Search Results

You are looking at 1 - 2 of 2 items for :

  • Author or Editor: D. E. Cain x
  • Refine by Access: All Content x
Clear All Modify Search
A. S. Dennis, Alexander Koscielski, D. E. Cain, J. H. Hirsch, and P. L. Smith Jr.


Magnetic tape records for radar observations of 80 moving one-hour test cases in a three-way randomized (no-seed, salt, silver iodide) cloud seeding experiment have been analyzed in terms of echoing areas and radar-estimated rainfall amounts. Individual test cases ranged from non-precipitating cumulus up to moderate thunderstorms with echoing areas exceeding 100 km2 and rainfall estimated at 3000 kT in 1 h.Out of numerous predictor variables, cloud depth is found to be the best single predictor for both echoing area and radar-estimated rainfall. The echoing area and radar-estimated rainfall are very closely correlated. A cube-root transformation of the radar-estimated rainfall improves the correlation between cloud depth and the radar-estimated rainfall for the no-seed (control) sample to 0.91. For clouds of a given depth, both the echoing area and radar-estimated rainfall are larger in seeded than in unseeded cases. The differences between no-seed and salt cases are of marginal statistical significance, but the differences in echoing area and rainfall between no-seed and silver iodide cases are significant at the 1% level. The indicated effects, expressed as a percentage of the echoing area or radar-estimated rainfall in the no-seed cases, decrease with cloud depth.A comparison of no-seed and AgI cases with the aid of a one-dimensional steady-state cloud model shows that AgI seeding may have led to increases in maximum cloud height averaging 600 m.It is concluded that seeding affected the precipitation in the Cloud Catcher test cases through both the microphysical processes and the cloud dynamics.

Full access
A. S. Dennis, J. R. Miller Jr., D. E. Cain, and R. L. Schwaller


Rainfall data collected at 67 gages in a 2750 mi2 target area during a four-year randomized cloud seeding experiment in North Dakota have been stratified in a variety of ways and subjected to several kinds of statistical tests. Some stratifications related to cloud model predictions were possible for only the last two years when a rawinsonde station was operated as part of the project. Monte Carlo experiments simulating 500 reruns of the four-year experiment have been used to establish significance levels for the tests within each data stratification.

The analysis provides significant evidence that seeding convective clouds on a determinate set of days leads to 1) an increase in the frequency of rainfall events at the individual target gages, 2) an increase in the average rainfall recorded per rainfall event, and 3) an increase in total rainfall on the target. The set of days to which this evidence applies is those days with dynamic seedability; that is, days for which a cloud model predicted an increase in cloud top height under the influence of silver iodide seeding. Rainfall observations on days when the cloud model predicted no increase in cloud height show no significant differences between seed and no-seed days.

The possibility of bias has been checked by comparing the frequencies of wet and dry days and the averages of several meteorological variables for seed and no-seed days within each stratification, by cross-checking the stratifications, and by comparing rainfall on seed and no-seed days over an area of roughly 50,000 square miles surrounding the target area. There is no obvious bias to account for the significant differences between seed and no-seed days with dynamic seedability.

It is tentatively concluded that dynamic effects, including rainfall increases, were produced by light to moderate silver iodide seeding from below cloud base. The potential rainfall increase resulting from seeding below selected clouds on days with dynamic seedability is estimated at one inch per growing season.

Full access