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

Cauteruccio, Arianna; Lanza, Luca G.

doi:10.3390/w12123431

Cited by 17 publications

(36 citation statements)

References 25 publications

(61 reference statements)

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“…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

Cauteruccio

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.

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Section: Introductionmentioning

confidence: 99%

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

Chinchella

Cauteruccio

Stagnaro

et al. 2021

Sensors

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“…Additionally, we implemented in the modelling scheme the turbulence intensity levels obtained from field measurements, using a 3D sonic anemometer. Finally, we used a Lagrangian Particle Tracking (LPT) model to quantify the impact of the free-stream turbulence on the CE of the gauge, to demonstrate that the role of free-stream turbulence is modulated by the particle size distribution (PSD) of the specific precipitation event, and thus depends on the precipitation intensity, consistently with the latest literature developments [16,17].…”

Section: Introductionmentioning

confidence: 64%

On Neglecting Free-Stream Turbulence in Numerical Simulation of the Wind-Induced Bias of Snow Gauges

Cauteruccio

Colli²,

Lanza

2021

Water

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Numerical studies of the wind-induced bias of precipitation measurements assume that turbulence is generated by the interaction of the airflow with the gauge body, while steady and uniform free-stream conditions are imposed. However, wind is turbulent in nature due to the roughness of the site and the presence of obstacles, therefore precipitation gauges are immersed in a turbulent flow. Further to the turbulence generated by the flow-gauge interaction, we investigated the natural free-stream turbulence and its influence on precipitation measurement biases. Realistic turbulence intensity values at the gauge collector height were derived from 3D sonic anemometer measurements. Large Eddy Simulations of the turbulent flow around a chimney-shaped gauge were performed under uniform and turbulent free-stream conditions, using geometrical obstacles upstream of the gauge to provide the desired turbulence intensity. Catch ratios for dry snow particles were obtained using a Lagrangian particle tracking model, and the collection efficiency was calculated based on a suitable particle size distribution. The collection efficiency in turbulent conditions showed stronger undercatch at the investigated wind velocity and snowfall intensity below 10 mm h−1, demonstrating that adjustment curves based on the simplifying assumption of uniform free-stream conditions do not accurately portray the wind-induced bias of snow measurements.

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“…Although factors have been proposed to correct the precipitation under-catch for cylindrical-type gauges [12], we did not correct the measured values in our study due to the lack of a more accurate rain gauge that may serve as a reference. Hence, the measurements returned by the TPB will be taken as a reference to validate the calculated precipitation from corrected DSDs during rainfall records with low wind speed where the expected wind-induced error would be less than 10% according to published literature [11,42,43].…”

Section: Sitementioning

confidence: 91%

“…A rain gauge acts as an obstacle that disturbs the incoming airflow originating turbulence and eddies around, resulting in deflected trajectories of some hydrometeors away from the funnel region and missing the gauge orifice [7,8]. The reduction of particle flow over the gauge (under-catch) due to wind effect depends on wind speed, precipitation type, rainfall intensity, and the aerodynamic design of the rain-gauge [9][10][11][12]. It is especially true for solid precipitation collected by unshielded gauges, where analyzing the measured type, rainfall intensity, and the aerodynamic design of the rain-gauge [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…The reduction of particle flow over the gauge (under-catch) due to wind effect depends on wind speed, precipitation type, rainfall intensity, and the aerodynamic design of the rain-gauge [9][10][11][12]. It is especially true for solid precipitation collected by unshielded gauges, where analyzing the measured type, rainfall intensity, and the aerodynamic design of the rain-gauge [9][10][11][12]. It is especially true for solid precipitation collected by unshielded gauges, where analyzing the measured precipitation characteristics becomes more complex [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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Corrections of Precipitation Particle Size Distribution Measured by a Parsivel OTT2 Disdrometer under Windy Conditions in the Antisana Massif, Ecuador

Gualco

Campozano

Maisincho³

et al. 2021

Water

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Monitoring precipitation in mountainous areas using traditional tipping-bucket rain gauges (TPB) has become challenging in sites with strong variations of air temperature and wind speed (Ws). The drop size distributions (DSD), amount, and precipitation-type of a Parsivel OTT2 disdrometer installed at 4730 m above sea level (close to the 0 °C isotherm) in the glacier foreland of the Antisana volcano in Ecuador are used to analyze the precipitation type. To correct the DSDs, we removed spurious particles and shifted fall velocities such that the mean value matches with the fall velocity–diameter relationship of rain, snow, graupel, and hail. Solid (SP) and liquid precipitation (LP) were identified through −1 and 3 °C thresholds and then grouped into low, medium, and high Ws categories by k-means approach. Changes in DSDs were tracked using concentration spectra and particle’s contribution by diameter and fall velocity. Thus, variations of concentration/dispersion and removed hydrometeors were linked with Ws changes. Corrected precipitation, assuming constant density (1 g cm−3), gives reliable results for LP with respect to measurements at TPB and overestimates SP measured in disdrometer. Therefore, corrected precipitation varying density models achieved fewer differences. These results are the first insight toward the understating of precipitation microphysics in a high-altitude site of the tropical Andes.

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

Cited by 17 publications

References 25 publications

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

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

On Neglecting Free-Stream Turbulence in Numerical Simulation of the Wind-Induced Bias of Snow Gauges

Corrections of Precipitation Particle Size Distribution Measured by a Parsivel OTT2 Disdrometer under Windy Conditions in the Antisana Massif, Ecuador

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