Quantification of lightning-produced NO_x over the Pyrenees and the Ebro Valley by using different TROPOMI-NO₂ and cloud research products

Lightning is one of the major sources of nitrogen oxides (NOx) in the atmosphere, contributing to the tropospheric concentration of ozone and to the oxidising capacity of the atmosphere. Lightning produces between 2–8 Tg N per year globally and on average about 250 ± 150 mol NOx per flash. In this work, we estimate the moles of NOx produced per flash (LNOx production efficiency) in the Pyrenees (Spain, France and Andorra) and in the Ebro Valley (Spain) by using nitrogen dioxide (NO2) and cloud properties from the TROPOspheric Monitoring Instrument (TROPOMI) and lightning data from the Earth Networks Global Lightning Network (ENGLN) and from the EUropean Co-operation for LIghtning Detection (EUCLID). The Pyrenees is one of the areas in Europe with the highest lightning frequency and, due to its remoteness as well as experiencing very low NOx background, enables us to better distinguish the LNOx signal produced by recent lightning in TROPOMI NO2 measurements. We compare the LNOx production efficiency estimates for 8 convective systems in 2018 using two different sets of TROPOMI research products, provided by the Royal Netherlands Meteorological Institute (KNMI) and the Deutsches Zentrum für Luft- und Raumfahrt (DLR), respectively. According to our results, the mean LNOx production efficiency in the Pyrenees and in the Ebro Valley, using a three-hour chemical lifetime, ranges between 14 and 103 mol NOx per flash from the 8 systems. The mean LNOx production efficiency estimates obtained using both TROPOMI products and ENGLN lightning data differ by ∼23 %, while it differs by ∼35 % when using EUCLID lightning data. The main sources of uncertainty when using ENGLN lightning data are the estimation of background NOx that is not produced by lightning and the time window before the TROPOMI overpass that is used to count the total number of lightning flashes contributing to fresh-produced LNOx. The main source of uncertainty when using EUCLID lightning data is the uncertainty in the detection efficiency of EUCLID.

From climate information to climate services: the need for a Belgian climate service centre

<p>The Belgian expertise with respect to climate research is very fragmented and led by both federal (like the Royal Meteorological Institute of Belgium, hereafter RMI) as well as regional scientific research institutions and universities. Furthermore, both in societal, research as well as policy context there is an increasing need for detailed, quantitative, reliable and consistent climate information and services, in particular linked to the expected climate changes and its impacts in different sectors (e.g. water, agriculture, energy, health, transport).</p><p>To make all this scientific expertise and climate information available in a coordinated and, above all, user-friendly way, a Belgian climate centre or a one-stop shop for climate research and services would fully address the needs. With its long-standing scientific expertise and service provision, RMI plays a crucial role in fulfilling this growing need for climate information and services.</p><p>Hence, RMI has elaborated a proposal on the creation of a Belgian climate centre. For the creation of such centre it is preferable to use existing collaborations from previous or ongoing research and service-provision activities in Belgium, requiring a structural cooperation in which each members’ expertise can be fully deployed. In the context of a previous research project, a large consortium of Belgian research institutions active in regional climate modelling, calculated for the first time a consistent set of high-resolution climate projections and sectoral impacts for Belgium. Nevertheless, it should be emphasized that the number of models used was far too limited to develop reliable information of the future climate. Moreover, this was a one-time project and there is currently an urgent need to update the climate projections to meet the new scientific requirements of the IPCC's new sixth Assessment Report.</p><p>One of the activities of the centre would thus be the coordination of the climate research based on scientific research projects. Furthermore, in order to ensure the continuous development and provision of climate services based on this objective and scientifically based expertise coming from Belgian climate scientists, the climate centre would carry out two main core tasks: (i) the production and storage of climate information and (ii) the support for the development of climate services.</p><p>The financing and implementation of a Belgian climate centre, would provide a structural framework for climate research and services, establishing partnerships with the various regions and communities, at both policy and research levels. In this way, RMI, as national meteorological institute and at the start of the climate services value chain, can guarantee a continuous scientific expertise and respond to the major needs for climate information and services at national and international level.</p>

European Weather Cloud at the service of the European Meteorological Infrastructure (EMI)

