Scaling analysis of the variability of the rain drop size distribution at small scale

Autor: Marc Schleiss, Joël Jaffrain, Alexis Berne
Předmět:
Popis: Like precipitation, the raindrop size distribution (DSD) is strongly variable in space and time. Understanding this variability is important for quantifying and minimizing some of the uncertainties in radar measurements and their interpretation in terms of rain rate. At the typical operational radar pixel scale (i.e., 1 × 1 km2), the variability of the DSD is not well documented and understood. A network of 16 identical disdrometers deployed over a 1 × 1 km2 area provides an adequate data set to investigate this small-scale variability of the DSD. The single-moment and double-moment DSD scaling approaches are used to analyze the DSD variability for a set of 36 rain events of various types. At fine temporal resolutions, neither the single-moment nor the double-moment normalization capture all the DSD variability, and the scaled DSDs appear different at the point and at the pixel scales. The double-moment normalization can however be used to obtain reliable estimates of the DSD moments at the pixel scale from point measurements, providing a way to upscale DSD moments. At coarser temporal resolutions, the spatial variability within the pixel becomes negligible, and the scaled DSDs are similar at the two spatial scales.
Databáze: OpenAIRE