RainFARM: Rainfall Downscaling by a Filtered Autoregressive Model

Rebora, Nicola; Ferraris, Luca; Hardenberg, Jost von; Provenzale, A.

doi:10.1175/jhm517.1

Cited by 111 publications

(98 citation statements)

References 43 publications

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“…For this purpose, techniques originally adopted to examine scalar turbulence have been used, including spectral analysis (Rebora et al, 2006), investigation of scale invariance and multifractality (Veneziano et al, 2006, and references therein), and wavelet-based methods (Venugopal et al, 2006). The application of such tools has revealed the existence of different scaling regimes, i.e., time intervals where the rainfall statistical properties can be expressed through power law relations across scales (Fraedrich and Larnder, 1993;Deidda et al, 1999;Verrier et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

On the nature of rainfall intermittency as revealed by different metrics and sampling approaches

Mascaro

Deidda

Hellies

2013

Hydrol. Earth Syst. Sci.

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Abstract. A general consensus on the concept of rainfall intermittencyhas not yet been reached, and intermittency is often attributed to different aspects of rainfall variability, including the fragmentation of the rainfall support (i.e., the alternation of wet and dry intervals) and the strength of intensity fluctuations and bursts. To explore these different aspects, a systematic analysis of rainfall intermittency properties in the time domain is presented using high-resolution (1-min) data recorded by a network of 201 tipping-bucket gauges covering the entire island of Sardinia (Italy). Four techniques, including spectral and scale invariance analysis, and computation of clustering and intermittency exponents, are applied to quantify the contribution of the alternation of dry and wet intervals (i.e., the rainfall support fragmentation), and the fluctuations of intensity amplitudes, to the overall intermittency of the rainfall process. The presence of three ranges of scaling regimes between 1 min to ∼ 45 days is first demonstrated. In accordance with past studies, these regimes can be associated with a range dominated by single storms, a regime typical of frontal systems, and a transition zone. The positions of the breaking points separating these regimes change with the applied technique, suggesting that different tools explain different aspects of rainfall variability. Results indicate that the intermittency properties of rainfall support are fairly similar across the island, while metrics related to rainfall intensity fluctuations are characterized by significant spatial variability, implying that the local climate has a significant effect on the amplitude of rainfall fluctuations and minimal influence on the process of rainfall occurrence. In addition, for each analysis tool, evidence is shown of spatial patterns of the scaling exponents computed in the range of frontal systems. These patterns resemble the main pluviometric regimes observed on the island and, thus, can be associated with the corresponding synoptic circulation patterns. Last but not least, we demonstrate how the methodology adopted to sample the rainfall signal from the records of the tipping instants can significantly affect the intermittency analysis, especially at smaller scales. The multifractal scale invariance analysis is the only tool that is insensitive to the sampling approach. Results of this work may be useful to improve the calibration of stochastic algorithms used to downscale coarse rainfall predictions of climate and weather forecasting models, as well as the parameterization of intensity-duration-frequency curves, adopted for land planning and design of civil infrastructures.

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Section: Introductionmentioning

confidence: 99%

On the nature of rainfall intermittency as revealed by different metrics and sampling approaches

Mascaro

Deidda

Hellies

2013

Hydrol. Earth Syst. Sci.

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“…Metta et al (2009) developed a probabilistic nowcasting system that exploits a Langevin-type model for the evolution of Fourier phases to generate isotropic stochastic rainfall fields. A similar approach was implemented within the RainFARM model of Rebora et al (2006b) for stochastic NWP precipitation downscaling in space and time. STREAP (Paschalis et al, 2013) also uses the Fourier transform for design storm generation to produce Gaussian random fields with an exponentially decaying isotropic autocorrelation function.…”

Section: Brief Review Of Spatial Stochastic Rainfall Generatorsmentioning

confidence: 99%

A non-stationary stochastic ensemble generator for radar rainfall fields based on the short-space Fourier transform

Nerini

Bešič

Sideris

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. In this paper we present a non-stationary stochastic generator for radar rainfall fields based on the short-space Fourier transform (SSFT). The statistical properties of rainfall fields often exhibit significant spatial heterogeneity due to variability in the involved physical processes and influence of orographic forcing. The traditional approach to simulate stochastic rainfall fields based on the Fourier filtering of white noise is only able to reproduce the global power spectrum and spatial autocorrelation of the precipitation fields. Conceptually similar to wavelet analysis, the SSFT is a simple and effective extension of the Fourier transform developed for space-frequency localisation, which allows for using windows to better capture the local statistical structure of rainfall. The SSFT is used to generate stochastic noise and precipitation fields that replicate the local spatial correlation structure, i.e. anisotropy and correlation range, of the observed radar rainfall fields. The potential of the stochastic generator is demonstrated using four precipitation cases observed by the fourth generation of Swiss weather radars that display significant non-stationarity due to the coexistence of stratiform and convective precipitation, differential rotation of the weather system and locally varying anisotropy. The generator is verified in its ability to reproduce both the global and the local Fourier power spectra of the precipitation field. The SSFT-based stochastic generator can be applied and extended to improve the probabilistic nowcasting of precipitation, design storm simulation, stochastic numerical weather prediction (NWP) downscaling, and also for other geophysical applications involving the simulation of complex nonstationary fields.

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“…The other components of the hydro-meteorological chain are the downscaling module RainFARM (Rebora et al, 2006), and the hydrological model DRiFt (Giannoni et al, 2005;Gabellani et al, 2008).…”

Section: The Hydrometeorological Forecasting Chainmentioning

confidence: 99%

“…The downscaling module produces high-resolution precipitation fields, say one hundred, by preserving the information at large scale derived from a quantitative precipitation prediction and it is in this way able to generate one hundred "universes" with small scale structures of precipitation that are consistent with radar observations of mid-latitude precipitation events (Rebora et al, 2006). Each of the one hundred precipitation fields is then used as input into the hydrological model of each catchment, down to scales of the square kilometer, in order to generate one hundred streamflow scenarios on each catchment.…”

Section: The Hydrometeorological Forecasting Chainmentioning

confidence: 99%

A hydrological analysis of the 4 November 2011 event in Genoa

Silvestro

Gabellani

Giannoni

et al. 2012

Nat. Hazards Earth Syst. Sci.

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Abstract. On the 4 November 2011 a flash flood event hit the area of Genoa with dramatic consequences. Such an event represents, from the meteorological and hydrological perspective, a paradigm of flash floods in the Mediterranean environment.The hydro-meteorological probabilistic forecasting system for small and medium size catchments in use at the Civil Protection Centre of Liguria region exhibited excellent performances for the event, by predicting, 24-48 h in advance, the potential level of risk associated with the forecast. It greatly helped the decision makers in issuing a timely and correct alert.In this work we present the operational outputs of the system provided during the Liguria events and the post event hydrological modelling analysis that has been carried out accounting also for the crowd sourcing information and data. We discuss the benefit of the implemented probabilistic systems for decision-making under uncertainty, highlighting how, in this case, the multi-catchment approach used for predicting floods in small basins has been crucial.

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RainFARM: Rainfall Downscaling by a Filtered Autoregressive Model

Cited by 111 publications

References 43 publications

On the nature of rainfall intermittency as revealed by different metrics and sampling approaches

On the nature of rainfall intermittency as revealed by different metrics and sampling approaches

A non-stationary stochastic ensemble generator for radar rainfall fields based on the short-space Fourier transform

A hydrological analysis of the 4 November 2011 event in Genoa

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