The Shape of Averaged Drop Size Distributions

Sauvageot, Henri; Lacaux, Jean‐Pierre

doi:10.1175/1520-0469(1995)052<1070:tsoads>2.0.co;2

Cited by 155 publications

(105 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The underestimation is seen clearly in comparisons between the DSDs measured by JWD and by 2D video disdrometer (Williams et al, 2000;Tokay et al, 2001). On the other hand, Sauvageot and Lacaux (1995) and Atlas and Ulbrich (2000) argued that the observed fewer small drops during heavy rain in the Tropics is a real atmospheric phenomenon and attributed it to drop sorting and evaporation. Notwithstanding these arguments, the acoustic noise was measured in both the monsoon seasons, when all the known acoustic noise sources were turned on (e.g.…”

Section: Discussionmentioning

confidence: 99%

“…It is important to understand whether the observed DSD variability is random or associated with any complex microphysical process. Several earlier studies have shown that the DSDs are not random, but can be reproduced under homogeneous environmental conditions (Jameson and Kostinski, 2001), and have investigated the variability of DSD and statistics of DSD parameters as a function of R (Sauvageot and Lacaux, 1995;Tokay et al, 2001;Nzeukou et al, 2004;Kozu et al, 2006). Therefore, the DSDs stratified based on R should look similar, unless they are fundamentally different.…”

Section: Discussionmentioning

confidence: 99%

“…This difference seems to be weakening continuously with increase of R and almost negligible in the last two rain rate classes (R > 32 mm hr −1 ). It is partly due to the problems associated with JWD in heavy rain (Tokay et al, 2001) and partly geophysical (Sauvageot and Lacaux, 1995) and will be discussed in detail in the next section. The contribution of number of drops in the NE monsoon season to the total number of drops (NE+SW) is ∼60-90% in the smaller drop regime during weak to moderate rain.…”

Section: Methodsmentioning

confidence: 97%

See 2 more Smart Citations

Differences in raindrop size distribution from southwest monsoon to northeast monsoon at Gadanki

Rao

Radhakrishna

Nakamura

et al. 2009

Quart J Royal Meteoro Soc

View full text Add to dashboard Cite

Characteristics of raindrop size distribution (DSD) are studied during the southwest (SW) and northeast (NE) monsoon seasons using 4 1/2 years of DSD measurements made at Gadanki (13.5 • N, 79.2 • E) by an impact-type disdrometer. The observed DSD is found to be distinctly different in the NE monsoon from that of the SW monsoon. The stratified DSD (based on rain rate) shows more small drops and fewer bigger drops in the NE monsoon than in the SW monsoon, particularly in the low rain rate regime. This feature is not an anomalous one, rather observed consistently in all the years. The diurnal variation of DSD (in terms of mass-weighted mean diameter, D m ) plots in both monsoons show large values of D m in the evening hours. Several possible reasons, from instrumental problems to geophysical mechanisms, for the observed DSD differences are examined. The wind field and the range of D m values indicate that the DSDs in the SW and NE monsoons are continental and oceanic in nature, respectively. Further, high temperature and intense convective activity (vigorous updraughts) in the SW monsoon modify the DSD through evaporation, drop sorting, and collision-coalescence processes.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 97%

See 1 more Smart Citation

Differences in raindrop size distribution from southwest monsoon to northeast monsoon at Gadanki

Rao

Radhakrishna

Nakamura

et al. 2009

Quart J Royal Meteoro Soc

View full text Add to dashboard Cite

show abstract

“…From comparisons with measurements, we know that rain drop spectra are well modeled by Γ-and Log-Normal Distributions [32][33][34][35]. While the Γ-Distribution in one-or two-parameter exponential form (as suggested by Marshall and Palmer [9] or Waldvogel [10]) is suitable for describing rain drop spectra averaged over a long time, the three-parameter Γ-and also the Log-Normal Distribution are both able to model spectra from a short rain event [32].…”

Section: Choices For the Distribution Functionmentioning

confidence: 99%

A Comparative Study of B-, Γ- and Log-Normal Distributions in a Three-Moment Parameterization for Drop Sedimentation

