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.

scholarly journals Errors and adjustments for single-Alter shielded and unshielded weighing gauge precipitation measurements from WMO-SPICE

2017 ◽  
Author(s):  
John Kochendorfer ◽  
Rodica Nitu ◽  
Mareile Wolff ◽  
Eva Mekis ◽  
Roy Rasmussen ◽  
...  
Keyword(s):  
Wind Speed ◽  
Transfer Functions ◽  
Climatic Conditions ◽  
Crystal Habit ◽  
Solid Precipitation ◽  
Precipitation Measurement ◽  
The World ◽  
Winter Time ◽  
Precipitation Gauge ◽  
Type Crystal

Abstract. Although precipitation has been measured for many centuries, precipitation measurements are still beset with significant inaccuracies. Solid precipitation is particularly difficult to measure accurately, and differences between winter-time precipitation measurements from different measurement networks or different regions can exceed 100 %. Using precipitation gauge results from the World Meteorological Organization Solid Precipitation Intercomparison Experiment (WMO-SPICE), errors in precipitation measurement caused by gauge uncertainty, spatial variability in precipitation, hydrometeor type, crystal habit, and wind were quantified. The methods used to calculate gauge catch efficiency and correct known biases are described. Adjustments, in the form of transfer functions that describe catch efficiency as a function of air temperature and wind speed, were derived using measurements from eight separate WMO-SPICE sites for both unshielded and single-Alter shielded weighing precipitation gauges. The use of multiple sites to derive such adjustments makes these results unique and more broadly applicable to other sites with various climatic conditions. In addition, errors associated with the use of a single transfer function to correct gauge undercatch at multiple sites were estimated.

scholarly journals The quantification and correction of wind-induced precipitation measurement errors

2017 ◽  
Vol 21 (4) ◽  
pp. 1973-1989 ◽  
Author(s):  
John Kochendorfer ◽  
Roy Rasmussen ◽  
Mareile Wolff ◽  
Bruce Baker ◽  
Mark E. Hall ◽  
...  
Keyword(s):  
Measurement Errors ◽  
Transfer Functions ◽  
Climate Change Research ◽  
Wind Speeds ◽  
Solid Precipitation ◽  
Precipitation Measurement ◽  
Single Function ◽  
Safety Work ◽  
The Usa ◽  
Precipitation Gauge

Abstract. Hydrologic measurements are important for both the short- and long-term management of water resources. Of the terms in the hydrologic budget, precipitation is typically the most important input; however, measurements of precipitation are subject to large errors and biases. For example, an all-weather unshielded weighing precipitation gauge can collect less than 50 % of the actual amount of solid precipitation when wind speeds exceed 5 m s−1. Using results from two different precipitation test beds, such errors have been assessed for unshielded weighing gauges and for weighing gauges employing four of the most common windshields currently in use. Functions to correct wind-induced undercatch were developed and tested. In addition, corrections for the single-Alter weighing gauge were developed using the combined results of two separate sites in Norway and the USA. In general, the results indicate that the functions effectively correct the undercatch bias that affects such precipitation measurements. In addition, a single function developed for the single-Alter gauges effectively decreased the bias at both sites, with the bias at the US site improving from −12 to 0 %, and the bias at the Norwegian site improving from −27 to −4 %. These correction functions require only wind speed and air temperature as inputs, and were developed for use in national and local precipitation networks, hydrological monitoring, roadway and airport safety work, and climate change research. The techniques used to develop and test these transfer functions at more than one site can also be used for other more comprehensive studies, such as the World Meteorological Organization Solid Precipitation Intercomparison Experiment (WMO-SPICE).

scholarly journals The Quantification and Correction of Wind-Induced Precipitation Measurement Errors

2016 ◽  
Author(s):  
John Kochendorfer ◽  
Roy Rasmussen ◽  
Mareile Wolff ◽  
Bruce Baker ◽  
Mark E. Hall ◽  
...  
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Measurement Errors ◽  
Transfer Functions ◽  
Universal Function ◽  
Climate Change Research ◽  
Wind Speeds ◽  
Solid Precipitation ◽  
The Us ◽  
Precipitation Gauge

