Comparison between Pludix and impact/optical disdrometers during rainfall measurement campaigns

Caracciolo, C.; Prodi, F.; Uijlenhoet, R.

doi:10.1016/j.atmosres.2005.09.007

Cited by 36 publications

(32 citation statements)

References 22 publications

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“…Bonadonna et al 2011). Disdrometers and ash collectors, however, currently show greater potential for measuring particle size and terminal velocity (Marchetti et al 2013;Shimano et al 2013) than PLUDIX, which was designed more for meteorological applications (Caracciolo et al 2006;Prodi et al 2011).…”

Section: How To Link the Geophysical Data With Pyroclast Textural Quamentioning

confidence: 98%

MeMoVolc consensual document: a review of cross-disciplinary approaches to characterizing small explosive magmatic eruptions

et al. 2015

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A workshop entitled “Tracking and understanding volcanic emissions through cross-disciplinary integration: a textural working group” was held at the Université Blaise Pascal (Clermont-Ferrand, France) on the 6–7 November 2012. This workshop was supported by the European Science Foundation (ESF). The main objective of the workshop was to establish an initial advisory group to begin to define measurements, methods, formats and standards to be applied in the integration of geophysical, physical and textural data collected during volcanic eruptions. This would homogenize procedures to be applied and integrated during both past and ongoing events. The workshop comprised a total of 35 scientists from six countries (France, Italy, Great Britain, Germany, Switzerland and Iceland). The four main aims were to discuss and define: standards, precision and measurement protocols for textural analysis; identification of textural, field deposit, chemistry and geophysical parameters that can best be measured and combined; the best delivery formats so that data can be shared between and easily used by different groups; and multi-disciplinary sampling and measurement routines currently used and measurement standards applied, by each community. The group agreed that community-wide, cross-disciplinary integration, centred on defining those measurements and formats that can be best combined, is an attainable and key global focus. Consequently, we prepared this paper to present our initial conclusions and recommendations, along with a review of the current state of the art in this field that supported our discussions

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Section: How To Link the Geophysical Data With Pyroclast Textural Quamentioning

confidence: 98%

MeMoVolc consensual document: a review of cross-disciplinary approaches to characterizing small explosive magmatic eruptions

et al. 2015

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“…For calibration of polarimetric radar by rain gauge and Disdrometer based on daily time, power regression showed the best fit according to Lee and Zawadzki (2006). Moreover, other types of regression models to compare other rainfall measurement instruments such as variety of Disderometer showed acceptable results [34]. The comparison of Ku-band space borne and two ground-based C-band radars during the winter precipitation field, demonstrated that the relationship between dependent and independent variable can be interpreted using logarithmic regression.…”

Section: A Applications Of the Regression Approachmentioning

confidence: 99%

Advanced of Mathematics-Statistics Methods to Radar Calibration for Rainfall Estimation; A Review

Nikahd¹

2015

IJRITCC

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Abstract-Ground-based radar is known as one of the most important systems for precipitation measurement at high spatial and temporal resolutions. Radar data are recorded in digital manner and readily ingested to any statistical analyses. These measurements are subjected to specific calibration to eliminate systematic errors as well as minimizing the random errors, respectively. Since statistical methods are based on mathematics, they offer more precise results and easy interpretation with lower data detail. Although they have challenge to interpret due to their mathematical structure, but the accuracy of the conclusions and the interpretation of the output are appropriate. This article reviews the advanced methods in using the calibration of ground-based radar for forecasting meteorological events include two aspects: statistical techniques and data mining. Statistical techniques refer to empirical analyses such as regression, while data mining includes the Artificial Neural Network (ANN), data Kriging, Nearest Neighbour (NN), Decision Tree (DT) and fuzzy logic. The results show that Kriging is more applicable for interpolation. Regression methods are simple to use and data mining based on Artificial Intelligence is very precise. Thus, this review explores the characteristics of the statistical parameters in the field of radar applications and shows which parameters give the best results for undefined cases.

