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

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

Measuring solid precipitation using heated tipping bucket gauges: an overview of performance and recommendations from WMO‐SPICE

Comunicación presentada en: TECO-2016 (Technical Conference on Meteorological and Environmental Instruments and Methods of Observation) celebrada en Madrid, del 27 al 30 de septiembre de 2016

Errors and adjustments for WMO-SPICE tipping-bucket precipitation gauges

Presentación realizada en: 19th Symposium on Meteorological Observation and Instrumentation celebrado del 7 al 11 de enero de 2018 en Austin, Texas

An assessment of the impact of a single-Alter windshield on snowfall accumulation reported by a heated tipping bucket gauge

Póster presentado en: WMO Technical Conference on Meteorological and Environmental Instruments and Methods of Observation celebrada del 8 al 11 de octubre de 2018 en Amsterdam

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

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

Applications of the WMO Solid Precipitation Intercomparison Experiment (WMO-SPICE) results for nowcasting activities

Presentación realizada en la 3rd European Nowcasting Conference, celebrada en la sede central de AEMET en Madrid del 24 al 26 de abril de 2019

Development and characterization of a laminar aerosol flow tube

The following article appeared in Review of Scientific Instruments and may be found at https://doi.org/10.1063/1.2175958. This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing.We have developed a new laminar aerosol flow tube (AFT) to study transformations such as ice nucleation, deliquescence, and efflorescence in model atmospheric aerosols. The apparatus consists of four sections which can be independently cooled to reproduce temperature profiles relevant to the troposphere and stratosphere. An automatic control system maintains the average axial temperature along each section between 100 and 300 K, within ±0.1 K. Changes in aerosol composition, phase, and size distribution are monitored at the tube exit using infrared spectroscopy AFT-IR. We used computational fluid dynamics simulations to investigate flow velocity and temperature distributions within the flow tube. Based on these computations, the final design was formulated to eliminate turbulent mixing zones and buoyancy-driven convection cells. The latter can occur even under conditions where the Reynolds number indicates laminar flow. In either case, recirculation causes aerosol residence times and temperature histories to be poorly defined, leading to erroneous interpretation of experimental measurements. The resulting AFT design used copper fins to reduce temperature gradients and axial mixing of aerosol and carrier gas flows in the inlet section to reduce turbulence. The performance of the new AFT is significantly better than for previous designs.The authors are grateful for the financial support of the Natural Sciences and Engineering Research Council of Canada and the Canadian Foundation for Climate and Atmospheric Studies

The potential for uncertainty in Numerical Weather Prediction model verification when using solidprecipitation observations

Precipitation forecasts made by Numerical Weather Prediction (NWP) models are typically verified using precipitation gauge observations that are often prone to the wind‐induced undercatch of solid precipitation. Therefore, apparent model biases in solid precipitation forecasts may be due in part to the measurements and not the model. To reduce solid precipitation measurement biases, adjustments in the form of transfer functions were derived within the framework of the World Meteorological Organization Solid Precipitation Inter‐Comparison Experiment (WMO‐SPICE). These transfer functions were applied to single‐Alter shielded gauge measurements at selected SPICE sites during two winter seasons (2015–2016 and 2016–2017). Along with measurements from the WMO automated field reference configuration at each of these SPICE sites, the adjusted and unadjusted gauge observations were used to analyze the bias in a Global NWP model precipitation forecast. The verification of NWP winter precipitation using operational gauges may be subject to verification uncertainty, the magnitude and sign of which varies with the gauge‐shield configuration and the relation between model and site‐specific local climatologies. The application of a transfer function to alter‐shielded gauge measurements increases the amount of solid precipitation reported by the gauge and therefore reduces the NWP precipitation bias at sites where the model tends to overestimate precipitation, and increases the bias at sites where the model underestimates the precipitation. This complicates model verification when only operational (non‐reference) gauge observations are available. Modelers, forecasters, and climatologists must consider this when comparing modeled and observed precipitation

A preliminary assessment of the biases between forecasted by ECMWF Numerical Weather Prediction model precipitation and the adjusted observed snowfall precipitation in different SPICE sites

Comunicación presentada en: TECO-2018 (Technical Conference on Meteorological and Environmental Instruments and Methods of Observation) celebrada en Amsterdam, del 8 al 11 de octubre de 2018

Errors, biases, and corrections for weighing gauge precipitation measurements from WMO-SPICE

Presentación realizada en: American Meteorological Society Annual Meeting (2017) celebrado en Seattle (Washington) del 22 al 26 de enero de 2017