<p>Since 2019, ECMWF (European Centre for Medium-Range Weather Forecasts) together with EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) initiated a project named “<strong>European Weather Cloud</strong>” (https://www.europeanweather.cloud/) expected to become operational in 2022. The strategic goal of this initiative is to build and offer a <strong>community cloud infrastructure</strong> on which Member and Co‐operating States of both organizations can create and manage on demand virtual resources enabling access to the ECMWF’s Numerical Weather Predication (NWP) products and EUMETSAT’s satellite data in a timely, efficient, and configurable fashion. Moreover, one of the main goals is to involve more entities in this initiative in a joint effort to form a federation of clouds/data offered from our Member States, for the maximum benefit of the European Meteorological Infrastructure.</p><p>During the current pilot phase of the project several use cases have been defined, mostly aimed at service developers own organisations. These broad categories of use cases are:</p><ul><li>Web services exploring hosted datasets.</li> <li>Infrastructure allowing the running of an atmospheric dispersion model on ECMWF forecast data.</li> <li>Platform to support the training of machine learning models on archive datasets.</li> <li>Platform to support workshops and training courses (DWD/ICON model training, various ECMWF training courses)</li> <li>Environment facilitating research in collaboration with external partners.</li> </ul><p>Some examples of the use cases currently developed at the European Weather Cloud are:</p><ul><li>The Royal Meteorological Institute of Belgium prepares ECMWF forecast data for use in a local atmospheric dispersion model.</li> <li>The German weather service, which is already feeding maps generated by a server it deployed on the cloud into its public GeoPortal service.</li> <li>The Royal Netherlands Meteorological Institute hosts a climate explorer web application based on KNMI climate explorer data and ECMWF weather and climate reanalyses.</li> <li>EUMETSAT Numerical Weather Prediction Satellite Application Facility (NWP SAF) develops a training module will develop a training module for a fast radiative transfer model (RTTOV) based on ERA5 reanalysis data.</li> <li>EUMETSAT and ECMWF joint use case assess bias correction schemes for the assimilation of radiance data based on several satellite data time series.</li> </ul><p>During the current pilot phase of the project, both organizations have organised user and technical workshops to actively engage with the meteorological community to align the evolution of the European Weather Cloud to reflect and satisfy their goals and needs.</p><p>In this presentation, the status of the project will be analysed describing the existing infrastructure, the offered services and how these are accessed by the end-users along with examples of the existing use cases. The plans, next steps for the evolution and the transition to operations of the European Weather Cloud and its relationship with other projects and initiatives will conclude the presentation.</p>

Autonomous driving in adverse winter weather conditions

<p>Autonomous driving can be challenging especially in winter conditions when road surface is covered by icy and snow or visibility is low due to precipitation, fog or blowing snow. These harsh weather and road conditions set up very important requirements for the guidance systems of autonomous cars. In the normal conditions autonomous cars can drive without limitations but otherwise the speed must be reduced, and the safety distances increased to ensure safety on the roads. </p><p>Autonomous driving needs very precise and real-time weather and road condition information. Data can be collected from different sources, like (road) weather models, fixed road weather station network, weather radars and vehicle sensors (for example Lidars, radars and dashboard cameras). By combining the all relevant weather and road condition information a weather-based autonomous driving mode system is developed to help and guide autonomous driving. The driving mode system is dividing the driving conditions from perfect conditions to very poor conditions. In between there are several steps with slightly alternate driving modes depending for example snow intensity and friction. In the most challenging weather conditions, automatic driving must be stopped because the sensors guiding the driving are disturbed by for example heavy snowfall or icy road.</p><p>Finnish Meteorological Institute is testing autonomous driving in the Arctic vehicular test track in Sodankylä, Northern Finland. The test track is equipped with road weather observation system network including road weather stations, IoT sensors measuring air temperature and humidity along with various communication systems. Also, tailored road weather services are produced to the test track, like precise road weather model calculations and very accurate radar precipitation observations and nowcasting. The developed weather-based autonomous driving system is tested on Sodankylä test track among other arctic autonomous driving testing.</p><p>This study presents the Sodankylä Arctic vehicular test track environment and weather-based autonomous driving mode system that is developed at the Finnish Meteorological Institute.</p>

Serving Open Data from mixed on-premise and cloud environment at the Finnish Meteorological Institute.

<p>Finnish Meteorological Institute has a long history of open data. Partly as a result of the INSPIRE directive almost all important data was opened back in 2013. Because of this we have quite a long history of usage of the data and as well experience on technical solutions and user needs. The presentation will open up the current status and future development keeping in mind the upcoming WMO WIS2 development as well as the Open Data directive with its High Value Dataset proposal which will very likely feature meteorological datasets.</p><p>Data is provided via machine-readable interfaces as well as human usable web interfaces. We use on-premise storage and interfaces and in addition also offer cloud-based distribution such as the Amazon Public Dataset program. The current operational interfaces are based on WFS 2.0 and WMS. Most recently added datasets include weather and flood warnings in Common Alerting Protocol (CAP) format, black carbon measurements and radar data archive via Amazon S3 in GeoTIFF and HDF5 formats. There is development starting for providing data via even more developer-friendly interfaces such as the OGC Features API. Also new data is being added continuously based on our own and user needs.</p><p>An impact study has also been conducted for the year 2018 which reveals some findings on what data is used and how it impacts the users and their potential businesses. Also valuable information on the future needs of users was gathered and the most important findings of this study will be presented during the session.</p>

