Articles | Volume 10, issue 4
Research article
25 Apr 2017
Research article |  | 25 Apr 2017

Data-driven clustering of rain events: microphysics information derived from macro-scale observations

Mohamed Djallel Dilmi, Cécile Mallet, Laurent Barthes, and Aymeric Chazottes

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Cited articles

Akrour, N., Chazottes, A., Verrier, S., Mallet, C., and Barthes, L.: Simulation of yearly rainfall time series at microscale resolution with actual properties: Intermittency, scale invariance, and rainfall distribution, Water Resour. Res., 51, 7417–7435, 2015.
Atlas, D., Ulbrich, C. W., Marks, F. D., Amitai, E., and Williams, C. R.: Systematic variation of drop size and radar-rainfall relations, J. Geophys. Res.-Atmos., 104, 6155–6169, 1999.
Balme, M., Vischel, T., Lebel, T., Peugeot, C., and Galle, S.: Assessing the water balance in the Sahel: impact of small scale rainfall variability on runoff Part 1: rainfall variability analysis, J. Hydrol., 331, 336–348, 2006.
Bringi, V. N., Chandrasekar, V., Hubbert, J., Gorgucci, E., Randeu, W. L., and Schoenhuber, M.: Raindrop size distribution in different climatic regimes from disdrometer and dual-polarized radar analysis, J. Atmos. Sci., 60, 354–365, 2003.
Brown, B. G., Katz, R. W., and Murphy, A. H.: Statistical analysis of climatological data to characterize erosion potential: 1. Precipitation Events in Western Oregon. Oregon Agricultural Experiment Station Spec. Rep. No. 689, Oregon State University, 1983.
Short summary
The concept of a rain event is used to obtain a parsimonious characterisation of rain events using a minimal subset of variables at macrophysical scale. A classification in five classes is obtained in a unsupervised way from this subset. Relationships between these classes of microphysical parameters of precipitation are highlighted. There are several implications especially for remote sensing in the context of weather radar applications and quantitative precipitation estimation.