A Space-Time Stochastic Model of Rainfall for Satellite Remote-Sensing Studies

Bell, Thomas L.

doi:10.1002/9781118782071.ch9

Cited by 34 publications

(82 citation statements)

References 22 publications

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“…As mentioned above, (19) is valid under the assumption that and therefore it is expected to be less and less accurate as diverges more and more from 1. Although the approximation proposed in (19) may appear to be quite rough for some of the values considered in this work (as mentioned in Section II, for ), as it will be shown in the next section, its overall effect on turns out to be very limited because the error inherent in the application of (19) tends to be cancelled out by the division in (18).…”

Section: Spatial Correlation Index Of Rain Attenuationmentioning

confidence: 94%

“…Based on (7) through (11), it is can be easily shown that will not depend on and . Therefore (18) If , obviously . If , it is cumbersome, if even possible, to obtain an exact analytical relationship between and .…”

Section: Spatial Correlation Index Of Rain Attenuationmentioning

confidence: 95%

“…Specifically, the denominator takes into account the distance between points along the same link, whilst the numerator involves sites pertaining to the two different links. Under the hypothesis of spatial stationarity, which is a well-accepted concept for rain fields approximately as wide as [18], the rainfall correlation between two points is assumed to depend only on the distance between them and not on their positions within the field. Thus, the denominator of (12), , can be simplified by the fact that pixels along the link separated by the same distance will be associated to the same correlation value.…”

Section: Spatial Correlation Index Of Rain Attenuationmentioning

confidence: 99%

“…In this position he was in charge of the installation of the meteorological radar of the CNR sited at Spino d'Adda, Italy, and since then he is the scientific responsible for the radar activity. In 1979, he was actively involved in the satellite Sirio SHF propagation experiment (11)(12)(13)(14)(15)(16)(17)(18) and later in the Olympus (12,20 and 30 GHz) and Italsat (20,40 and 50 GHz) satellites experiments. His scientific activity is mainly concerned with theoretical and experimental aspects of electromagnetic wave propagation at centimeter and millimeter wavelengths in presence of atmospheric precipitation with particular emphasis on attenuation, wave depolarization, incoherent radiation, interference due to hydrometeor scatter, precipitation fade countermeasures, modeling of the radio channel and design of advanced satellite communication systems.…”

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confidence: 99%

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On the Relationship Between the Spatial Correlation of Point Rain Rate and of Rain Attenuation on Earth-Space Radio Links

Luini

Capsoni

2013

IEEE Trans. Antennas Propagat.

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This contribution presents an analytical expression to predict the spatial correlation of the rain attenuation A impairing two Earth-space radio links in a site diversity configuration (A) as a function of the spatial correlation of the rain precipitation affecting the area (R), of the distance between the two stations d and of the electrical and geometrical characteristics of the links. Well-established properties of the rain field (i.e. quasi-ergodicity and spatial stationarity) are exploited in the derivation of the proposed analytical expression, whose accuracy is evaluated by means of an extensive set of rain field data collected by the NIMROD weather radar network in the UK. Results indicate a satisfactory prediction performance in the 10-50 GHz frequency range, with negligible dependence on the site separation distance d and on the electrical and geometrical characteristics of the system

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Section: Spatial Correlation Index Of Rain Attenuationmentioning

confidence: 94%

Section: Spatial Correlation Index Of Rain Attenuationmentioning

confidence: 95%

Section: Spatial Correlation Index Of Rain Attenuationmentioning

confidence: 99%

mentioning

confidence: 99%

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On the Relationship Between the Spatial Correlation of Point Rain Rate and of Rain Attenuation on Earth-Space Radio Links

Luini

Capsoni

2013

IEEE Trans. Antennas Propagat.

