Dependence of Snow Gauge Collection Efficiency on Snowflake Characteristics

2012 ◽  
Vol 51 (4) ◽  
pp. 745-762 ◽  
Author(s):  
Julie M. Thériault ◽  
Roy Rasmussen ◽  
Kyoko Ikeda ◽  
Scott Landolt
Keyword(s):  
Wind Speed ◽  
Theoretical Study ◽  
Collection Efficiency ◽  
Weather Conditions ◽  
Systematic Errors ◽  
Lagrangian Model ◽  
Field Observations ◽  
Research Fields ◽  
Different Types ◽  
Precipitation Gauge

AbstractAccurate snowfall measurements are critical for a wide variety of research fields, including snowpack monitoring, climate variability, and hydrological applications. It has been recognized that systematic errors in snowfall measurements are often observed as a result of the gauge geometry and the weather conditions. The goal of this study is to understand better the scatter in the snowfall precipitation rate measured by a gauge. To address this issue, field observations and numerical simulations were carried out. First, a theoretical study using finite-element modeling was used to simulate the flow around the gauge. The snowflake trajectories were investigated using a Lagrangian model, and the derived flow field was used to compute a theoretical collection efficiency for different types of snowflakes. Second, field observations were undertaken to determine how different types, shapes, and sizes of snowflakes are collected inside a Geonor, Inc., precipitation gauge. The results show that the collection efficiency is influenced by the type of snowflakes as well as by their size distribution. Different types of snowflakes, which fall at different terminal velocities, interact differently with the airflow around the gauge. Fast-falling snowflakes are more efficiently collected by the gauge than slow-falling ones. The correction factor used to correct the data for the wind speed is improved by adding a parameter for each type of snowflake. The results show that accurate measure of snow depends on the wind speed as well as the type of snowflake observed during a snowstorm.

Study of Photovoltaic Systems’ Performances with Different Module Types

2016 ◽  
Vol 856 ◽  
pp. 279-284 ◽  
Author(s):  
Zahari Zarkov ◽  
Ludmil Stoyanov ◽  
Hristiyan Kanchev ◽  
Valentin Milenov ◽  
Vladimir Lazarov
Keyword(s):  
Theoretical Study ◽  
Weather Conditions ◽  
Operating Conditions ◽  
Experimental Results ◽  
Photovoltaic Systems ◽  
Experimental Site ◽  
Pv Systems ◽  
Research Platform ◽  
Pv Modules ◽  
Different Types

The purpose of the work is to study and compare the performance of photovoltaic (PV) generators built with different types of panels and operating in real weather conditions. The paper reports the results from an experimental and theoretical study of systems with PV modules manufactured according to different technologies and using different materials. The experiment was carried out at a research platform for PV systems developed by the authors, built and located at an experimental site near the Technical University of Sofia. Based on the obtained results, comparisons are made between the different PV generators for the same operating conditions. The comparison between the theoretical and the experimental results demonstrates a good level of overlap.

scholarly journals Adjustments for Wind-Induced Undercatch in Snowfall Measurements Based on Precipitation Intensity

2020 ◽  
Vol 21 (5) ◽  
pp. 1039-1050 ◽  
Author(s):  
Matteo Colli ◽  
Mattia Stagnaro ◽  
Luca G. Lanza ◽  
Roy Rasmussen ◽  
Julie M. Thériault
Keyword(s):  
Wind Speed ◽  
Field Experiments ◽  
Transfer Functions ◽  
Collection Efficiency ◽  
Surface Air Temperature ◽  
Field Measurements ◽  
Precipitation Intensity ◽  
Operational Conditions ◽  
Explanatory Variables ◽  
Precipitation Gauge

AbstractAdjustments for the wind-induced undercatch of snowfall measurements use transfer functions to account for the expected reduction of the collection efficiency with increasing the wind speed for a particular catching-type gauge. Based on field experiments or numerical simulation, collection efficiency curves as a function of wind speed also involve further explanatory variables such as surface air temperature and/or precipitation type. However, while the wind speed or wind speed and temperature approach is generally effective at reducing the measurement bias, it does not significantly reduce the root-mean-square error (RMSE) of the residuals, implying that part of the variance is still unexplained. In this study, we show that using precipitation intensity as the explanatory variable significantly reduces the scatter of the residuals. This is achieved by optimized curve fitting of field measurements from the Marshall Field Site (Colorado, United States), using a nongradient optimization algorithm to ensure optimal binning of experimental data. The analysis of a recent quality-controlled dataset from the Solid Precipitation Intercomparison Experiment (SPICE) campaign of the World Meteorological Organization confirms the scatter reduction, showing that this approach is suitable to a variety of locations and catching-type gauges. Using computational fluid dynamics simulations, we demonstrate that the physical basis of the reduction in RMSE is the correlation of precipitation intensity with the particle size distribution. Overall, these findings could be relevant in operational conditions since the proposed adjustment of precipitation measurements only requires wind sensor and precipitation gauge data.