Abstract. Hydrologic measurements are becoming increasingly important for both the short and long term management of water resources. Of all the terms in the hydrologic budget, precipitation is the typically most important input. However, measurements of precipitation are still subject to large errors and biases. For example, a high-quality but unshielded weighing precipitation gauge can collect less than 50 % of the actual amount of solid precipitation when wind speeds exceed 5 ms−1. Using results from two different precipitation testbeds, such errors have been assessed for unshielded weighing gauges and for four of the most common windshields currently in use. Functions used to correct wind-induced undercatch were developed and tested. In addition, corrections for the single Altar weighing gauge were developed using the combined results of two separate sites, one of which was in Norway and other in the US. In general the results indicate that corrections described as a function of air temperature and wind speed effectively remove the undercatch bias that affects such precipitation measurements. In addition, a single ‘universal’ function developed for the single Altar gauges effectively removed the bias at both sites, with the bias at the US site improved from −12 % to 0 %, and the bias at the Norwegian site improved from −27 % to −3 %. These correction functions require only wind speed and air temperature, and were developed for use in national and local precipitation networks, hydrological monitoring, roadway and airport safety work, and climate change research. The techniques used to develop and test these transfer functions at more than one site can also be used for other more comprehensive studies, such as the WMO Solid Precipitation Intercomparison Experiment.

scholarly journals Improvement of Snowgauge Collection Efficiency through a knowledge of solid precipitation fallspeed

2021 ◽  
Author(s):  
Nicolas R. Leroux ◽  
Julie M. Thériault ◽  
Roy Rasmussen
Keyword(s):  
Wind Speed ◽  
Transfer Function ◽  
Transfer Functions ◽  
Collection Efficiency ◽  
Particle Diameter ◽  
Field Site ◽  
Solid Precipitation ◽  
Gauge Data ◽  
The Relationship ◽  
Measured Particle

AbstractThe collection efficiency (CE) of a typical gauge-shield configuration decreases with increasing wind speed, with a high scatter for a given wind speed. The scatter in the CE for a given wind speed arises in part from the variability in the characteristics of falling snow and atmospheric turbulence. This study uses weighing gauge data collected at the Marshall Field Site near Boulder, Colorado during the WMO Solid Precipitation InterComparison Experiment (SPICE) to show that the scatter in the collection efficiency can be reduced by considering the fallspeed of solid precipitation particle types. Particle diameter and fallspeed data from a laser disdrometer were used to arrive at this conclusion. In particular, the scatter in the CE of an unshielded snow gauge and a single Alter shield snow gauge is shown to be largely produced by the variation in measured particle fallspeed. The CE was divided into two classes depending on the measured mean-event particle fallspeed. Slower-falling particles were associated with a lower CE. A new transfer function (i.e. the relationship between CE and other meteorological variables, such as wind speed or air temperature) that includes the fallspeed of the hydrometeors was developed. The RMSE of the adjusted precipitation with respect to a weighing gauge placed in a Double Fence Intercomparison Reference was lower than using previously developed transfer functions. This shows that the measured fallspeed of solid precipitation with a laser disdrometer accounts for a large amount of the observed scatter in weighing gauge collection efficiency.

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 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 Using Snowfall Intensity to Improve the Correction of Wind-Induced Undercatch in Solid Precipitation Measurements

2018 ◽  
Author(s):  
Matteo Colli ◽  
Mattia Stagnaro ◽  
Luca Lanza ◽  
Roy Rasmussen ◽  
Julie M. Thériault
Keyword(s):  
Wind Speed ◽  
Field Experiments ◽  
Cfd Simulation ◽  
Transfer Functions ◽  
Collection Efficiency ◽  
Surface Air Temperature ◽  
Test Site ◽  
Precipitation Intensity ◽  
Solid Precipitation ◽  
Tracking Model

