ES1.1

In 2022 the European Commission has been monitoring and enforcing the transposition of the Open Data Directive in all EU Member States. Furthermore, it will identify a list of ‘high-value datasets’, whose re-use can bring particular benefits for society, the environment and the economy. Such data will have to be available for re-use for free, in machine-readable format, via APIs and, where relevant, as a bulk download. Meteorological data will likely represent an important part of high-value datasets. The Digital Europe Programme will support creation of common EU data spaces. Finally, two other new and upcoming pieces of legislation focus on easier sharing of data: the Data Governance Act (the Regulation was adopted by the co-legislators in May 2022) and the Data Act (the proposal was submitted to the co-legislators in February 2022).

How to cite: Pilar, J.: Progress with the High Value Datasets project and its potential to enhance the economic impact of the weather value chain, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-721, https://doi.org/10.5194/ems2022-721, 2022.

Lake Street's aim is to help companies 'work with the weather'.  In other words, we look to deliver high value meteorological services that enable the end user to take informed action.  Invariably this means processing weather data alongside datasets from the end user’s sector. 

Using an example from the growing renewable energy sector, we will show how private sector companies are able to identify the relevant datasets – weather and sector specific, translate weather variables to power generation, and present a product that enables informed decision-making. 

Having accurate weather information enables efficient dispatch of fossil-fuel generators when required to match demand, and so helps nations work towards net zero.  This includes information about temporal and spatial correlations that are not immediately obvious from raw weather model output. 

Different models are best for varying timeframes (think within day compared to next week) making no single weather model sufficient on its own.  Further, the timetable of the network operator determines the cut off time for model information, and so influences model choice.

Weather forecasts are not exact and model errors can be considerable.  Knowledge of uncertainties aids decision-making, yet this information is often one of the greatest challenges to calculate.     

Private sector companies act as the translator, and add value at the last step, but could not do this work alone.  They draw on the work of national and international bodies and academia, and in turn feedback observations about forecast error enabling model improvement.  With collaboration, we increase the value of meteorological services and their usefulness to society.

How to cite: Finney, I.: Forecasting renewable energy generation: an example of how the private sector adds value, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-242, https://doi.org/10.5194/ems2022-242, 2022.

The international meteorological community is on a journey to embrace open data policies. Using our experiences from meteoblue, we give examples of how open data policies have fostered innovation, created private sector capabilities, and can “jump-start” meteorological value chains. These examples are typical and variations of them can be found in many companies and countries that implement effective open data policies.

meteoblue as a company wouldn't have been created and might not be sustainable without the benefit of open data. Already prior to forming the company the availability of WRF, GDAS assimilations, and GFS global model output enabled an initial NWP chain. Over time, the evolving processing chain provided an improved, easily accessible forecast for central Europe, in particular the Alps. Additional accuracy was achieved with running models at higher resolutions and tuning them. The development also led to an automatic post-processing and web-based visualisation chain with numerous innovative diagrams and maps.

The increased availability of open NWP data from national weather models and their further improvement allowed meteoblue to automatically evaluate an increasing number of forecasts for a given location, compare them to weather station data, compute a consensus forecast, and quantify the uncertainties of local forecasts. All information could be made available to end users in straightforward diagrams that in part of the world are used by illiterate farmers.

Availability of open weather station data allowed meteoblue to devise learning methods and further improve local forecast accuracy. Verification results are publicly available and allow users to assess how valuable the forecasts can be to them. Open radar data form the basis of a high accuracy nowcast and short term rain forecasts.

With its multi-model capability the processing chain is open to ingest additional models as well as precipitation radar and weather station data, giving their providers (and their users) instant access to all meteoblue post-processing capabilities. The multi-model processing chain is highly resilient against individual model or other data feed failures. Together, these capabilities allow partners, e.g. from small national weather services to both provide immediate access to their local models and service their communities and customers without interruptions. Therefore, meteorological value chains can be started up very quickly.

How to cite: Ramshorn, C., Müller, M. D., and Gutbrod, K. G.: Open data foster innovation and facilitate public-private engagement to create socio-economic value, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-508, https://doi.org/10.5194/ems2022-508, 2022.

EUMETNET Meteoalarm acts as a one-stop-shop for bringing together in one place the authoritative hydromet warnings of 37 National Meteorological and Hydrological Services (NMHSs) in Europe. Global enterprises such as Google, Apple, IBM/The Weather Channel and AccuWeather, who aim to provide a high-quality information service to their users, ingest warnings from European NMHSs, which have been submitted to Meteoalarm via the XML-based Common Alerting Protocol (CAP) format and the Meteoalarm CAP Profile, into their systems. This allows the warning products and services of the relevant NMHSs to reach hundreds of millions end-users 24/7, helping to contribute to public safety in Europe and to offer a seamless transboundary warning service to citizens. Well known products and services of these companies include the standard weather apps for Android and iPhone, weather widgets for Windows 10 and 11 and many others. The engagement of these major re-users allows NMHSs to successfully bridge the often-quoted "last mile" delivery to end-users, which NMHSs by themselves can struggle to achieve. Based on a recent workshop, a survey, and more than ten years of hand-on experience in cooperating with these and other partners, this contribution will give an overview of the needs of re-users in the private sector, both technically and content-wise, with respect to hydromet warnings and connected meta-data. Finally the presentation will discuss future possibilities in deepening cooperation between the public and private sectors, including possible ways and means through which this successful cooperation could, based on user-profiling at the re-users side, in future potentially lead to tailor-made and user-specific impact warnings.

How to cite: Kaltenberger, R.: The Needs of Re-users of Authoritative Hydromet Warnings - Lessons Learned from Meteoalarm, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-706, https://doi.org/10.5194/ems2022-706, 2022.