scholarly journals Snow Particle Collection Efficiency and Adjustment Curves for the Hotplate© Precipitation Gauge

2021 ◽  
Author(s):  
Arianna Cauteruccio ◽  
Enrico Chinchella ◽  
Mattia Stagnaro ◽  
Luca G. Lanza
Keyword(s):  
Wind Speed ◽  
Bluff Body ◽  
Stokes Equations ◽  
Collection Efficiency ◽  
Navier Stokes ◽  
Strong Wind ◽  
Navier Stokes Equations ◽  
Relevant Role ◽  
Tracking Model ◽  
Precipitation Gauge

AbstractThe hotplate precipitation gauge operates by means of a thermodynamic principle. It is composed by a small size disk with two thin aluminium heated plates on the upper and lower faces. Each plate has three concentric rings to prevent the hydrometeors from sliding off in strong wind. As for the more widely used tipping-bucket and weighing gauges, measurements are affected by the wind-induced bias due to the bluff-body aerodynamics of the instrument outer shape. Unsteady Reynolds-Averaged Navier-Stokes equations were numerically solved, using a k-ω shear stress transport closure model, to simulate the aerodynamic influence of the gauge body on the airflow. Wind tunnel tests were conducted to validate simulation results. Solid particle trajectories were modelled using a Lagrangian Particle Tracking model to evaluate the influence of the airflow modification on the ability of the instrument to collect the incoming hydrometeors. A suitable parameterization of the particle size distribution, as a function of the snowfall intensity, was employed to calculate the Collection Efficiency (CE) under different wind conditions. Results reveal a relevant role of the three rings in enhancing the collection performance of the gauge. Below 7.5 m s-1, the CE curves linearly decrease with increasing the wind speed, while beyond that threshold, the blocking caused by the rings counter effects the aerodynamic induced undercatch, and the CE curves quadratically increase with the wind speed. At high wind speed, the undercatch vanishes and the instrument exhibits a rapidly increasing overcatch. For operational purposes, adjustment curves were formulated as a function of the wind speed and the measured snowfall intensity.

Evaluation of wind-induced errors for the Hotplate precipitation gauge using computational fluid dynamic simulations.

2020 ◽  
Author(s):  
Enrico Chinchella ◽  
Arianna Cauteruccio ◽  
Mattia Stagnaro ◽  
Andrea Freda ◽  
Luca Giovanni Lanza
Keyword(s):  
Particle Size ◽  
Wind Speed ◽  
Velocity Field ◽  
Wind Velocity ◽  
Complex Geometry ◽  
Collection Efficiency ◽  
Fluid Dynamic ◽  
Strong Wind ◽  
Precipitation Gauge ◽  
Number Of Particles