Weather and Climate Services in Africa as Digital Public Goods

<p>The global digitalization of societies is arguably one of the most influential  drivers of change in the development, implementation and dissemination of weather and climate information. From observations and measurements, to communication of weather warnings, the value chain of Weather & Climate Services (WCS) is increasingly characterized by digital interactions. Yet, digitalization occurs at different paces across regions, depending on a wide range of (local) socio-economic factors. Access to digital information is an important indicator of socio-economic development, and as such strongly embedded in the UN’s Sustainable Development Goals. Particularly in the context of objectives to provide equal access to information, education and knowledge, open weather data can provide significant benefits in developing countries, and contribute to meeting various SDGs. </p><p>Many NMHSs, including the Norwegian Meteorological Institute, currently provide access to weather data under open access licences. One of its most important open data data services is MET Norway Weather API, a global location based time-series forecast service. Recently this api has formally been recognized as a Digital Public Good. </p><p>Open weather data can provide opportunities to improve the forecasting capacity of African NMHSs and improve the quality of weather and climate information in African countries. With the objective to provide leading examples of the potential of open weather data as Digital Public Good, the Norwegian Meteorological Institute has been funded by NORAD to explore this potential in a pilot project together with African NMHSs. We present insights and experiences from the pilot phase of our collaboration with NMA in Ethiopia, and DCCMS in Malawi. We reflect on the challenges and successes of the first phase of this project. Also, we present an overview of key factors that need consideration when aiming to transform open weather data into value-added services that meet user-oriented criteria of Digital Public Goods. Finally, we provide an overview of next steps to move beyond the pilot phase.</p>

Atmospheric aerosol, gases, and meteorological parameters measured during the LAPSE-RATE campaign by the Finnish Meteorological Institute and Kansas State University

Small unmanned aerial systems (sUASs) are becoming very popular as affordable and reliable observation platforms. The Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE), conducted in the San Luis Valley (SLV) of Colorado (USA) between 14 and 20 July 2018, gathered together numerous sUASs, remote-sensing equipment, and ground-based instrumentation. Flight teams from the Finnish Meteorological Institute (FMI) and the Kansas State University (KSU) co-operated during LAPSE-RATE to measure and investigate the properties of aerosol particles and gases at the surface and in the lower atmosphere. During LAPSE-RATE the deployed instrumentation operated reliably, resulting in an observational dataset described below in detail. Our observations included aerosol particle number concentrations and size distributions, concentrations of CO2 and water vapor, and meteorological parameters. All datasets have been uploaded to the Zenodo LAPSE-RATE community archive (https://zenodo.org/communities/lapse-rate/, last access: 21 August 2020). The dataset DOIs for FMI airborne measurements and surface measurements are available here: https://doi.org/10.5281/zenodo.3993996, Brus et al. (2020a), and those for KSU airborne measurements and surface measurements are available here: https://doi.org/10.5281/zenodo.3736772, Brus et al. (2020b).

TV meteorologists at MET Norway as climate communicators

Climate change ought to be a natural part of the weather conversation on TV, radio and social media. Inspired by similar projects in other countries, the Norwegian Meteorological institute established a project in 2019 to develop their TV meteorologists as climate change communicators. The main objective in the project was to integrate research-based, localized climate content in the weather presentation, as to inform and engage the Norwegian public about climate change. Over a period of almost two years, the project has produced several climate stories on the national TV-news. The majority of the stories have also been shared through social media and through press releases to reach a wide range of audiences. In this paper, experiences from the project at the Norwegian Meteorological institute are shared along with recommendations for climate communication. We claim that TV meteorologists can have an important role in climate change communication, with a potential that is often not yet fully realized, and give our thoughts on how to further develop their role.

Hourly and Daily Reference Evapotranspiration with ASCE-PM Model for Paraná State, Brazil

The objective of this study was to verify the magnitude and trend of hourly reference evapotranspiration (EToh), as well as associate and analyze daily ETo (ETod) series and the sum of hourly ETo (ETo24h) in 24 h, estimated with the Penman-Monteith ASCE model for Paraná State (Cfa and Cfb climate type). Relative humidity (RH), temperature (T), solar radiation (Rs) and wind speed (u2) data were obtained from 25 meteorological stations from the National Meteorological Institute (INMET), between December 1, 2016 to November 8, 2018. The analyzes were performed by linear regression and associations considering the root mean square error, correlation coefficient and index of agreement. The EToh trend has a Gaussian distribution, with the highest values between 12:00 p.m. and 2:00 p.m., with the maximum average being 0.44 mm h−1 (Cfa climate type) and 0.35 mm h−1 (Cfb climate type). The average difference between the ETo24h and ETod values was small (5.1% for Cfa and 7.4% for Cfb), resulting in close linear associations. The results obtained indicate that EToh has good potential to be used in planning and management in the field of soil and water engineering, in Paraná State.