Abstract. In the study of space-time rainfall it is particularly important to establish characteristic properties to guide both theoretical and modeling research efforts. In the present paper, new observational analyses on the scaling properties of time-evolving cumulated rainfall fields are presented, and a theoretical framework for their interpretation is introduced. It is found that the time evolution of the spatial organization of a cumulated rainfall field produces scaling relationships of spatial variance versus time and characteristic values for the scaling exponent. The reproduction of these values constitutes a basic requirement for spatial-temporal field generators in order to model important properties of real rainfall fields. It...
International audienceThe theory of scale similarity and breakdown coefficients is applied here to i...
The coupling of hydrological distributed models to numerical weather prediction outputs is an import...
International audienceSimulations based on random multiplicative cascade models are used to investig...
In the study of space-time rainfall it is particularly important to establish characteristic propert...
[1] The identification of general relationships linking statistical properties of rainfall aggregate...
The identification of general relationships linking statistical properties of rainfall aggregated at...
Scale invariance is the most fertile concept to be introduced in stochastic rainfall modeling in 15 ...
The need of understanding and modeling the high space-time variability of rainfall fields produced a...
The rainfall fields exhibits a high space-time variability which generates a large degree of uncerta...
This study gives a phenomenologically based stochastic model of space-time rainfall. Specifically, t...
Several of the existing rainfall models involve diverse assumptions, a variety of uncertain paramete...
This study gives a phenomenologically based stochastic model of space -time rainfall. Specifically, ...
Rainfall has been characterised by a hierarchical structure, the basic elements being rain cells—sma...
High-resolution space-time stochastic models for precipitation are crucial for hydrological applicat...
This study of the behaviour of rainfall dynamics at different temporal scales identifies the type of...
International audienceThe theory of scale similarity and breakdown coefficients is applied here to i...
The coupling of hydrological distributed models to numerical weather prediction outputs is an import...
International audienceSimulations based on random multiplicative cascade models are used to investig...
In the study of space-time rainfall it is particularly important to establish characteristic propert...
[1] The identification of general relationships linking statistical properties of rainfall aggregate...
The identification of general relationships linking statistical properties of rainfall aggregated at...
Scale invariance is the most fertile concept to be introduced in stochastic rainfall modeling in 15 ...
The need of understanding and modeling the high space-time variability of rainfall fields produced a...
The rainfall fields exhibits a high space-time variability which generates a large degree of uncerta...
This study gives a phenomenologically based stochastic model of space-time rainfall. Specifically, t...
Several of the existing rainfall models involve diverse assumptions, a variety of uncertain paramete...
This study gives a phenomenologically based stochastic model of space -time rainfall. Specifically, ...
Rainfall has been characterised by a hierarchical structure, the basic elements being rain cells—sma...
High-resolution space-time stochastic models for precipitation are crucial for hydrological applicat...
This study of the behaviour of rainfall dynamics at different temporal scales identifies the type of...
International audienceThe theory of scale similarity and breakdown coefficients is applied here to i...
The coupling of hydrological distributed models to numerical weather prediction outputs is an import...
International audienceSimulations based on random multiplicative cascade models are used to investig...