<p>Wind is recognised as the major environmental source of error in precipitation measurements. For traditional catching type gauges, which are composed by a funnel to collect the precipitation and a container with a bluff body shape, the exposure effect produces the updraft and acceleration of the velocity field in front and above of the collector. These divert the trajectories of approaching hydrometeors producing  a relevant under-catch, which increases with increasing the wind velocity. This problem has been recently addressed in the literature using Computational Fluid Dynamics (CFD) simulations and a Lagrangian Particle Tracking (LPT) model to provide correction curves for various instruments, which closely match the under-catch observed in field measurements.</p><p>The present work concentrates on the Hotplate precipitation gauge developed at the Research Applications Laboratory, National Center for Atmospheric Research in Boulder, Colorado. The Hotplate differs from the traditional catching type gauges because it operates by means of an indirect thermodynamic principle. Therefore, it is not equipped with any funnel to collect the precipitation and is composed by a small disk with a diameter of 13 cm with two thin aluminium heated plates on the upper and lower faces. On the plates three concentric rings are installed to prevent the hydrometeors from sliding off during strong wind conditions.</p><p>In order to quantify the wind-induced error, the Unsteady Reynolds Averaged Navier Stokes (URANS) equations were numerically solved, with a k-ω SST turbulence closure model, to calculate the airflow velocity field around the instrument. Numerical results were validated by comparison with wind tunnel flow velocity measurements from pressure probes and a Particle Image Velocimetry (PIV) technique.</p><p>Then, with the objective to calculate the Collection Efficiency (CE) the hydrometeor trajectories were modelled using a literature LPT model (Colli et al. 2015) that solves the particle motion equation under the effects of gravity and wind. The path of each particle was analysed, considering the complex geometry of the gauge body, to establish whether it is captured by the instrument or not.</p><p>For various particle size/wind velocity combinations, the ratio between the number of particles captured by the instrument and the number of particles that would be captured if the instrument was transparent to the wind was calculated. Finally, the CE curve was derived assuming a suitable particle size distribution for solid precipitation.</p><p>The results show that the Hotplate gauge presents a very unique response to the wind if compared with more traditional instruments. The CE indeed decreases with increasing the wind speed up to 7.5 m/s, where the effect of geometry starts to overcome the aerodynamic effect, and slowly reverses the trend beyond that value. This effect is so prominent at high wind speed that slightly beyond 15 m/s the under-catch fully disappears and the instrument starts to exhibit a rapidly increasing over-catching bias.</p><p><strong>References:</strong></p><p>Colli, M., Lanza, L.G., Rasmussen, R., Thériault, J.M., Baker, B.C. & Kochendorfer, J. An improved trajectory model to evaluate the collection performance of snow gauges.  Journal of Applied Meteorology and Climatology, 2015, 54, 1826–1836.</p>

scholarly journals Unshielded precipitation gauge collection efficiency with wind speed and hydrometeor fall velocity

2021 ◽  
Vol 25 (10) ◽  
pp. 5473-5491
Author(s):  
Jeffery Hoover ◽  
Michael E. Earle ◽  
Paul I. Joe ◽  
Pierre E. Sullivan
Keyword(s):  
Wind Speed ◽  
Transfer Functions ◽  
Collection Efficiency ◽  
Threshold Function ◽  
Precipitation Event ◽  
Bias Error ◽  
Velocity Dependence ◽  
Fall Velocity ◽  
Dynamics Modelling ◽  
Precipitation Gauge

Abstract. Collection efficiency transfer functions that compensate for wind-induced collection loss are presented and evaluated for unshielded precipitation gauges. Three novel transfer functions with wind speed and precipitation fall velocity dependence are developed, including a function from computational fluid dynamics modelling (CFD), an experimental fall velocity threshold function (HE1), and an experimental linear fall velocity dependence function (HE2). These functions are evaluated alongside universal (KUniversal) and climate-specific (KCARE) transfer functions with wind speed and temperature dependence. Transfer function performance is assessed using 30 min precipitation event accumulations reported by unshielded and shielded Geonor T-200B3 precipitation gauges over two winter seasons. The latter gauge was installed in a Double Fence Automated Reference (DFAR) configuration. Estimates of fall velocity were provided by the Precipitation Occurrence Sensor System (POSS). The CFD function reduced the RMSE (0.08 mm) relative to KUniversal (0.20 mm), KCARE (0.13 mm), and the unadjusted measurements (0.24 mm), with a bias error of 0.011 mm. The HE1 function provided a RMSE of 0.09 mm and bias error of 0.006 mm, capturing the collection efficiency trends for rain and snow well. The HE2 function better captured the overall collection efficiency, including mixed precipitation, resulting in a RMSE of 0.07 mm and bias error of 0.006 mm. These functions are assessed across solid and liquid hydrometeor types and for temperatures between −22 and 19 ∘C. The results demonstrate that transfer functions incorporating hydrometeor fall velocity can dramatically reduce the uncertainty of adjusted precipitation measurements relative to functions based on temperature.

scholarly journals Unshielded precipitation gauge collection efficiency with wind speed and hydrometeor fall velocity. Part I: modelling results

