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 Evaluation of the WMO Solid Precipitation Intercomparison Experiment (SPICE) transfer functions for adjusting the wind bias in solid precipitation measurements

2020 ◽  
Vol 24 (8) ◽  
pp. 4025-4043 ◽  
Author(s):  
Craig D. Smith ◽  
Amber Ross ◽  
John Kochendorfer ◽  
Michael E. Earle ◽  
Mareile Wolff ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Transfer Functions ◽  
Pearson Correlation ◽  
Data Set ◽  
Solid Precipitation ◽  
Extensive Field ◽  
Precipitation Gauge ◽  
Automated Instruments ◽  
Precipitation Phase ◽  
Wind Bias

Abstract. The World Meteorological Organization (WMO) Solid Precipitation Intercomparison 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 wind shield configurations. Due to the short intercomparison period, the data set was not sufficiently large to develop and evaluate transfer functions using independent precipitation measurements, although on average the adjustments were effective at reducing the bias in unshielded gauges from −33.4 % to 1.1 %. The present analysis uses data collected at eight SPICE sites over the 2015/2016 and 2016/2017 winter periods, comparing 30 min 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 evaluation of the transfer function. Performance is assessed in terms of relative total catch (RTC), root mean square error (RMSE), Pearson correlation (r), and percentage of events (PEs) within 0.1 mm of the DFAR. Metrics are reported for combined 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 to 0.38 mm, r from 0.28 to 0.94, and PEs from 37 % to 84 %, depending on precipitation phase, site, and gauge configuration (gauge and wind screen type). Generally, windier sites, such as Haukeliseter (Norway) and Bratt's Lake (Canada), exhibit a net under-adjustment (RTC of 54 % to 83 %), while the less windy sites, such as Sodankylä (Finland) and Caribou Creek (Canada), exhibit a net over-adjustment (RTC of 102 % to 123 %). 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 variability in the performance metrics among sites suggests that the functions be applied with caution.

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 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 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 Measuring precipitation with a geolysimeter

2017 ◽  
Author(s):  
Craig D. Smith ◽  
Garth van der Kamp ◽  
Lauren Arnold ◽  
Randy Schmidt
Keyword(s):  
Transfer Functions ◽  
Water Pressure ◽  
Pressure Change ◽  
Precipitation Event ◽  
Surface Loading ◽  
Rainfall Events ◽  
Solid Precipitation ◽  
Precipitation Gauge ◽  
Observation Wells ◽  
The Relationship

Abstract. Using the relationship between measured groundwater pressures in deep observation wells with total surface loading, a geological weighing lysimeter (geolysimeter) has the capability of measuring precipitation event totals independent of conventional precipitation gauge observations. Correlations between ground water pressure change and event precipitation were observed at a co-located site near Duck Lake, SK over a multi-year and multi-season period. Correlations varied from 0.99 for rainfall to 0.94 for snowfall. The geolysimeter was shown to underestimate rainfall by 7 % while overestimating snowfall by 9 % as compared to the unadjusted gauge precipitation. It is speculated that the underestimation of rainfall is due to unmeasured runoff and evapotranspiration within the sensing area of the geolysimeter during larger rainfall events while the overestimation of snow is at least partially due to the systematic undercatch common to most precipitation gauges due to wind. Using recently developed transfer functions from the World Meteorological Organization's (WMO) Solid Precipitation Intercomparison Experiment (SPICE), bias adjustments were applied to the Alter shielded, Geonor T-200B precipitation gauge measurements of snowfall to mitigate wind induced errors. The bias between the gauge and geolysimeter measurements was reduced to 3 %. This suggests that the geolysimeter is capable of accurately measuring solid precipitation, and can be used as an independent and representative reference of true precipitation.

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 Measuring precipitation with a geolysimeter

2017 ◽  
Vol 21 (10) ◽  
pp. 5263-5272 ◽  
Author(s):  
Craig D. Smith ◽  
Garth van der Kamp ◽  
Lauren Arnold ◽  
Randy Schmidt
Keyword(s):  
Transfer Functions ◽  
Correlation Coefficients ◽  
Pressure Change ◽  
Precipitation Event ◽  
Surface Loading ◽  
Solid Precipitation ◽  
Run Off ◽  
Precipitation Gauge ◽  
Observation Wells ◽  
The Relationship

Abstract. Using the relationship between measured groundwater pressures in deep observation wells and total surface loading, a geological weighing lysimeter (geolysimeter) has the capability of measuring precipitation event totals independently of conventional precipitation gauge observations. Correlations between groundwater pressure change and event precipitation were observed at a co-located site near Duck Lake, SK, over a multi-year and multi-season period. Correlation coefficients (r2) varied from 0.99 for rainfall to 0.94 for snowfall. The geolysimeter was shown to underestimate rainfall by 7 % while overestimating snowfall by 9 % as compared to the unadjusted gauge precipitation. It is speculated that the underestimation of rainfall is due to unmeasured run-off and evapotranspiration within the response area of the geolysimeter during larger rainfall events, while the overestimation of snow is at least partially due to the systematic undercatch common to most precipitation gauges due to wind. Using recently developed transfer functions from the World Meteorological Organization's (WMO) Solid Precipitation Intercomparison Experiment (SPICE), bias adjustments were applied to the Alter-shielded, Geonor T-200B precipitation gauge measurements of snowfall to mitigate wind-induced errors. The bias between the gauge and geolysimeter measurements was reduced to 3 %. This suggests that the geolysimeter is capable of accurately measuring solid precipitation and can be used as an independent and representative reference of true precipitation.

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 Testing and development of transfer functions for weighing precipitation gauges in WMO-SPICE

2018 ◽  
Vol 22 (2) ◽  
pp. 1437-1452 ◽  
Author(s):  
John Kochendorfer ◽  
Rodica Nitu ◽  
Mareile Wolff ◽  
Eva Mekis ◽  
Roy Rasmussen ◽  
...  
Keyword(s):  
Transfer Functions ◽  
World Meteorological Organization ◽  
Solid Precipitation ◽  
Different Types ◽  
Measurement Biases ◽  
Precipitation Gauge

Abstract. Weighing precipitation gauges are used widely for the measurement of all forms of precipitation, and are typically more accurate than tipping-bucket precipitation gauges. This is especially true for the measurement of solid precipitation; however, weighing precipitation gauge measurements must still be adjusted for undercatch in snowy, windy conditions. In WMO-SPICE (World Meteorological Organization Solid Precipitation InterComparison Experiment), different types of weighing precipitation gauges and shields were compared, and adjustments were determined for the undercatch of solid precipitation caused by wind. For the various combinations of gauges and shields, adjustments using both new and previously existing transfer functions were evaluated. For most of the gauge and shield combinations, previously derived transfer functions were found to perform as well as those more recently derived. This indicates that wind shield type (or lack thereof) is more important in determining the magnitude of wind-induced undercatch than the type of weighing precipitation gauge. It also demonstrates the potential for widespread use of the previously developed transfer functions. Another overarching result was that, in general, the more effective shields, which were associated with smaller unadjusted errors, also produced more accurate measurements after adjustment. This indicates that although transfer functions can effectively reduce measurement biases, effective wind shielding is still required for the most accurate measurement of solid precipitation.

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.

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