Simulation of yearly rainfall time series at microscale resolution with actual properties: Intermittency, scale invariance, and rainfall distribution. Issue 9 (13th September 2015)

• Record Type: Journal Article
• Authors: Akrour, Nawal; Chazottes, Aymeric; Verrier, Sébastien; Mallet, Cécile; Barthes, Laurent
• Is Part Of: Water resources research. Volume 51:Issue 9(2015:Sep.)
• Page Start: 7417
• Page End: 7435
• Publication Date: 2015-09-13
• Subjects: Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2014WR016357
• Languages: English
• ISSNs: 0043-1397

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Rainfall is a physical phenomenon resulting from the combination of numerous physical processes involving a wide range of scales, from microphysical processes to the general circulation of the atmosphere. Moreover, unlike other geophysical variables such as water vapor concentration, rainfall is characterized by a relaxation behavior that leads to an alternation of wet and dry periods. It follows that rainfall is a complex process which is highly variable both in time and space. Precipitation is thus characterized by the following features: rain/no‐rain intermittency, multiple scaling regimes, and extreme events. All these properties are difficult to model simultaneously, especially when a large time and/or space scale domain is required. The aim of this paper is to develop a simulator capable of generating high‐resolution rain‐rate time series (15 s), the main statistical properties of which are close to an observed rain‐rate time series. We also attempt to develop a model having consistent properties even when the fine‐resolution‐simulated time series are aggregated to a coarser resolution. In order to break the simulation problem down into subcomponents, the authors have focused their attention on several key properties of rainfall. The simulator is based on a sequential approach in which, first, the simulation of rain/no‐rain durations permits the retrieval of fractal properties of the rain support. Then, the generation of rain rates through the use of a multifractal, Fractionally Integrated Flux (FIF), model enables the restitution of the rainfall's multifractal properties. This second step includes a denormalization process that was added in order to generate realistic rain‐rate distributions.</p> </abstract>