Some models for rainfall based on stochastic point processes

Rodrı́guez-Iturbe, Ignacio; Cox, David; Isham, Valerie

doi:10.1098/rspa.1987.0039

Cited by 501 publications

(271 citation statements)

References 3 publications

Supporting

Mentioning

265

Contrasting

Unclassified

Order By: Relevance

“…In this study, we examine the impacts of convective variance arising intrinsically at the unresolved scales by representing such variance as a stochastic component of convection. Like the stochastic point process approach to simulating temporal rainfall [Eagleson, 1978;Rodriguez-Iturbe et al, 1987] used in hydrology, the stochastic forcing used in this study aims to reproduce a few statistical features of precipitation, such as the variance and autocorrelation. The aims, however, for the present modeling are different from the hydrology approach; we are not interested in reconstructing sub-grid scale variability for a given mean, but rather we are interested in the variance at the grid-scale arising from sub-grid scale processes.…”

Section: Introductionmentioning

confidence: 99%

Influence of a stochastic moist convective parameterization on tropical climate variability

Lin

Neelin

2000

Geophysical Research Letters

132

111

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

Influence of a stochastic moist convective parameterization on tropical climate variability

Lin

Neelin

2000

Geophysical Research Letters

132

111

View full text Add to dashboard Cite

show abstract

“…Ces modèles s'articulent autour de la modélisation de deux phéno-mènes aléatoires qui sont, l'occurrence et le positionnement de cellules pluvieuses, et la caractérisation du volume de ces cellules (par leur durée et leur intensité) ( ACREMAN (1990), COWPERTWAIT (1991), ONOF et al (1995), RODRIGUEZ-ITURBE et al (1987), WAYMIRE et GUPTA (1981)) ; -les modèles basés sur l'approche directe, (LEBEL (1984), TOURASSE (1981)), qui s'attache à une description géométrique des hyétogrammes horaires par l'intermédiaire de variables aléatoires.…”

Section: -Présentation Du Modèle Initialunclassified

Amélioration des performances d'un modèle stochastique de génération de hyétogrammes horaires: application au pourtour méditerranéen français

Arnaud¹,

Lavabre²,

Masson³

2005

rseau

View full text Add to dashboard Cite

Ce document est protégé par la loi sur le droit d'auteur. L'utilisation des services d'Érudit (y compris la reproduction) est assujettie à sa politique d'utilisation que vous pouvez consulter en ligne. Reçu le 23 janvier 1998, accepté le 13 janvier 1999**. SUMMARYA stochastic mode] for generating hourly hyetographs has been recently developed, in the Cemagref of Aix-en-Provence, to be coupled with a rainfall runoff conversion modelling. Thus, by simulation of very long periods (1000 years for example), we obtain a large number of hourly hyetographs and flood scénarios that are statistically studied and used in flood predetermination problems. The rainfall model studied is based on the theory that rainfall can be linked to a random and intermittent process whose évolution is described by stochastic laws. It is also based on the hypothesis of independence between variables describing hyetographs and on the hypothesis of the stationary nature of the phenomenon studied. Generating a rainfall time séries involves two steps: descriptive study of the phenomenon (nine independent variables are chosen to describe the phenomenon and thèse variables are deflned by a theoretical law of probability fltted to the observations) and création of a rainfall time séries using descriptive variables generated randomly from their law of probability. Initially developed on the Real Collobrier watershed data, the model has been applied to fifty raingauges located on the Mediterranean French seaboard. The extension of the model applying area has shown heterogeneousness in the results. Therefore, modifications hâve been made to the model to improve its performances. Among thèse modifications, three of them hâve presented notable improvements.A study of the sensitivity of the parameters has been made. Parameters of shape variables and of some other variables had only a slight influence on depth of generated rainfalls. But, the law of mean rainfall intensities clearly differentiates the stations. Then, a theoretical probability distribution for the storm intensity variable, less sensitive to the sampling problems, has been Finally, the modelling of storm persistence in a same rainfall épisode has been studied to generate some high 24 hours maximum rainfalls. Persistence modelling is entirely justified by the fact that "ordinary storms" cluster together around the "main storm" (the "main storm" is the greatest storm of an épisode and the "ordinary storms" are the other storms of the épisode). When the study of this phenomenon is extended, it can be observed that there is a certain positive dependency between occurrence probability of the "main storm" and occurrence probability of storms which corne before or after it. Two combined effects occur: within one rainy épisode, the strongest "ordinary storms" are preferentially clustered together around the "main storm", and considering the number of "ordinary storms" throughout ail the épisodes, the strongest storms close to the "main storm" are preferentially associated with the strongest "main ...

show abstract

“…[21] There is no continuous field of streamflow as a function of distance between two nearby gauges on distinct tributaries, as can be assumed for rainfall in point process models [e.g., Rodriguez-Iturbe et al, 1987], because each streamflow gauge makes measurements of flow that is fed through a discrete tributary basin. However, nearby tributary basins that have similar characteristics (e.g., drainage area, slope, land use, and vegetation) are likely to produce similar synchronous streamflow near their confluences with the main channel if there are no orographic effects that consistently cause more rainfall to occur in one basin over the other.…”

Section: Correlation In Eventsmentioning

confidence: 99%

An empirical‐stochastic, event‐based program for simulating inflow from a tributary network: Framework and application to the Sacramento River basin, California

Singer

Dunne

2004

Water Resources Research

View full text Add to dashboard Cite

[1] A stochastic streamflow program was developed to simulate inflow to a large river from a network of gauged tributaries. The program uses historical streamflow data from major tributary gauges near their confluence with the main stem and combines them stochastically to represent spatial and temporal patterns in flood events. It incorporates seasonality, event basis, and correlation in flood occurrence and flood peak magnitude between basins. The program produces synchronous tributary inflow hydrographs, which when combined and routed, reproduce observed main stem hydrograph characteristics, including peak, volume, shape, duration, and timing. Verification of the program is demonstrated using daily streamflow data from primary tributary and main stem gauges in the Sacramento River basin, California. The program is applied to simulating flow at ungauged main stem locations, assessing risk in fluvial systems, and detecting bed level change.

show abstract

Some models for rainfall based on stochastic point processes

Cited by 501 publications

References 3 publications

Influence of a stochastic moist convective parameterization on tropical climate variability

Influence of a stochastic moist convective parameterization on tropical climate variability

Amélioration des performances d'un modèle stochastique de génération de hyétogrammes horaires: application au pourtour méditerranéen français

An empirical‐stochastic, event‐based program for simulating inflow from a tributary network: Framework and application to the Sacramento River basin, California

Contact Info

Product

Resources

About