Abstract. Transfer functions are generally used to adjust for the wind-induced undercatch of solid precipitation measurements. These functions are derived based on the variation of the collection efficiency with wind speed for a particular type of gauge, either using field experiments or based on numerical simulation. Most studies use the wind speed alone, while others also include surface air temperature and/or precipitation type to try to reduce the scatter of the residuals at a given wind speed. In this study, we propose the use of the measured precipitation intensity to improve the effectiveness of the transfer function. This is achieved by applying optimized curve fitting to field measurements from the Marshall field-test site (CO, USA). The use of a non-gradient optimization algorithm ensures optimal binning of experimental data according to the parameter under test. The results reveal that using precipitation intensity as an explanatory variable significantly reduce the scatter of the residuals. The scatter reduction as indicated by the Root Mean Square Error (RMSE) is confirmed by the analysis of the recent quality controlled data from the WMO/SPICE campaign, showing that this approach can be applied to a variety of locations and catching-type gauges. We demonstrate the physical basis of the relationship between the collection efficiency and the measured precipitation intensity, due to the correlation of large particles with high intensities, by conducting a Computational Fluid-Dynamics (CFD) simulation. We use a Reynolds Averaged Navier-Stokes SST k-ω model coupled with a Lagrangian particle-tracking model. Results validate the hypothesis of using the measured precipitation intensity as a key parameter to improve the correction of wind-induced undercatch. Findings have the potential to improve operational measurements since no additional instrument other than a wind sensor is required to apply the correction. This improves the accuracy of precipitation measurements without the additional cost of ancillary instruments such as particle counters.

scholarly journals Assessment of snowfall accumulation underestimation by tipping bucket gauges in the Spanish operational network

2017 ◽  
Vol 10 (3) ◽  
pp. 1079-1091 ◽  
Author(s):  
Samuel T. Buisán ◽  
Michael E. Earle ◽  
José Luís Collado ◽  
John Kochendorfer ◽  
Javier Alastrué ◽  
...  
Keyword(s):  
Transfer Functions ◽  
Test Site ◽  
Environmental Variable ◽  
State Agency ◽  
Mountain Range ◽  
Northern Spain ◽  
Wind Speeds ◽  
Solid Precipitation ◽  
The World ◽  
Precipitation Gauge

Abstract. Within the framework of the World Meteorological Organization Solid Precipitation Intercomparison Experiment (WMO-SPICE), the Thies tipping bucket precipitation gauge was assessed against the SPICE reference configuration at the Formigal–Sarrios test site located in the Pyrenees mountain range of Spain. The Thies gauge is the most widely used precipitation gauge by the Spanish Meteorological State Agency (AEMET) for the measurement of all precipitation types including snow. It is therefore critical that its performance is characterized. The first objective of this study is to derive transfer functions based on the relationships between catch ratio and wind speed and temperature. Multiple linear regression was applied to 1 and 3 h accumulation periods, confirming that wind is the most dominant environmental variable affecting the gauge catch efficiency, especially during snowfall events. At wind speeds of 1.5 m s−1 the tipping bucket recorded only 70 % of the reference precipitation. At 3 m s−1, the amount of measured precipitation decreased to 50 % of the reference, was even lower for temperatures colder than −2 °C and decreased to 20 % or less for higher wind speeds.The implications of precipitation underestimation for areas in northern Spain are discussed within the context of the present analysis, by applying the transfer function developed at the Formigal–Sarrios and using results from previous studies.

scholarly journals Testing the transfer functions for Geonor T-200B and Chinese standard precipitation gauge (CSPG) in the central Qinghai-Tibet Plateau

2021 ◽  
Author(s):  
Zhang Lele ◽  
Liming Gao ◽  
Ji Chen ◽  
Lin Zhao ◽  
Kelong Chen ◽  
...  
Keyword(s):  
Transfer Functions ◽  
Capture Rate ◽  
Tibet Plateau ◽  
Event Scale ◽  
Solid Precipitation ◽  
Precipitation Measurement ◽  
Precipitation Type ◽  
Precipitation Gauge ◽  
Chinese Standard ◽  
Qinghai Tibet Plateau