2020 ◽  
Author(s):  
Jeffery Hoover ◽  
Pierre E. Sullivan ◽  
Paul I. Joe ◽  
Michael E. Earle
Keyword(s):  
Wind Speed ◽  
Collection Efficiency ◽  
Navier Stokes ◽  
Lagrangian Analysis ◽  
Fall Velocity ◽  
Empirical Expression ◽  
Wind Speeds ◽  
Wet Snow ◽  
Precipitation Type ◽  
Precipitation Gauge

Abstract. A new method for assessing collection efficiency using wind speed and hydrometeor fall velocity is presented for the unshielded Geonor T-200B3 precipitation gauge based on computational fluid dynamics results. Time-averaged Navier–Stokes simulations with a k–e turbulence model were used to determine the airflow around the gauge for 0 to 10 m s−1 wind speeds. Hydrometeor trajectories and collection efficiencies were determined using Lagrangian analysis for spherical 10 hydrometeor fall velocities between 0.25 to 10 m s−1 for rain (0.01–3.9 mm diameter), wet snow (0.2–21 mm diameter), dry snow (0.2–7.1 mm diameter), and ice pellets (1.5–4.3 mm diameter). The model results demonstrate that gauge collection efficiency strongly depends on both wind speed and hydrometeor fall velocity. Collection efficiency differences for identical hydrometeor fall velocities are within 0.05 for wind speeds less than 4 m s−1, despite differences in hydrometeor type, diameter, density, and mass. An empirical expression for collection efficiency with dependence on wind speed and fall velocity is 15 presented based on the numerical results, giving a RMSE of 0.03 for dry snow, wet snow, and rain, for wind speeds between 0 and 10 m s−1. The use of fall velocity captures differences in collection efficiency due to different hydrometeor types and sizes, and can be broadly applied even where the precipitation type may be unknown or uncertain. Results are compared to previous models and good model agreement with experimental results is demonstrated in Part II.

Impact of Wind Direction, Wind Speed, and Particle Characteristics on the Collection Efficiency of the Double Fence Intercomparison Reference

2015 ◽  
Vol 54 (9) ◽  
pp. 1918-1930 ◽  
Author(s):  
Julie M. Thériault ◽  
Roy Rasmussen ◽  
Eddy Petro ◽  
Jean-Yves Trépanier ◽  
Matteo Colli ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Wind Speed ◽  
Collection Efficiency ◽  
Weather Conditions ◽  
Sources Of Uncertainty ◽  
Fields Of Study ◽  
Particle Characteristics ◽  
The World ◽  
The Impact

AbstractThe accurate measurement of snowfall is important in various fields of study such as climate variability, transportation, and water resources. A major concern is that snowfall measurements are difficult and can result in significant errors. For example, collection efficiency of most gauge–shield configurations generally decreases with increasing wind speed. In addition, much scatter is observed for a given wind speed, which is thought to be caused by the type of snowflake. Furthermore, the collection efficiency depends strongly on the reference used to correct the data, which is often the Double Fence Intercomparison Reference (DFIR) recommended by the World Meteorological Organization. The goal of this study is to assess the impact of weather conditions on the collection efficiency of the DFIR. Note that the DFIR is defined as a manual gauge placed in a double fence. In this study, however, only the double fence is being investigated while still being called DFIR. To address this issue, a detailed analysis of the flow field in the vicinity of the DFIR is conducted using computational fluid dynamics. Particle trajectories are obtained to compute the collection efficiency associated with different precipitation types for varying wind speed. The results show that the precipitation reaching the center of the DFIR can exceed 100% of the actual precipitation, and it depends on the snowflake type, wind speed, and direction. Overall, this study contributes to a better understanding of the sources of uncertainty associated with the use of the DFIR as a reference gauge to measure snowfall.

The Hotplate Precipitation Gauge

2011 ◽  
Vol 28 (2) ◽  
pp. 148-164 ◽  
Author(s):  
Roy M. Rasmussen ◽  
John Hallett ◽  
Rick Purcell ◽  
Scott D. Landolt ◽  
Jeff Cole
Keyword(s):  
Wind Speed ◽  
Weather Conditions ◽  
Rain Gauge ◽  
Precipitation Rate ◽  
Electronic Circuitry ◽  
Precipitation Measurement ◽  
New Instrument ◽  
Update Rate ◽  
Aluminum Plates ◽  
Precipitation Gauge

