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Mr. W. N. SHAW

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W. N. SHAW

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W. N. SHAW

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W. N. SHAW

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W. N. SHAW

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W. N. SHAW

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R. E. Stewart
,
R. W. Shaw
, and
G. A. Isaac

The field phase of the Canadian Atlantic Storms Program (CASP) was conducted from 15 January to 15 March 1986. The principal objective of the meteorological component of the program was to begin the process of improving the understanding and prediction of mesoscale features within East Coast storms as well as the storms themselves. The project area, instrumentation platforms used, real-time forecasts, and the linkage of the program to the American Genesis of Atlantic Lows Experiment (GALE) are discussed. Sixteen storms were sampled during the field phase. A number of mesoscale features such as fronts, precipitation bands, heavy snow, and freezing precipitation were sampled. These features and the storms themselves will be studied over the next several years. It is anticipated that scientific progress in understanding the nature of these winter systems and experience gained with new forecasting tools will lead to improved weather forecasts.

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W. N. SHAW
and
W. H. DINES

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K. K. Chandrakar
,
W. Cantrell
, and
R. A. Shaw

Abstract

Cloud droplet relative dispersion, defined as the standard deviation over the mean cloud droplet size, is of central importance in determining and understanding aerosol indirect effects. In recent work, it was found that cloud droplet size distributions become broader as a result of supersaturation variability and that the sensitivity of this effect is inversely related to cloud droplet number density. The subject is investigated in further detail using an extensive dataset from a laboratory cloud chamber capable of producing steady-state turbulence. An extended stochastic theory is found to successfully describe properties of the droplet size distribution, including an analytical expression for the relative dispersion. The latter is found to depend on the cloud droplet removal time, which in turn increases with the cloud droplet number density. The results show that relative dispersion decreases monotonically with increasing droplet number density, consistent with some recent atmospheric observations. Experiments spanning fast to slow microphysics regimes are reported. The observed dispersion is used to estimate time scales for autoconversion, demonstrating the important role of the turbulence-induced broadening effect on precipitation development. An initial effort is made to extend the stochastic theory to an atmospheric context with a steady updraft, for which autoconversion time is the controlling factor for droplet lifetime. As in the cloud chamber, relative dispersion is found to increase with decreasing cloud droplet number density.

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N. Desai
,
K. K. Chandrakar
,
K. Chang
,
W. Cantrell
, and
R. A. Shaw

Abstract

Diffusional growth of droplets by stochastic condensation and a resulting broadening of the size distribution has been considered as a mechanism for bridging the cloud droplet growth gap between condensation and collision–coalescence. Recent studies have shown that supersaturation fluctuations can lead to a broadening of the droplet size distribution at the condensational stage of droplet growth. However, most studies using stochastic models assume the phase relaxation time of a cloud parcel to be constant. In this paper, two questions are asked: how variability in droplet number concentration and radius influence the phase relaxation time and what effect it has on the droplet size distributions. To answer these questions, steady-state cloud conditions are created in the laboratory and digital inline holography is used to directly observe the variations in local number concentration and droplet size distribution and, thereby, the integral radius. Stochastic equations are also extended to account for fluctuations in integral radius and obtain new terms that are compared with the laboratory observations. It is found that the variability in integral radius is primarily driven by variations in the droplet number concentration and not the droplet radius. This variability does not contribute significantly to the mean droplet growth rate but does contribute significantly to the rate of increase of the size distribution width.

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