Dimension statistics of rain cell cores and associated rain rate isopleths derived from radar measurements in the mid-Atlantic coast of the United States

Goldhirsh, J.; Musiani, B.H.

doi:10.1109/36.124213

Cited by 13 publications

(10 citation statements)

References 10 publications

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“…From the distribution of D e , we can deduce the same range of D e between 3.56 and 15.88 km for the MP and SP rain cells but a larger average extension of MP cells (with D e average: 6.64 km) with respect to SP cells (with D e average: 5.28 km). Most authors [21], [30], [34] have proposed an exponential form to represent the equivalentdiameter distribution. The slope parameter values (Λ) of the exponential best fits, which are made on the distributions of D e , result for Λ = 0.43 and Λ = 0.24 for the SP and MP rain cells, respectively.…”

Section: Description Of Midlatitude Rain-cell Featuresmentioning

confidence: 99%

“…4 shows the distribution of another considerable rain-cell parameter: the equivalent diameter D e . The latter is a rain-cell parameter, which is commonly used as a characteristic of the rain-cell size, and it is defined as the diameter of a circular rain cell of area equal to the measured one [21]. We have accounted for the measured rain-cell area A Rm as the number N a of pixels within the rain structure, our spatial sampling being 1 km.…”

Section: Description Of Midlatitude Rain-cell Featuresmentioning

confidence: 99%

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Maximum-Likelihood Retrieval of Modeled Convective Rainfall Patterns from Midlatitude C-Band Weather Radar Data

Montopoli

Marzano

2007

IEEE Trans. Geosci. Remote Sensing

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A spatial characterization of the midlatitude mesoscale rain fields from C-band radar measurements is performed by means of a systematic analysis and modeling of convective rain-cell bidimensional shapes and spatial correlation. A large rainfall dataset that is derived from an operational C-band dual-polarized radar, which is placed in S. Pietro Capofiume near Bologna (Italy), has been collected and analyzed for this purpose. Different models of convective rainy horizontal structures are described and compared. Special attention is devoted to the consolidated unimodal models (or unimodal patterns) like GAUCELL with a Gaussian rain-rate profile and EXCELL with an exponential rain-rate profile, and the hybrid models like HYCELL and DEXCELL based on a proper combination of the previous unimodal models. The new hybrid model DEXELL, which is introduced here, is an extension of the HYCELL model, which is previously proposed in literature. A pixel-by-pixel model numerical integration is carried out in order to perform a homogeneous comparison between the rain-cell model and the measured features such as peak, average, root mean square, gradient average, and gradient deviation of rain rate. A maximum-likelihood algorithm, which is expressed in terms of the principal component of the previous rain-cell features, is introduced to estimate rain-cell pattern parameters from the available radar data. A detailed sensitivity analysis, which is devoted to find the best behavior in terms of root-mean-square error and correlation coefficient between the modeled and measured rain-cell features, is finally carried out.

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Section: Description Of Midlatitude Rain-cell Featuresmentioning

confidence: 99%

Section: Description Of Midlatitude Rain-cell Featuresmentioning

confidence: 99%

Maximum-Likelihood Retrieval of Modeled Convective Rainfall Patterns from Midlatitude C-Band Weather Radar Data

Montopoli

Marzano

2007

IEEE Trans. Geosci. Remote Sensing

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“…Studies published in the past, such as [20] and [21], carried out on the basis of ground radar data collected in different parts of the world, have shown that the distribution function of follows the exponential law (a key assumption of the HYCELL model, as well [15]) (10) where is measured in km, is the threshold in mm/h, whereas and are the two parameters of the distribution. It is worth pointing out that the results shown in Fig.…”

Section: Rain Cells' Probability Of Occurrencementioning

confidence: 99%

“…is the error function (20) whereas , are given by (13) and (14). For the practical application of (18), following the approach of several rainfall models such as [11], [14] and [15], the input is fitted by an analytical model.…”

Section: Rain Cells' Probability Of Occurrencementioning

confidence: 99%

MultiEXCELL: A New Rain Field Model for Propagation Applications

Luini

Capsoni

2011

IEEE Trans. Antennas Propagat.

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MultiEXCELL, a new rainfall model oriented to the analysis of radio propagation impairments which was developed on the basis of a comprehensive rain field database collected by the weather radar sited in Spino d’Adda (Italy), is presented. Single rain cells are modeled by an analytical exponential profile which best represents real single-peaked rain structures. The rain cells’ probability of occurrence is analytically derived from the local rainfall statistics. The spatial features of the rain field at mid- and large-scale are investigated through their natural aggregative process. The clusters (aggregates) of cells are studied in terms of distance between individual cells, of number of cells per aggregate and of distance between aggregates. Finally, the fractional area covered by rain, which the rainfall spatial correlation strongly depends on, is derived from radar data through the comparison with the same quantity provided by global long-term numerical weather products. The MultiEXCELL procedure for the generation of spatially correlated synthetic rain fields is duly presented and the model’s accurateness is preliminary assessed against the available radar dataset. Although MultiEXCELL is mainly oriented to propagation related applications, its cellular approach may reveal useful also in hydrology, for the prediction/management of water resources, and in meteorology, for the nowcasting of the temporal evolution of rain structures

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“…Moreover, in Europe there are about 80 weather radars for meteorological purposes. Images from weather radars have also been used for the characterization of the spatial properties of rain [11].…”

Section: Introductionmentioning

confidence: 99%

Distributed Sensors Network Applied to the Rain Impairment Study on Radiocommunication Systems

Mariño

Fontán

Machado

et al. 2006

2006 IEEE International Conference on Industrial Informatics

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The performance of millimetre wavelength wireless access network technologies are significantly impaired by rain effects. To evaluate the rain effects over a communication system, it is essential to know the temporal and spatial evolution of rainfall rate. For this reason it is necessary to develop an experimental network that provides sufficient data to study and establish means to prevent and compensate for the detrimental effects of rain. In this paper, an experimental rain gauge network is presented. This network comprises weather stations capable of measuring rainfall rate, temperature and humidity. The paper describes first the experimental network for automatic data acquisition as a system based in a distributed process. The design of the experimental network is explained in detail and finally the interest for millimetre wavelength applications is pointed out.

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Dimension statistics of rain cell cores and associated rain rate isopleths derived from radar measurements in the mid-Atlantic coast of the United States

Cited by 13 publications

References 10 publications

Maximum-Likelihood Retrieval of Modeled Convective Rainfall Patterns from Midlatitude C-Band Weather Radar Data

Maximum-Likelihood Retrieval of Modeled Convective Rainfall Patterns from Midlatitude C-Band Weather Radar Data

MultiEXCELL: A New Rain Field Model for Propagation Applications

Distributed Sensors Network Applied to the Rain Impairment Study on Radiocommunication Systems

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