Editorial Type:
Article
Article Type:
Research Article

Stochastic Simulation of Intermittent DSD Fields in Time

Marc Schleiss Laboratoire de Télédétection Environnementale, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

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Joel Jaffrain Laboratoire de Télédétection Environnementale, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

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Alexis Berne Laboratoire de Télédétection Environnementale, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

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Print Publication:
01 Apr 2012
DOI:
https://doi.org/10.1175/JHM-D-11-018.1
Page(s):
621–637
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Abstract

A method for the stochastic simulation of (rain)drop size distributions (DSDs) in space and time using geostatistics is presented. At each pixel, the raindrop size distribution is described by a Gamma distribution with two or three stochastic parameters. The presence or absence of rainfall is modeled using an indicator field. Separable space–time variograms are used to estimate and reproduce the spatial and temporal structures of all these parameters. A simple and user-oriented procedure for the parameterization of the simulator is proposed. The only data required are DSD time series and radar rain-rate (or reflectivity) measurements. The proposed simulation method is illustrated for both frontal and convective precipitation using real data collected in the vicinity of Lausanne, Switzerland. The spatial and temporal structures of the simulated fields are evaluated and validated using DSD measurements from eight independent disdrometers.

Corresponding author address: Alexis Berne, GR C2 564, Station 2, 1015 Lausanne, Switzerland. E-mail: alexis.berne@epfl.ch

Abstract

A method for the stochastic simulation of (rain)drop size distributions (DSDs) in space and time using geostatistics is presented. At each pixel, the raindrop size distribution is described by a Gamma distribution with two or three stochastic parameters. The presence or absence of rainfall is modeled using an indicator field. Separable space–time variograms are used to estimate and reproduce the spatial and temporal structures of all these parameters. A simple and user-oriented procedure for the parameterization of the simulator is proposed. The only data required are DSD time series and radar rain-rate (or reflectivity) measurements. The proposed simulation method is illustrated for both frontal and convective precipitation using real data collected in the vicinity of Lausanne, Switzerland. The spatial and temporal structures of the simulated fields are evaluated and validated using DSD measurements from eight independent disdrometers.

Corresponding author address: Alexis Berne, GR C2 564, Station 2, 1015 Lausanne, Switzerland. E-mail: alexis.berne@epfl.ch
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Journal of Hydrometeorology

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