Development of a novel balloon-borne optical sonde for the measurement of ozone and other stratospheric trace gases

Ozone, balloon-borne measurements, atmospheric trace gases, concentration profiles, climate change. - In the frame of this work, a new small-size balloon-borne sonde was developed. A miniature grating spectrometer in the sonde measures simultaneously the solar spectral irradiance at a wide wavelength range from 200 to 850. As a first application, ozone profiles have been determined by measuring the changes in the spectral irradiance, caused by ozone absorption in the Huggins band. The wide spectral coverage of the spectrometer offers the possibility for measurements of other trace gases which absorb within the wavelength range, e.g. NO2 and BrO. The low weight of the new sonde (1.7 kg), the moderate price, and the autonomous portable telemetry system makes it a very versatile tool for satellite validation and for case studies, which requires a high number of launches. The newly developed sonde works well without temperature stabilisation, even so the spectrometer experiences rather large temperature changes (15 - 20 K) during the ascent through the atmosphere. Laboratory measurements were performed in ...thesi

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

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

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

Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field Campaign

The High-Latitude Measurement of Snowfall (HiLaMS) campaign explored variability in snowfall properties and processes at meteorologically distinct field sites located in Haukeliseter, Norway, and Kiruna, Sweden, during the winters of 2016/17 and 2017/18, respectively. Campaign activities were founded upon the sensitivities of a low-cost, core instrumentation suite consisting of Micro Rain Radar, Precipitation Imaging Package, and Multi-Angle Snow Camera. These instruments are highly portable to remote field sites and, considered together, provide a unique and complementary set of snowfall observations including snowflake habit, particle size distributions, fall speeds, surface snowfall accumulations, and vertical profiles of radar moments and snow water content. These snow-specific parameters, used in combination with existing observations from the field sites such as snow gauge accumulations and ambient weather conditions, allow for advanced studies of snowfall processes. HiLaMS observations were used to 1) successfully develop a combined radar and in situ microphysical property retrieval scheme to estimate both surface snowfall accumulation and the vertical profile of snow water content, 2) identify the predominant snowfall regimes at Haukeliseter and Kiruna and characterize associated macrophysical and microphysical properties, snowfall production, and meteorological conditions, and 3) identify biases in the HARMONIE-AROME numerical weather prediction model for forecasts of snowfall accumulations and vertical profiles of snow water content for the distinct snowfall regimes observed at the mountainous Haukeliseter site. HiLaMS activities and results suggest value in the deployment of this enhanced snow observing instrumentation suite to new and diverse high-latitude locations that may be underrepresented in climate and weather process studies.Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field CampaignpublishedVersio

Errors, Biases, and Corrections for Weighing Gauge Precipitation Measurements from the WMO Solid Precipitation Intercomparison Experiment

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.Although precipitation has been measured for many centuries, precipitation measurements are still beset with significant biases and errors. Solid precipitation is particularly difficult to measure accurately, and biases between winter-time precipitation measurements from different measurement networks or different regions can exceed 100%. Using precipitation gauge results from the WMO Solid Precipitation Intercomparison Experiment (WMO-SPICE), errors in precipitation measurement caused by gauge uncertainty, spatial variability in precipitation, hydrometeor type, and wind are quantified. The methods used to calculate gauge catch efficiency and correct known biases are described briefly. Transfer functions describing catch efficiency as a function of air temperature and wind speed are also presented. In addition, the biases and errors associated with the use of a single transfer function to correct gauge undercatch at multiple sites are discussed

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

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