. Smith, 1992: An observational study of the interaction of clouds, radiation and general circulation. Proc. IRS’92: Current Problems in Atmospheric Radiation, Tallinn, Estonia, 151–154.

  • Chatterjee, R. N., K. Ali, and P. Prakash, 1994: Fractal dimensions of convective clouds around Delhi. Indian J. Radio Space Phys.,23 (3), 189–192.

  • Diggle, P. J., J. E. Besag, and J. T. Gleaves, 1976: Statistical analysis of spatial point patterns by means of distance methods. Biometrics,32, 659–667.

  • Di Girolamo, L., and R. Davies, 1997: Cloud fraction errors caused by finite resolution measurements. J. Geophys. Res.,102 (D2), 1739–1756.

  • Ellingson, R. G., 1982: On the effects of cumulus dimensions on longwave iradiance and heating rate calculations. J. Atmos. Sci.,39, 886–896.

  • Illingworth, A. J., and I. J. McKendrick, 1994: Utility and Feasibility of a Cloud Profiling Radar—Report of the GEWEX Topical Workshop. International GEWEX Project Office, 48–57.

  • Joseph, J. H., 1985: The role of cloud field morphology in weather and climate studies. Isr. J. Earth Sci.,34 (2–3), 96–101.

  • Kite, A., 1987: The albedo of broken cloud fields. Quart. J. Roy. Meteor. Soc.,113, 517–531.

  • Kuo, K. S., R. M. Welch, R. C. Weger, M. M. Engelstad, and S. K. Sengupta, 1993: The 3-dimensional structure of cumulus clouds over the ocean. 1. Structural-analysis. J. Geophys. Res.,98 (D11), 20 685–20 711.

  • Lopez, R. E., 1977: The lognormal distribution and cumulus cloud populations. Mon. Wea. Rev.,105, 865–872.

  • Lovejoy, S., 1982: Area–perimeter relation for rain and cloudy areas. Science,216 (9), 185–187.

  • Luo, G., 1995: Simulations exploring the dependence of cloud-cover frequency distribution on cloud size and pixel resolution. J. Atmos. Oceanic Technol.,12, 712–720.

  • Mapes, B. E., 1993: Gregarious tropical convection. J. Atmos. Sci.,50, 2026–2037.

  • ——, and R. A. Houze Jr., 1993: Cloud clusters and superclusters over the oceanic warm pool. Mon. Wea. Rev.,121, 1398–1415.

  • Pielou, E. C., 1960: A single mechanism to account for regular, random and aggregated populations. J. Ecol.,48, 575–584.

  • Plank, V. G., 1969: The size distribution of cumulus clouds in representative Florida populations. J. Appl. Meteor.,8, 46–67.

  • Ramirez, J. A., and R. L. Bras, 1990: Clustered or regular cumulus cloud fields: The statistical character of observed and simulated cloud fields. J. Geophys. Res.,95 (D3), 2035–2045.

  • Randall, D. A., and G. J. Huffman, 1980: A stochastic model of cumulus clumping. J. Atmos. Sci.,37, 2068–2078.

  • Rossow, W. B., 1994: Utility and Feasibility of a Cloud Profiling Radar—Report of the GEWEX Topical Workshop. International GEWEX Project Office, 58–59.

  • ——, and R. A. Schiffer, 1991: ISCCP cloud data products. Bull. Amer. Meteor. Soc.,72, 2–20.

  • Shenk, W. E., and V. V. Salomonson, 1972: A simulation study exploring the effects of sensor spatial resolution on estimates of cloud cover from satellites. J. Appl. Meteor.,11, 214–220.

  • Su, B. J., and G. C. Pomraning, 1994: A stochastic description of a broken cloud field. J. Atmos. Sci.,51, 1969–1977.

  • Tessier, Y., S. Lovejoy, and D. Schertzer, 1993: Universal multifractals: Theory and observation from rain and clouds. J. Appl. Meteor.,32, 223–250.

  • Weger, R. C., J. Lee, T. Zhu, and R. M. Welch, 1992: Clustering, randomness and regularity in cloud fields: 1. Theoretical considerations. J. Geophys. Res.,97 (D18), 20 519–20 536.

  • Welch, R. M., and B. A. Wielicki, 1986: The stratocumulus nature of fog. J. Climate Appl. Meteor.,25, 101–111.

  • Wielicki, B. A., and R. M. Welch, 1986: Cumulus cloud field properties derived using Landsat digital images. J. Climate Appl. Meteor.,25, 261–276.

  • ——, and L. Parker, 1992: On the determination of cloud cover from satellite sensors: The effect of sensor spatial resolution. J. Geophys. Res.,97 (D12), 12 799–12 823.

  • Zhu, T., J. Lee, R. C. Weger, and R. M. Welch, 1992: Clustering randomness and regularity in cloud fields: 2. Cumulus cloud fields. J. Geophys. Res.,97 (D18), 20 537–20 558.

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