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Journal ArticleDOI

Parameter Estimation for a Model of Space‐Time Rainfall

James A Smith, +1 more
- 01 Aug 1985 - 
- Vol. 21, Iss: 8, pp 1251-1257
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TLDR
In this article, the spatial distribution of daily rainfall in a 240-mi2 (621 km2) catchment in the Potomac River basin is modeled using a network of rainfall gages.
Abstract
In this paper, parameter estimation procedures, based on data from a network of rainfall gages, are developed for a class of space-time rainfall models. The models, which are designed to represent the spatial distribution of daily rainfall, have three components, one that governs the temporal occurrence of storms, a second that distributes rain cells spatially for a given storm, and a third that determines the rainfall pattern within a rain cell. Maximum likelihood and method of moments procedures are developed. We illustrate that limitations on model structure are imposed by restricting data sources to rain gage networks. The estimation procedures are applied to a 240-mi2 (621 km2) catchment in the Potomac River basin.

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Physical modeling and analysis of rain and clouds by anisotropic scaling multiplicative processes

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Multisite generalization of a daily stochastic precipitation generation model

TL;DR: In this article, the chain-dependent process stochastic model of daily precipitation is extended to simultaneous simulation at multiple locations by driving a collection of individual models with serially independent but spatially correlated random numbers.
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Multiscaling properties of spatial rainfall and river flow distributions

TL;DR: In this paper, a general class of continuous multiplicative processes is constructed to provide a theoretical framework for these observations, namely, the log-log linearity of moments with spatial scale and the concavity of corresponding slopes.
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Multifractals, universality classes and satellite and radar measurements of cloud and rain fields

TL;DR: This work shows how to characterize this variability of cloud and rain fields using scale invariant codimension functions which are exponents characterizing the probability distributions and forms a three parameter universality class for infrared and visible satellite cloud images.
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Influence of rainfall spatial variability on flood prediction

TL;DR: In this paper, the sensitivity of distributed hydrological models to different patterns that account for the spatial distribution of rainfall: spatially averaged rainfall or rainfall field was analyzed and three models were tested using different runoff production models: storm-runoff coefficient, complete or partial interception.
References
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Journal ArticleDOI

A new interdisciplinary focus on precipitation research

TL;DR: In the Hydrology Section of the American Geophysical Union, a new Committee on Precipitation was formed in fall 1982 consisting of nine members from the fields of hydrology, atmospheric sciences, statistics, and mathematics.
Journal ArticleDOI

Stochastic Considerations in Thunderstorm Modeling

TL;DR: In this paper, a mesoscale stochastic model of thunderstorm activity is developed to simulate the hourly development of both air mass and squall-line storms, which is intended to provide a more complete theoretical understanding of the thunderstorm process.
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