Using Radar Data to Evaluate the Variability of Mass-Dimension Parameters Within Ice Clouds

Mass-dimension (m-D) relationships used to derive bulk microphysical properties such as total water content (TWC) and radar reflectivity factor (Z) are used in both numerical models and remote sensing retrievals. The most common way of estimating a-b coefficients used in m=aD^b relationships is to minimize the difference between the TWC or Z derived from number distribution functions and that directly measured by a bulk water probe or radar. These a and b values, however, can vary significantly based on meteorological conditions, particle habit, definition of particle maximum dimension, probes used to obtain the data, or even the techniques used to process the cloud probe data.

Microphysical data collected by two-dimensional optical array probes (OAPs) installed on the University of North Dakota Citation aircraft during the Midlatitude Continental Convective Clouds Experiment (MC3E) and the Olympic Mountain Experiment (OLYMPEX) are used here in conjunction with TWC data from the Nevzorov probe and ground-based radar data at S-band to test a novel approach that determines m-D relationships for a variety of environments. A surface of equally realizable a and b coefficients in (a,b) phase space is determined using a technique that minimizes the chi-squared difference between TWC or Z derived from the OAPs and that directly measured by a TWC probe or radar, accepting as valid all coefficients within a specified tolerance as equally realizable solutions to the m=aD^b relationship. The surfaces of solutions for different cases are compared to establish how environmental conditions and spatial and temporal variability within clouds controls the a-b coefficients. It is shown that using fixed a-b coefficients in selected numerical modeling and remote retrieval schemes cannot adequately represent the ensemble-retrieved particle mass-dimension variability of observed cloud conditions.