Abstract A new instrument designed to measure precipitation, the “hotplate precipitation gauge,” is described. The instrument consists of a heated thin disk that provides a reliable, low-maintenance method to measure precipitation rate every minute without the use of a wind shield. The disk consists of two heated, thermally isolated identical aluminum plates—one facing upward and the other downward. The two plates are heated independently, and both are maintained at constant temperature above 75°C by electronic circuitry that heats the plates depending on the deviation from the set temperature. Precipitation rate is estimated by calculating the power required to either melt or evaporate snow or to evaporate rain on the upward-facing plate, compensated for wind effects by subtracting out the power on the lower, downward-facing plate. Data from the World Meteorological Organization reference standard for liquid-equivalent snowfall rate measurements, the Double Fence Intercomparison Reference (DFIR) shield system, were used as the truth to develop the hotplate algorithm. The hotplate measures the liquid-equivalent precipitation rate from 0.25 to 35 mm h−1 within the National Weather Service standard for solid precipitation measurement. The hotplate was also shown to measure wind speed during severe icing conditions and during vibration. The high update rate (precipitation rate, wind speed, and temperature every 1 min), make this an ideal gauge for real-time applications, such as aircraft deicing and road weather conditions. It serves as an accumulation gauge by integrating the 1-min rates over time. It can also be used as a rain gauge for rainfall rates up to 35 mm h−1.

scholarly journals Improvement of solid precipitation measurements using a hotplate precipitation gauge

2021 ◽  
Author(s):  
Julie M. Thériault ◽  
Nicolas R. Leroux ◽  
Roy Rasmussen
Keyword(s):  
Wind Speed ◽  
Transfer Functions ◽  
Collection Efficiency ◽  
Meteorological Conditions ◽  
Speed Limit ◽  
Mean Square ◽  
Wind Speeds ◽  
Solid Precipitation ◽  
Precipitation Measurement ◽  
Precipitation Gauge

AbstractAccurate snowfall measurement is challenging because it depends on the precipitation gauge used, meteorological conditions, and the precipitation microphysics. Upstream of weighing gauges, the flow field is disturbed by the gauge and any shielding used usually creates an updraft, which deflects solid precipitation from falling in the gauge resulting in significant undercatch. Wind shields are often used with weighing gauges to reduce this updraft and transfer functions are required to adjust the snowfall measurements to consider gauge undercatch. Using these functions reduce the bias in precipitation measurement but not the Root Mean Square Error (RMSE) (Kochendorfer et al. 2017a, b). The analysis performed in this study shows that the hotplate precipitation gauge bias after wind correction is near zero and similar to wind corrected weighing gauges but improves on the RMSE or scatter of the collection efficiency of weighing gauges for a given wind speed. To do this, the accuracy of the hotplate was compared to standard unshielded and shielded weighing gauges collected during the WMO SPICE program. The RMSE of the hotplate measurements is lower than weighing gauges (with or without an Alter shield) for wind speeds up to 5 m s-1; the wind speed limit at which sufficient data were available. This study shows that the hotplate precipitation measurement has a low bias and RMSE due to its aerodynamic shape, making its performance mostly independent of the type of solid precipitation.

Theoretical and Experimental Study of Mesoscopic Impactors

1999 ◽  
Author(s):  
Mingqiang Yi ◽  
Howard Hu ◽  
Haim H. Bau ◽  
K. Erickson
Keyword(s):  
Reynolds Number ◽  
Theoretical Study ◽  
Stokes Equations ◽  
Collection Efficiency ◽  
Equation Of Motion ◽  
Navier Stokes ◽  
Navier Stokes Equations ◽  
Different Types ◽  
Theoretical Predictions ◽  
Plate Distance

Abstract An inertial impactor is a device that separates particles from a gas stream according to their mass. The characteristics of two different types of mesoscopic impactors, one with and one without a collection cup, were studied theoretically and experimentally. The theoretical study consists of a numerical solution of the Navier-Stokes equations for the fluid’s flow field and a solution of Newton’s equation of motion for the particles. The particle cut-off sizes and the impactor’s efficiency curves were computed as functions of the jet-to-plate distance, nozzle size, cup size, and the jet’s Reynolds number (Re < 100). Prototypes of impactors were fabricated in low temperature co-fired ceramic tapes. Preliminary experiments were carried out to determine the collection efficiency as a function of particle size and the Reynolds number. The experimental results were critically compared with theoretical predictions.

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