Validation and application of an urban turbulence parameterisation scheme for mesoscale atmospheric models

Growing population, extensive use (and abuse) of the natural resources, increasing pollutants emissions in the atmosphere: these are a few obstacles (and not the least) one has to face with nowadays to ensure the sustainability of our planet in general, and of the air quality in particular. In the case of air pollution, the processes that govern the transport and the chemical transformation of pollutants are highly complex and non-linear. The use of numerical models for simulating meteorological fields, which in turn will determine the transport of pollutants in the atmosphere, is thus a very appropriate tool to describe and understand the air pollution problematic. This work focuses on the meteorological simulation, using a mesoscale model. The stress is particularly put on the parameterisation of urban induced effects on the meteorological fields above a city. A detailed urban parameterisation scheme has been implemented in a mesoscale model in a previous work. This new scheme takes into account the presence of a city in a more accurate way as the traditional method usually used in mesoscale models. In the first part of this work, the urban module was validated for a one-dimensional off-line simulation within and above a street canyon in the city of Basel/Switzerland. The simulation results were compared with measurements taken within and above the same street canyon during an intensive observation period in the frame of the BUBBLE project (Basel UrBan Boundary Layer Experiment). The comparison with the measurements and with a simulation using the traditional urban parameterisation showed that the detailed urban scheme improved the quality of the simulation of turbulent fluxes and meteorological parameters (wind, temperature) in the urban canopy. Further on, the mesoscale was applied for a three-dimensional simulation over the city of Basel and its surroundings. The results showed that the model is able to reproduce the wind pattern that prevailed during the simulated episode, and that the accuracy of the temperature simulation in the city is improved with the urban module. In the third part of this work, an air quality study was performed over the Mexico City basin. The mesoscale model simulated the meteorological conditions for the chosen episode (1 and 2 March 1997). The results were then passed to TAPOM, a Eulerian photochemical model that calculates the space and time distribution of air pollutants. The simulated concentrations over the basin showed good agreement with the observed values. The validated model could then be used to test some emissions reduction scenarios for Mexico City. The use of the detailed urban parameterisation scheme for meteorological fields and air pollutants concentration simulation improved the quality of the results in almost all the applied situations. Consequently, the full modelling tool presented and validated in this work can be used for air quality modelling studies over cities and their surroundings

Intercomparison of snowfall measurements using disdrometers in two mountainous environments: Weissfluhjoch (Switzerland) and Formigal-Sarrios (Spain)

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.One of the objectives of the WMO/CIMO Solid Precipitation Intercomparison Experiment (SPICE) is to assess the performance of emerging technologies such as disdrometers for the measurement of solid precipitation. Numerous studies have assessed the performance of disdrometers for liquid precipitation, but the experience of using such instruments for solid precipitation is still limited. Among others, the Spanish site at Formigal and the Swiss site at Weissfluhjoch were built with very similar design (especially the reference measurement setting in a Double Fence Intercomparison Reference (DFIR)). Moreover, the environment of both sites (siting) is similar. This work evaluates the potential use of disdrometers for solid precipitation measurement in a mountainous environment. At each site two LPM Thies disdrometers, one shielded in a DFIR and the other one outside (with or without a Thies wind shield), are intercompared under different weather conditions (wind speed and direction, temperature and snowfall intensity) against the SPICE reference measurement using a weighing gauge (OTT Pluvio2 in a DFIR). This study will present preliminary results from both sites and will give first conclusion on the impact of various external parameters (such as wind and temperature) on the disdrometer snow accumulation measurement in and outside the DFIR, and with and without a Thies shield. Moreover, new lines of research are recommended in order to better understand the instrument and the raw data output

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

On the impact of urban surface exchange parameterisations on air quality simulations: the Athens case

Most of the standard mesoscale models represent the dynamic and thermodynamic surface exchanges in urban areas with the same technique used for ruralareas (based on Monin–Obukhov similarity theory and a surface energy budget). However it has been shown that this technique is not able to fully capture the structure of the turbulent layer above a city. Aim of this study is to evaluate the importance for meteorological and air quality simulations, of properly capture the dynamic and thermodynamic surface exchanges in urban areas. Two sets of simulations were performed over the city of Athens (Greece): a first using a mesoscale model with a detailed urban surface exchange parameterisation (able to reproduce the surface exchanges better than the traditionalmethod), and a second with the traditionalapproach. Meteorological outputs are passed to a Eulerian photochemical model (the photochemical model is run offline). Comparison with measurements shows better agreement for the simulation with the detailed parameterisation. The differences between the simulations concern, mainly, wind speed (maximum difference of 0.5–1ms-1), night-time temperatures (2–3°C), turbulence intensity (2m2 s-2) and heat fluxes (0.15Kms-1) over the urban area, urban nocturnal land breeze intensity, timing and extension of sea breeze. These differences modify the pollutant distribution (e.g. for ozone maximum differences are of the order of 30 ppb). Differences between the simulations are also found in AOT60 values (inside and outside the city) and in O3 chemicalregimes

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

The WMO SPICE snow-on-ground intercomparison: an overview of sensor assessment and recommendations on best practices

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.One of the objectives of the WMO Solid Precipitation Intercomparison Experiment (SPICE) was to assess the performance and capabilities of automated sensors for measuring snow on the ground (SoG), including sensors that measure snow depth and snow water equivalent (SWE). The intercomparison focused on five snow depth sensors (models SHM30, SL300, SR50A, FLS-CH 10 and USH-8) and two SWE sensors (models CS725 and SSG1000) over two winter seasons (2013/2014 and 2014/2015). A brief discussion of the measurement reference(s) and an example of the intercomparisons are included. Generally, each of the sensors under test operated according to the manufacturer’s specifications and compared well with the site references, exhibiting high correlations with both the manual and automated reference measurements. The use of natural and artificial surface targets under snow depth sensors were examined in the context of providing a stable and representative surface for snow depth measurements. An assessment of sensor derived measurement quality and sensor return signal strength, where available as an output option, were analysed to help explain measurement outliers and sources of uncertainty with the goal of improving data quality and maximizing the sensor capabilities. Finally, where possible, relationships are established between the gauge measurement of solid precipitation and the measurement of snow on the ground. This paper will provide a brief summary of these results with more detail included in the WMO SPICE Final Report