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“…Thus, from a sampling spectra by the JW impact disdrometer having an electromechanical technology, as it was the case in Dakar and Niamey sites located within the sources zones of sand and dust storms, false spurious spectra (mixture of raindrops and sand/dust particles) would therefore be likely to contaminate the sampled DSDs. Indeed, such an instrument suffers from difficulties to distinguish raindrops and the particles of sand/dust which would fall simultaneously or almost simultaneously [51]. Unfortunately, we could not eliminate such spectra.…”

Section: Consistent Character Of Z-r Relation Variabilitymentioning

confidence: 99%

“…It is not the scope of this paper to study the processes related to the desert dust nor their implications in West Africa monsoon which governs the rainfall. But, we draw attention to the fact that such storms of mixed particles could be, for the JW disdrometer, sources of additional acoustic noise due to the impacts of the particles of sand and dust that could be superimposed on those products by the rain itself [51]. Thus, from a sampling spectra by the JW impact disdrometer having an electromechanical technology, as it was the case in Dakar and Niamey sites located within the sources zones of sand and dust storms, false spurious spectra (mixture of raindrops and sand/dust particles) would therefore be likely to contaminate the sampled DSDs.…”

Section: Consistent Character Of Z-r Relation Variabilitymentioning

confidence: 99%

Consistency in <i>Z</i>-<i>R</i> Relationship Variability Regardless Precipitating Systems, Climatic Zones Observed from Two Types of Disdrometer

Bamba¹,

Ochou²,

Zahiri³

et al. 2014

ACS

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Data from rain Drop Size Distributions gathered on five sites in Africa as well as those of the pilot site in Kourou (French Guyana, South America), located in different climatic zones, and collected by two types of disdrometer (the impact JW RD-69 disdrometer and the Optical Spectro-Pluviometer, OSP) are used to study the consistency of the reflectivity factor-rain rate at the ground (Z-R) relationship variability. The results clearly confirm that the relationship Z-R knows a large spatial variability, from a type of precipitation to another and within the same precipitation regardless the type of disdrometer used for DSD measurements. Base on the similarity of the relations reflectivity factor-rain rate and ratio median volume diameter over the total number of drops-rain rate, the variability of the Z-R coefficients (A, b) through the simultaneously implication of the size and number of drops which characterize the DSD was exhibited. It was shown that the relationships A-α and b-β designed to understand the involvement of parameters D0 and NT of DSD in the variability of the relationship Z-R are similar regardless the types of disdrometer used. However, the relations A-α in the Sahelian region appear to deviate from those of Guinean, equatorial and Soudanian zones. The plausible reasons were discussed.

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Comparison between Pludix and impact/optical disdrometers during rainfall measurement campaigns

Cited by 36 publications

References 22 publications

MeMoVolc consensual document: a review of cross-disciplinary approaches to characterizing small explosive magmatic eruptions

MeMoVolc consensual document: a review of cross-disciplinary approaches to characterizing small explosive magmatic eruptions

Advanced of Mathematics-Statistics Methods to Radar Calibration for Rainfall Estimation; A Review

Consistency in <i>Z</i>-<i>R</i> Relationship Variability Regardless Precipitating Systems, Climatic Zones Observed from Two Types of Disdrometer

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Comparison between Pludix and impact/optical disdrometers during rainfall measurement campaigns

Cited by 36 publications

References 22 publications

MeMoVolc consensual document: a review of cross-disciplinary approaches to characterizing small explosive magmatic eruptions

MeMoVolc consensual document: a review of cross-disciplinary approaches to characterizing small explosive magmatic eruptions

Advanced of Mathematics-Statistics Methods to Radar Calibration for Rainfall Estimation; A Review

Consistency in &lt;i&gt;Z&lt;/i&gt;-&lt;i&gt;R&lt;/i&gt; Relationship Variability Regardless Precipitating Systems, Climatic Zones Observed from Two Types of Disdrometer

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Consistency in <i>Z</i>-<i>R</i> Relationship Variability Regardless Precipitating Systems, Climatic Zones Observed from Two Types of Disdrometer