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Gupta and Waymire (1993) categorically rejected the concept of universality in cascade processes as 'untenable' but failed to discuss the reasons why this is an erroneous proposition. This unique error argument is proven to be irrelevant by presenting universality and universal multifractals using an innovative approach. This multifractal approach results in a desirable model for analyzing and simulating highly nonlinear meteorological fields across a broad range of scales and intensities.

A series of multifractal analysis techniques applied to network density over a range of 200-20,000 km shows that the density of stations can be characterized by multifractal measures and the limits and types of multiscale network. There is a change in the scaling behavior at very low and high densities, which is produced by a universal multifractal process used to simulate the effects of the finite number of stations on a network with same statistical properties. A large number of geophysical fields exhibit multiscaling properties over various ranges, and the bias introduced by the network clustering can be removed by new multifractal objective analysis procedures.

The double trace moment analysis technique is presented as a new technique for the estimation of universal multifractal parameters. The new technique, together with conventional energy spectra, is used to analyze satellite cloud radiances, and to estimate the fundamental universal multifractal exponents characterizing the fields. These exponents, together with appropriate space-time transformations, facilitate dynamical multifractal simulations. Finally, these simulations facilitate our understanding of atmospheric dynamics.

A codimension multifractal methodology was used to analyze and to model scalar concentration fluctuations within sulfur hexafluoride tracer gas plumes from a line source in atmospheric surface-layer flows. Correspondence was exhibited between the double trace moments parameters [Alpha] and [C.sub.1] of the codimension methodology and the experimentally measured plume concentration characteristics of peak-to-mean ratio and concentration fluctuation intensity. Data series were generated using an extremal Levy, stochastic multifractal model, with the experimental [Alpha] and [C.sub.1] as inputs. Uncertainties in experimentally determined plume characteristic values overlapped the uncertainties in model-simulated values. The utility of the procedure includes 1) characterizing the state of scalar turbulent mixing, 2) helping to evaluate and to model hazardous plume concentrations, and 3) being able to estimate the probability of realizing extreme events at timescales of observation beyond or at magnitudes in excess of those present in the actual observations.