Ziemer

Wacker

2014

Atmosphere

View full text Add to dashboard Cite

This paper examines different distribution functions used in a three-moment parameterization scheme with regard to their influence on the implementation and the results of the parameterization scheme. In parameterizations with moment methods, the prognostic variables are interpreted as statistical moments of a drop size distribution, for which a functional form has to be assumed. In cloud microphysics, parameterizations are frequently based on gamma-and log-normal distributions, while for particle-laden flows in engineering, the beta-distribution is sometimes used. In this study, the three-moment schemes with beta-, gamma-and log-normal distributions are tested in a 1D framework for drop sedimentation, and their results are compared with those of a spectral reference model. The gamma-distribution performs best. The results of the parameterization with the beta-and the log-normal distribution have less similarity to the reference solution, particularly with regard to number density and rain rate. Theoretical considerations reveal that (depending on the type of the distribution function) only selected combinations of moments can be predicted together. Among these is the important combination of "number density, liquid water content, radar reflectivity" for all three distributions. Advection or source/sink terms can only be calculated under certain conditions on the moment values (positivity of the Hankel-Hadamard determinant). These are derived from mathematical theory ("moment problem") and are more restrictive for three-moment than for two-moment schemes.Atmosphere 2014, 5 485

show abstract

“…Aux latitudes tropicales, où la hauteur de chute est importante puisque le niveau de fusion des précipitations est habituellement à environ 5 000 m d'altitude, on observe sur les pluies intenses un déficit des petites gouttes, par rapport à l'exponentielle décrois-sante, qui s'accentue avec R. Par contre, pour les gouttes de taille supérieure au mode de la distribution, N(D) est représentée, en coordonnées logarithmiques, par une droite de pente constante pour R > 20 mm.h -1 (Sauvageot et Lacaux, 1995). La figure 4 met en évidence cette propriété sur des distributions moyennées par classe d'intensité et calculées à partir des mesures de N(D) obtenues avec un disdromètre de Joss et Waldvogel (1967), qui est un capteur électromécanique permettant une mesure ponctuelle, in situ, de la DSD.…”

Section: Réflectivité Et Atténuation Par Les Nuagesunclassified

Le radar polarimétrique, une nouvelle approche pour l'observation des champs de précipitations

Sauvageot¹

2000

Météorologie

Self Cite

View full text Add to dashboard Cite

Pour l'observation des champs de précipitations instantanés, on utilise des réseaux de radars. Cependant, les algorithmes de restitution des intensités de précipitations à partir de la réflectivité radar ne permettent pas d'obtenir une précision satisfaisante. Parmi les diverses voies explorées ou proposées pour améliorer la qualité des résultats, les méthodes polarimé-triques sont les plus prometteuses. Dans cet article, après avoir rappelé pourquoi et comment les radars « voient » les précipitations, les principaux concepts qui sous-tendent les méthodes polarimétriques sont présentés et les solutions proposées sont discutées de façon comparative. Les premiers algorithmes polarimétriques n'ont pas apporté d'amélioration décisive, en raison de leur sensibilité aux erreurs dues à l'atténuation et à l'étalonnage. Les algorithmes de polarimétrie différentielle récemment proposés semblent capables de surmonter la plupart des problèmes puisqu'ils ne sont pas, ou peu, affectés par l'atténuation, par les variations de la distribution de taille des gouttes, par les occultations de faisceau, par les échos de sol, par la grêle. Ils peuvent être utilisés pour détecter les propagations anormales et ils sont indépendants de l'étalonnage du radar. Cependant, leur validation en conditions opérationnelles reste à faire. Polarimetric radar: a new approach for rain-field observationA meteorological radar network is indispensable for instantaneous precipitation field observation. However, the usual rain-rate retrieval algorithms do not have sufficient accuracy. Polarimetric methods are the most promising of the various ways investigated, or proposed, to increase the effectiveness of radar estimation of rainfall. This paper first reminds why and how radars "see" precipitation, then presents the main concepts underlying the polarimetric methods and finally compares the solutions proposed. The early polarimetric algorithms did not bring any decisive improvement because of their sensitivity to attenuation and calibration error. The differential polarimetric algorithms recently proposed seem able to overcome most of the problems since they are not, or are only weakly, affected by attenuation, variations in drop-size distribution, beam occultation, ground clutter or hail. They also enable the detection of anomalous propagation and are independent of the radar calibration. However polarimetric methods have yet to be validated in operational conditions.

show abstract

The Shape of Averaged Drop Size Distributions

Cited by 155 publications

References 0 publications

Differences in raindrop size distribution from southwest monsoon to northeast monsoon at Gadanki

Differences in raindrop size distribution from southwest monsoon to northeast monsoon at Gadanki

A Comparative Study of B-, Γ- and Log-Normal Distributions in a Three-Moment Parameterization for Drop Sedimentation

Le radar polarimétrique, une nouvelle approche pour l'observation des champs de précipitations

Contact Info

Product

Resources

About