Geonor T-200B weighing precipitation gauge (Geonor) and Chinese standard precipitation gauge (CSPG) are widely used for measuring precipitaion in the Qinghai-Tibet Plateau. However, their measurements must be adjusted due to wetting, evaporation loss and wind-induced undercatch. Some transfer functions had been proposed in previous studies, but their applicability in the Qinghai-Tibetan Plateau has not been evaluated. In our study, a precipitation measurement intercomparison experiment was carried out from August 2018 to September 2020 at a station in the central Qinghai-Tibet Plateau, and these transfer functions are also evaluated based on the results of the experiment. The results show that: (1) the catch efficiency of Geonor for rain, mixed, snow, hail are 92.06%, 85.32%, 68.08% and 91.82% respectively, and the catch efficiency of CSPG are 92.59%, 81.32%, 46.43% and 95.56% respectively. (2) K2017b has the most accurate correction results for Geonor solid and mixed precipitation at 30 minutes time scale, and the M2007e scheme has the most accurate correction results for Geonor solid precipitation at event scale. (3) The current transfer functions for CSPG underestimate the solid precipitation, while overestimate the liquid precipitation. Based on the results of the comparative observation in our study, new CSPG transfer functions are proposed for the central Qinghai-Tibet Plateau. (4) Hail is also an important precipitation type in the central Qinghai-Tibet Plateau. Because the capture rate of hail precipitation is close to that of rain, and the temperature when hail precipitation occurs is high, it is not necessary to determine the hail precipitation type, and the transfer functions recommended in this study can also get a good correction results.

scholarly journals Precipitation measurement intercomparison in the Qilian Mountains, Northeastern Tibetan Plateau

2015 ◽  
Vol 9 (2) ◽  
pp. 2201-2230 ◽  
Author(s):  
R. Chen ◽  
J. Liu ◽  
E. Kang ◽  
Y. Yang ◽  
C. Han ◽  
...  
Keyword(s):  
Wind Speed ◽  
Tibet Plateau ◽  
Wind Speeds ◽  
Northeastern Tibet ◽  
Precipitation Measurement ◽  
Combined Use ◽  
The Qilian Mountains ◽  
Precipitation Gauge ◽  
Chinese Standard ◽  
Calibration Equations

Abstract. Systematic errors in gauge-measured precipitation are well-known but no reports have come from the Tibet Plateau. An intercomparison experiment was carried out from September 2010 to September 2014 in the Hulu watershed, northeastern Tibet Plateau. Precipitation gauges included a Chinese standard precipitation gauge (CSPG), a CSPG with Alter shelter (Alter), a Pit type gauge with the CSPG (Pit) and a Double-Fence International Reference with Tretyakov shelter and CSPG (DFIR). The intercomparison experiments show that the Pit gauge caught 1% more rainfall, 2% more mixed precipitation, 4% less snowfall and 0.8% more precipitation (all types) than the DFIR from September 2012 to September 2014. The Pit caught 4% more rainfall, 21% more snow and 16% more mixed precipitation than the CSPG. The DFIR caught 3% more rainfall, 27% more snowfall, and 13% more mixed precipitation than the CSPG, respectively. For rain and mixed precipitation, the catch ratios (CRs) for the gauges are ranked as follows: CRPit > CRDFIR > CRAlter > CRCSPG. For snowfall, the CRs are ranked as follows: CRDFIR > CRPit > CRAlter > CRCSPG. Catch ratio vs. 10 m wind speed indicates that with increasing wind speed from 0 to 4.5 m s−1, the CRCSPG or CRAlter decreased slightly. For mixed precipitation, the ratios of DFIR/Alter or DFIR/Pit vs. wind speed show that wind speed has no significant effect on catch ratio below 3.5 m s−1. For snowfall, the ratio of CSPG/DFIR or Alter/DFIR vs. wind speed shows that catch ratio decreases with increasing wind speed. The calibration equations for three different precipitation types for the CSPG and Alter were established with 10 m wind speeds based on the CR vs. wind speed analysis. Results indicate that combined use of the DFIR and the Pit as reference gauges for snow and rainfall, respectively, could enhance precipitation observation precision. Applicable regions for the Pit gauge or the DFIR as representative gauges for all precipitation types are present in China.

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