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 Analysis of single-Alter-shielded and unshielded measurements of mixed and solid precipitation from WMO-SPICE

2017 ◽  
Vol 21 (7) ◽  
pp. 3525-3542 ◽  
Author(s):  
John Kochendorfer ◽  
Rodica Nitu ◽  
Mareile Wolff ◽  
Eva Mekis ◽  
Roy Rasmussen ◽  
...  
Keyword(s):  
Transfer Functions ◽  
Climatic Conditions ◽  
Crystal Habit ◽  
Solid Precipitation ◽  
Precipitation Measurement ◽  
The World ◽  
The Mean ◽  
Measurement Biases ◽  
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 wintertime precipitation measurement biases between different observing 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 precipitation-weighing gauges. For the unshielded gauges, the average undercatch for all eight sites was 0.50 mm h−1 (34 %), and for the single-Alter-shielded gauges it was 0.35 mm h−1 (24 %). After adjustment, the mean bias for both the unshielded and single-Alter measurements was within 0.03 mm h−1 (2 %) of zero. 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 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 Evaluation of the WMO-SPICE transfer functions for adjusting the wind bias in solid precipitation measurements

2019 ◽  
Author(s):  
Craig D. Smith ◽  
Amber Ross ◽  
John Kochendorfer ◽  
Michael E. Earle ◽  
Mareile Wolff ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Transfer Functions ◽  
Pearson Correlation ◽  
Solid Precipitation ◽  
Extensive Field ◽  
The World ◽  
Precipitation Gauge ◽  
Automated Instruments ◽  
Precipitation Phase ◽  
Wind Bias

Abstract. The World Meteorological Organization (WMO) Solid Precipitation Inter-Comparison Experiment (SPICE) involved extensive field intercomparisons of automated instruments for measuring snow during the 2013/2014 and 2014/2015 winter seasons. A key outcome of SPICE was the development of transfer functions for the wind bias adjustment of solid precipitation measurements using various precipitation gauge and windshield configurations. Due to the short intercomparison period, the dataset was not sufficiently large to develop and evaluate transfer functions using independent precipitation measurements. The present analysis uses data collected at eight SPICE sites over the 2015/2016 and 2016/2017 winter periods, comparing 30-minute adjusted and unadjusted measurements from Geonor T-200B3 and OTT Pluvio2 precipitation gauges in different shield configurations to the WMO Double Fence Automated Reference (DFAR) for the verification of the transfer function. Performance is assessed in terms of relative total catch (RTC), root mean square error (RMSE), and Pearson correlation (r), and Nash-Sutcliffe Efficiency (NSE) for all precipitation types, and for snow only. The evaluation shows that the performance varies substantially by site. Adjusted RTC varies from 54 % to 123 %, RMSE from 0.07 mm to 0.38 mm, and r from 0.28 to 0.94 and NSE from −1.88 to 0.89, depending on precipitation phase, site, and gauge configuration. Generally, windier sites such as Haukeliseter (Norway) and Bratt's Lake (Canada) exhibit a net under-adjustment (17 % to 46 %), while the less windy sites such as Sodankylä (Finland) and Caribou Creek (Canada) exhibit a net over-adjustment (2 % to 23 %). Although the application of transfer functions is necessary to mitigate wind bias in solid precipitation measurements, especially at windy sites and for unshielded gauges, the inconsistency in the performance metrics among sites suggests that the functions be applied with caution.

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 Evaluation of Catch Efficiency Transfer Functions for Unshielded and Single-Alter-Shielded Solid Precipitation Measurements

2019 ◽  
Vol 36 (5) ◽  
pp. 865-881 ◽  
Author(s):  
Amandine Pierre ◽  
Sylvain Jutras ◽  
Craig Smith ◽  
John Kochendorfer ◽  
Vincent Fortin ◽  
...  
Keyword(s):  
Transfer Functions ◽  
Regional Climate ◽  
Solid Precipitation ◽  
Precipitation Measurement ◽  
Mean Wind Speed ◽  
The Mean ◽  
Using Data ◽  
Precipitation Gauge ◽  
Boreal Climate ◽  
Similar Site

AbstractSolid precipitation undercatch can reach 20%–70% depending on meteorological conditions, the precipitation gauge, and the wind shield used. Five catch efficiency transfer functions were selected from the literature to adjust undercatch from unshielded and single-Alter-shielded precipitation gauges for different accumulation periods. The parameters from these equations were calibrated using data from 11 sites with a WMO-approved reference measurement. This paper presents an evaluation of these transfer functions using data from the Neige site, which is located in the eastern Canadian boreal climate zone and was not used to derive any of the transfer functions available for evaluation. Solid precipitation measured at the Neige site was underestimated by 34% and 21% when compared with a manual reference precipitation measurement for unshielded and single-Alter-shielded gauges, respectively. Catch efficiency transfer functions were used to adjust these solid precipitation measurements, but all equations overestimated amounts of solid precipitation by 2%–26%. Five different statistics evaluated the accuracy of the adjustments and the variance of the results. Regardless of the adjustment applied, the catch efficiency for the unshielded gauge increased after the adjustment. However, this was not the case for the single-Alter-shielded gauges, for which the improvement of the results after applying the adjustments was not seen in all of the statistics tests. The results also showed that using calibrated parameters on datasets with similar site-specific characteristics, such as the mean wind speed during precipitation and the regional climate, could guide the choice of adjustment methods. These results highlight the complexity of solid precipitation adjustments.

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.

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