The Concept of “Normalized” Distribution to Describe Raindrop Spectra: A Tool for Cloud Physics and Cloud Remote Sensing

By Jacques Testud, S. Oury, R. Black, P. Amayenc, X. Dou. 2001

639 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/221b9be67e58c740fa2502e4c66f4053320de0bd

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Citations in the corpus

On the Parameterization of Evaporation of Raindrops as Simulated by a One-Dimensional Rainshaft Model (2008, background): “The variability of the shape parameter and its parameterization has been the focus of many investigations, especially within radar meteorology (Ulbrich 1983; Testud et al. 2001; and others).”
Estimation of Gamma Raindrop Size Distribution Parameters: Statistical Fluctuations and Estimation Errors (2009, methodology): “The term m̂ is then the parameter, which adjusts the least squares fit of log[ f m*(X)], defined in (2), to log [ f̂ *(Xi)] (Testud et al. 2001).”
Parametrization of ice‐particle size distributions for mid‐latitude stratiform cloud (2005, methodology): “Testud et al. (2001) went on to show that drop size distributions could be successfully scaled by normalizing with liquid-water content and mean volume radius without any knowledge of the underlying universal distribution.”
Evaluation of a New Polarimetrically Based Z–R Relation (2004, methodology): “Testud et al. (2001) further made the important generalization that the form of (4) is valid for any general DSD, not necessarily of the gamma form.”
Rainfall spatial variability observed by X-band weather radar and its implication for the accuracy of rainfall estimates (2009, methodology): “ZPHI operates in three steps: first, it corrects the observed reflectivity for along path attenuation; second it derives the N 0 parameter of the drop size distribution [15]; third, it retrieves the rain rate using the universal Z–R relationship parameterized by N 0 given by R 1⁄4 aðN 0Þ 1 Z ð1Þ”
A Microphysical Interpretation of Radar Reflectivity–Rain Rate Relationships (2004, background): “…1 ) the slope coefﬁcient, and the distribution shape factor (Clark 1974; Ulbrich 1983; Willis 1984; Chandrasekar and Bringi 1987; Russchen-berg 1993; Testud et al. 2001; Illingworth and Blackman 1 Strictly speaking N 0 is a concentration scaling parameter that becomes the intercept parameter only…”
The Impact of Raindrop Collisional Processes on the Polarimetric Radar Variables (2014, methodology): “The idea is to explore a range of rainfall rates and initial DSDs for comparison with the simulations rather than to simulate speciﬁc events.”
Comparison of Evaporation and Cold Pool Development between Single-Moment and Multimoment Bulk Microphysics Schemes in Idealized Simulations of Tornadic Thunderstorms (2010, methodology): “Note that for 500mMY2DA and 500mMY3, the physical meaning of N0 changes (see, e.g., Ulbrich 1983; Testud et al. 2001), due to the dependence on a, which is”
The Retrieval of Ice Water Content from Radar Reflectivity Factor and Temperature and Its Use in Evaluating a Mesoscale Model (2006, background): “…no significant temperature dependence of the concentration of particles larger than 100 m but found that the “normalized” intercept parameter of Testud et al. (2001) (a generalized version of N0 for nonexponential distributions) decreased by two orders of magnitude between 50° and 0°C. Ice…”
Snow Size Distribution Parameterization for Midlatitude and Tropical Ice Clouds (2007, methodology): “Many others have previously rescaled both raindrop distributions (e.g., Sekhon and Srivastava 1971; Willis 1984; SempereTorres et al. 1998; Illingworth and Blackman 1999; Testud et al. 2001; Lee et al. 2004) and ice size distributions (e.”