Wind Tunnel Validation of a Particle Tracking Model to Evaluate the Wind-Induced Bias of Precipitation Measurements.

Lanza

2020

Water

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Despite the numerous contributions available in the literature about the wind-induced bias of rainfall intensity measurements, adjustments based on collection efficiency curves are rarely applied operationally to rain records obtained from catching-type rain gauges. The many influencing variables involved and the variability of the results of field experiments do not facilitate the widespread application of adjustment algorithms. In this paper, a Lagrangian particle tracking model is applied to the results of computational fluid dynamic simulations of the airflow field surrounding a rain gauge to derive a simple formulation of the collection efficiency curves as a function of wind speed. A new parameterization of the influence of rainfall intensity is proposed. The methodology was applied to a cylindrical gauge, which has the typical outer shape of tipping-bucket rain gauges, as a representative specimen of most operational measurement instruments. The wind velocity is the only ancillary variable required to calculate the adjustment, together with the measured rainfall intensity. Since wind is commonly measured by operational weather stations, its use adds no relevant burden to the cost of meteo-hydrological networks.

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Parameterization of the Collection Efficiency of a Cylindrical Catching-Type Rain Gauge Based on Rainfall Intensity

Lanza

2020

Water

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“…The gauge body, immersed in a wind field, behaves like a bluff‐body obstacle in the free flow, and produces strong velocity gradients, upwards or downwards components and turbulence close to the gauge (Cauteruccio et al, 2020). The hydrometeors trajectories are diverted by the velocity field around the instrument (Cauteruccio et al, 2021a; Cauteruccio et al, 2021b; Cauteruccio et al, 2021c; Colli et al, 2020; Folland, 1988; Jevons, 1861; Nešpor & Sevruk, 1999) and, depending on the gauge shape and wind speed, the number of hydrometeors that cross the sensing volume is affected, leading to an over‐ or under‐estimation of the precipitation intensity. The exposure effect therefore introduces an error, common to all precipitation gauges, that is simply due to the presence of the instrument itself (invasive measurement) and varies with the gauge shape, wind speed and direction, and the PSD.…”

Section: Influence Of Parametersmentioning

confidence: 99%

Calibration of non‐catching precipitation measurement instruments: A review

Lanza

Merlone

Meteorological Applications

et al. 2021

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Non-catching type gauges are the emerging class of in situ precipitation measurement instruments. For these instruments, rigorous testing and calibration are more challenging than for traditional gauges. Hydrometeors characteristics like particle size, shape, fall velocity and density must be reproduced in a controlled environment to provide the reference precipitation, instead of the equivalent water flow used for catching-type gauges. They are generally calibrated by the manufacturers using internal procedures developed for the specific technology employed. No agreed methodology exists, and the adopted procedures are rarely traceable to internationally recognized standards. The EURAMET project 18NRM03 'INCIPIT' on 'Calibration and accuracy of non-catching instruments to measure liquid/solid atmospheric precipitation', funded by the European Metrology Programme for Innovation and Research (EMPIR), was initiated in 2019 to investigate calibration and accuracy issues of non-catching measuring instruments used for liquid/solid atmospheric precipitation measurement. A survey of the existing models of non-catching type instruments was initially performed and this paper provides an overview and a description of their working principles and the adopted calibration procedures. Both literature works and technical manuals disclosed by manufacturers are summarized and discussed, while current limitations and metrological requirements are identified.

“…The gauge body, immersed in a wind field, behaves like a bluff-body obstacle to the undisturbed airflow, producing strong velocity gradients, vertical components, and the development of turbulence close to the gauge surface, see, e.g., [ 4 , 5 ]. The hydrometeor trajectories are diverted by the velocity field around the instrument [ 6 ] depending on their diameter, the gauge shape, wind speed, and wind direction. The induced change in the number of hydrometeors that cross the sensing volume/collecting area of the gauge (for NCGs and CGs, respectively) can lead, in windy conditions, to an over or under estimation of the precipitation amount and intensity (see, e.g., [ 7 ]).…”

Section: Introductionmentioning

confidence: 99%

Investigation of the Wind-Induced Airflow Pattern Near the Thies LPM Precipitation Gauge

Chinchella

Stagnaro

et al. 2021

Sensors

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The airflow velocity pattern generated by a widely used non-catching precipitation gauge (the Thies laser precipitation monitor or LPM) when immersed in a wind field is investigated using computational fluid dynamics (CFD). The simulation numerically solves the unsteady Reynolds-averaged Navier–Stokes (URANS) equations and the setup is validated against dedicated wind tunnel measurements. The adopted k-ω shear stress transport (SST) turbulence model closely reproduces the flow pattern generated by the complex, non-axisymmetric outer geometry of the instrument. The airflow pattern near the measuring area varies with the wind direction, the most intense recirculating flow and turbulence being observed when the wind blows from the back of the instrument. Quantitative parameters are used to discuss the magnitude of the airflow perturbations with respect to the ideal configuration where the instrument is transparent to the wind. The generated airflow pattern is expected to induce some bias in operational measurements, especially in strong wind conditions. The proposed numerical simulation framework provides a basis to develop correction curves for the wind-induced bias of non-catching gauges, as a function of the undisturbed wind speed and direction.