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“…The methodology lies on the algorithmic approach defined by [20] to simulate bidimensional Gaussian processes with arbitrary spatial covariance function. Here, its adaptation to the one-dimensional case is conducted and is fully demonstrated in Appendix B.…”

Section: Generating Of a One-dimensional Correlated Gaussian Procementioning

confidence: 99%

A Rain Attenuation Time-Series Synthesizer Based on a Dirac and Lognormal Distribution

Boulanger

Féral

Castanet

et al. 2013

IEEE Trans. Antennas Propagat.

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In Recommendation ITU-R P.1853-1, a stochastic approach is proposed to generate long-term rain attenuation time series , including rain and no rain periods anywhere in the world. Nevertheless, its dynamic properties have been validated so far from experimental rain attenuation time series collected at mid-latitudes only. In the present paper, an effort is conducted to derive analytically the first-and second-order statistical properties of the ITU rain attenuation time-series synthesizer. It is then shown that the ITU synthesizer does not reproduce the first-order statistics (particularly the rain attenuation cumulative distribution function CDF), however, given as input parameters. It also prevents any rain attenuation correlation function other than exponential to be reproduced, which could be penalizing if a worldwide synthesizer that accounts for the local climatology has to be defined. Therefore, a new rain attenuation time-series synthesizer is proposed. It assumes a mixed Dirac-lognormal modeling of the absolute rain attenuation CDF and relies on a stochastic generation in the Fourier plane. It is then shown analytically that the new synthesizer reproduces much better the first-order statistics given as input parameters and enables any rain attenuation correlation function to be reproduced. The ability of each synthesizer to reproduce absolute rain attenuation CDFs given by Recommendation ITU-R P.618 is finally compared on a worldwide basis. It is then concluded that the new rain attenuation time-series synthesizer reproduces the rain attenuation CDF much better, preserves the rain attenuation dynamics of the current ITU synthesizer for simulations at mid-latitudes, and, if it proves to be necessary for worldwide applications, is able to reproduce any rain attenuation correlation function.

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Stochastic downscaling of precipitation to high-resolution scenarios in orographically complex regions: 1. Model evaluation

Bordoy

Burlando

2014

Water Resour. Res.

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[1] The simulation of space-time precipitation has been studied since the late 1980s. However, there are still many open issues concerning the most appropriate approach to simulate it, specially in highly heterogeneous areas, such as in mountain environments. For this reason, we present here a comprehensive investigation of the Space-Time NeymanScott Rectangular Pulses model, with the purpose of analyzing its performance in a challenging Alpine environment of Switzerland and identifying weaknesses that can drive future improvements. The results point at the suitability of the model in reproducing not only the basic statistics at different temporal aggregations, but also the more challenging distributional and scaling properties. The intrinsic stationarity of the model in space, induced by the parameter estimation procedure, poses occasional limitations with regard to the accurate simulation of the variability of the observed climate characteristics, which are strongly influenced by local microclimates. However, the model is able, even in the complex Alpine environment, to preserve the spatial patterns observed in the actual precipitation process. The study allowed (i) to conclude about the robustness of the model and its suitability for multisite downscaling of precipitation estimated from climate model simulations, as reported in the companion paper, and (ii) to put in evidence some limitations that require further consideration to improve space-time rainfall generation.Citation: Bordoy, R., and P. Burlando (2014), Stochastic downscaling of precipitation to high-resolution scenarios in orographically complex regions: 1. Model evaluation, Water Resour. Res., 50, 540-561,

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A Space-Time Stochastic Model of Rainfall for Satellite Remote-Sensing Studies

Cited by 34 publications

References 22 publications

On the Relationship Between the Spatial Correlation of Point Rain Rate and of Rain Attenuation on Earth-Space Radio Links

On the Relationship Between the Spatial Correlation of Point Rain Rate and of Rain Attenuation on Earth-Space Radio Links

A Rain Attenuation Time-Series Synthesizer Based on a Dirac and Lognormal Distribution

Stochastic downscaling of precipitation to high-resolution scenarios in orographically complex regions: 1. Model evaluation

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