The Normalized Intercept Parameter N0* to describe the variability of the particle size distribution of hydrometeors, and to parameterize the rain and cloud relations

A rain drop spectra may be characterized by three elements mutually independent: the liquid water content LWC, the mean volume diameter Dm and the "intrinsic shape" of the drop size distribution (DSD). The "intrinsic shape" (independent of LWC and Dm) is defined as that of the spectrum after normalizing the diameters by Dm and the concentrations by N0* proportional to LWC/Dm**4. Parameter N0* is also defined as the intercept parameter of the exponential DSD with same LWC and Dm. With spectra of ice particles the same normalization concept applies considering the "melted diameter" of each particle. This normalization has been extensively applied to various microphysical data bases for rain an clouds.

For rain, the TOGA-COARE airborne microphysical data, and various sites of disdrometer data in the tropics and at mid latitude are investigated. It is shown that the intrinsic shape of the DSD is remarkably stable, while N0* is extremely variable: its variability covers two decades, nevertheless centered on Marshall and Palmer's. In addition N0* shows a distinct behavior according rain is stratiform and convective rain.

For ice clouds the airborne microphysical data investigated are CEPEX, CLARE 98, and CARL, 99. Similar features are found: the intrinsic shape of the particle size distribution (PSD) is quite stable while N0* is extremely variable (over 4 to 5 decades) for clouds. It seems that when aggregation occurs N0* decreases downward to reach values similar to Marshall-Palmer's when approaching the 0° isotherm.

Because the shape of the DSD (or PSD) is quite stable, N0* suffices to describe its variability. It is shown that "normalized" cloud and rain relations may be established that are parameterized by N0*. These relationships are "universal" in the sense that they apply to any situation, whatever be the type of rain or climate. Thus any remote sensing technique and associated algorithm (dual polarization radar, cloud radar and lidar combination) able to retrieve N0* will be able to perform cloud parameter retrieval not subject to DSD or PSD variability.