Skewness as measure of the invariance of instantaneous renormalized drop diameter distributions – Part 2: Orographic precipitation

Abstract

Abstract. Here we use the skewness parameter, and the procedure developed in the companion paper (Ignaccolo and De Michele, 2012), to investigate the variability of instantaneous renormalized spectra of rain drop diameter in presence of orographic precipitation. Disdrometer data, available at Bodega Bay and Cazadero, California, are analyzed either as a whole, or as divided (using the bright band echo) in precipitation intervals weakly and strongly influenced by orography, and compared to results obtained at Darwin, Australia. We find that also at Bodega Bay and Cazadero exists a most common distribution of the skewness values of instantaneous spectra of drop diameter, but peaked at values greater than 0.64, found at Darwin. No appreciable differences are found in the skewness distributions of precipitation weakly and strongly influenced by orography. However the renormalized drop diameter spectra of precipitation with strong orographic component have fatter right tail than precipitation with a weaker orographic component. The differences between orographic and non-orographic precipitation are investigated within the parametric space represented by number of drops, mean value and standard deviation of drop diameter. A filter is developed which is able to identify 1 min time intervals during which precipitation is mostly of orographic origin.

Skewness as measure of the invariance of instantaneous renormalized drop diameter distributions – Part 1: Convective vs. stratiform precipitation

“…E.g. in the companion paper (Ignaccolo and De Michele, 2012) we will discuss the properties of instantaneous renormalized spectra in presence of orography. Stratiform, convective and orographic are the three main kinds of precipitation.…”

“…A full disclosure of these effects, and the rationale for improving statistical accuracy by discarding outliers drop counts is presented in the Appendix of the companion paper (Ignaccolo and De Michele, 2012). Here, we set to zero the outliers drop counts before applying the renormalization procedure.…”

New perspectives on rainfall from a discrete view

“…Recent analyses of disdrometric time series allow us to point out that: The rainfall is a nonstationary phenomenon at short time scales, ∼10 s (Smith, ; Jameson and Kostinski, ; Ignaccolo et al ., ). A second‐order stationarity renormalization procedure, removing the local mean and standard deviation, permits the derivation of a ‘renormalized diameter’, which is a stationary (Ignaccolo et al ., ). The normalized drop diameter is characterized by a frequency distribution which is invariant in time , and above all is the same for convective and stratiform rainfall, the two principal types of rainfall (Ignaccolo and De Michele, ). The normalized drop diameter is characterized by a frequency distribution which is invariant in space (Ignaccolo and De Michele, ,). This last result is in agreement with Villermaux and Bossa ()’s conjecture that the drop diameter polydispersivity can be derived from the fragmentation of non‐interacting, isolated raindrops. The probability distribution of drought durations can be derived analytically by the probability distribution of the inter‐drop time interval (Ignaccolo and De Michele, ).…”

Skewness as measure of the invariance of instantaneous renormalized drop diameter distributions – Part 1: Convective vs. stratiform precipitation

“…Even if the drop counts following a gap constitute a small portion of total drop count inside a renormalization time interval, their effects amount to (1) larger values for the parameters µ I , σ I , and γ I (2) fatter left and right tail for the instantaneous probability densities function at ground p G,I (D) and p G,I (D R ) and for the probability p G (D R ) relative to the entire data set. A full disclosure of these effects, and the rationale for improving statistical accuracy by discarding outliers drop counts is presented in the Appendix of the companion paper (Ignaccolo and De Michele, 2012). Here, we set to zero the outliers drop counts before applying the renormalization procedure.…”