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Meccanica

, Volume 31, Issue 1, pp 27–42 | Cite as

Identification of rain cells from radar and stochastic modelling of space-time rainfall

  • Daniele Veneziano
  • Paolo Villani
Article

Abstract

We discuss two problems related to the utilization of weather radar: the automated identification of rain cells and the extension of cluster models to include the random variability of space-time rainfall within and between cells. The need for such extension emerges from visual inspection and formal analysis of radar reflectivity images. The algorithm proposed for the identification of cells is based on statistical techniques for the estimation of probability density mixtures. The algorithm does not assign pixels to cells deterministically; rather, it calculates the probability with which each pixel belongs to the different cells. Through an iterative procedure, the cell parameters and pixel probabilities are updated until the final identification of cells is reached. The second part of the paper deals with a generalization of cluster rainfall models in space and time. The models studied here combine an arbitrary birth point process with arbitrary random fields generated by the cells. Second-moment properties of these processes are derived.

Key words

Radar image Rain cells Random fields Stochastic models Hydrometeorology 

Sommario

Vengono descritti i primi risulati di un lavoro in corso su due problemi legati all'uso del radar meteorologico: l'identificazione automatica delle celle di pioggia e l'estensione dei modelli a cluster per includere la variabilità casuale delle precipitazioni nello spazio e nel tempo all'interno e fra le celle. La necessità di tale estensione sorge sia dall'esame visivo, sia da un'analisi formale delle immagini della riflettività radar. L'algoritmo proposto per l'identificazione delle celle è basato sulle tecniche statistiche per la stima delle miscele di distribuzioni di densità di probabilità. L'algoritmo non assegna in maniera deterministica i singoli pixels alle celle, bensì calcola la probabilità con cui ogni pixel appartiene alle diverse celle. Attraverso una procedura iterativa si calcolano di volta in volta i parametri delle celle e le probabilità dei pixels, fino a che si raggiunge un assetto finale e le celle vengono identificate. Nella seconda parte del lavoro si tratta della generalizzazione dei modelli a cluster nello spazio e nel tempo. I modelli qui studiati combinano un processo arbitrario di occorrenza delle celle con un campo casuale arbitrario generato dalle celle. In particolare, sono derivate le proprietà generali dei secondi momenti di tali processi.

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Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Daniele Veneziano
    • 1
  • Paolo Villani
    • 2
  1. 1.Department of Civil and Environmental EngineeringMassachusetts Institute of TechnologyCambridgeU.S.A.
  2. 2.Dipartimento di Ingegneria CivileUniversità di SalernoFisciano (SA)Italy

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