4-9 September 2022, Bonn, Germany
Delivering high value meteorological services to benefit our communities


The European Union Report on ‘High-value datasets’ examined 6 key sectors and ranked Meteorological data second, just below Geospatial data, in terms of Economic impact. When combined with the third ranked sector (Earth observation and environment), meteorology datasets represent by far the most significant data sector for society.

These data have to be processed into services and delivered to a wide range of public and business sectors in the economic value chain.

The ‘Value-chain’ concept is now widely discussed in the meteorological community; it describes the sequential steps in the journey from basic (observational) data, through forecasting technology and onto the delivery of targeted services. It is recognised that the products and services that deliver the highest value often arise at the far end of the value-chain and may create the highest impact when integrated with other datasets that lie outside the meteorological domain, such as e.g. renewable energy forecasts, air traffic and ship routing, impact based warnings, climate change impact assessment etc.

This session will include:
• A keynote speaker to describe the High-value datasets concepts and provide an update on progress towards the goal of delivering the potential Economic Impact along the value chain.
• Examples from providers of innovative products and services operating at the end of the value chain where maximum impact is achieved by integrating weather information with other sources of data.

Speakers will be invited from all players in the Global Weather Enterprise:
• National and International bodies that require government funding.
• Private sector companies that thrive in an open and competitive environment.
• Academia where new research drives scientific progress.

These players are mutually dependent to deliver the full value of meteorological data and must align their strategy to deliver the EU Vision.

Conveners: Andrew Eccleston, Willie McCairns, Gerald Fleming
| Thu, 08 Sep, 11:00–13:00 (CEST)|Room HS 7
| Attendance Thu, 08 Sep, 14:00–15:30 (CEST) | Display Thu, 08 Sep, 08:00–Fri, 09 Sep, 14:00|b-IT poster area

Session assets

Orals: Thu, 8 Sep | Room HS 7

Chairpersons: Willie McCairns, Andrew Eccleston
Onsite presentation
Jiri Pilar

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.

Onsite presentation
Andrew Eccleston, Karl Gutbrod, Christian Gruninger-Hermann, and Dennis Schulze

PRIMET has conducted a market research study on the weather services market in the EU-28 countries for the period of 2010-2020, including National and Private Weather services providers. The study covers annual revenue, employee numbers and segments of market activities. The study does not include the market for meteorological instruments, nor down-stream markets with integrators of meteorology information, such as insurances, agriculture and others.

The study identifies the market activity in each country by the 5 classes described below and makes some projections for the next decade.

a. monopolistic: private sector not allowed, only National Hydro-Meteorological Service (NHMS; state agency) allowed to provide weather services;

b. centralistic: private sector allowed, but NHMS is main provider of weather services and does not provide the necessary base data to private sector, so no, or only very few private companies exist (e.g. Romania);

c. oligopolistic: private sector allowed, NHMS provides the necessary base data to private sector, but influences rules and exerts strong commercial competition in the market place, so private companies are disadvantaged in the competition (e.g. France);

d. polipolistic: private sector allowed, NHMS provides all necessary base data to private sector, and is commercially active in some segments, without unfair competition in the market place (e.g. Germany);

e. free: private sector allowed, NHMS provides all the necessary base data to private sector as open data and is NOT commercially active (e.g. USA);

The research was undertaken independently by Prof. Dr. Christian Gruninger-Hermann of Baden-Wuerttemberg Cooperative State University Loerrach. Prof Gruninger-Hermann is a specialist in the fields of digital transformation and business models, Ecommerce, trade management and market research.

PRIMET is a pan European Trade Association for meteorological service providers operating in the private sector. It aims to promote a fair trading environment between the public and private sector in meteorology and its related disciplines. 

How to cite: Eccleston, A., Gutbrod, K., Gruninger-Hermann, C., and Schulze, D.: EU Weather markets: a EU-28 perspective from 2010 to 2020 and beyond, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-551, https://doi.org/10.5194/ems2022-551, 2022.

Online presentation
Isla Finney

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.

Onsite presentation
Christoph Ramshorn, Mathias D. Müller, and Karl G. Gutbrod

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.

Online presentation
Dana Castellano, Matthew Dib, Jeremy DeMoss, Matt Nuss, Darrell Converse, and Adam Bakke

For the past 50+ years, Fleetweather has provided ship routing and marine forecasting services to ship owners, charterers, and vessel crews across the globe. Over time as meteorological and oceanographic data has become more abundant and accessible, Fleetweather has evolved and improved their methods and products to enhance the value of the services delivered to clients.

Our group of approximately thirty Marine Routers utilise and interpret a variety of data from numerous sources and agencies, including marine observations, meteorological and oceanographic forecast model output, satellite and radar data, tropical warnings, and marine ice data. This data, in combination with expertise in ship performance characteristics, marine navigation, maritime threats such as piracy, and environmental regulations, allows our routers to provide optimal route recommendations to vessels in every ocean basin. The safety of crew and cargo is always the number one priority, but many other considerations factor into recommendations, such as minimising fuel consumption, voyage distance, or voyage time.

Additionally, historical data is analysed to both examine the past performance and predict future performance for vessels and fleets. As more data becomes accessible, more precise analysis and prediction results, to the benefit of all parties involved.

Given the plethora of data available to the public, proper and clear communication of what the data actually means is vital to the end user, and conveying this information as accurately and concisely as possible is key to maximising the value to the client. Expertise in meteorology and oceanography is a requirement, but equally important is having a strong understanding of the concerns and priorities of those in the maritime industry, and the ability to communicate the same is a crucial part of the services Fleetweather provides. 

Fleetweather is positioned to take the available high-value datasets, applying our knowledge and expertise, and then delivering a high value product at the end of the value-chain.  This end product/deliverable is of high value to our clients in the maritime industry, and also provides societal benefits to the population at large, through reduction of fuel consumption and increased vessel efficiency, leading to a contribution to reducing global greenhouse gas emissions worldwide.

How to cite: Castellano, D., Dib, M., DeMoss, J., Nuss, M., Converse, D., and Bakke, A.: Interpreting Meteorological and Oceanographic Data to Provide Optimal and Safe Ship Routing, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-318, https://doi.org/10.5194/ems2022-318, 2022.

Onsite presentation
Rainer Kaltenberger

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.

Display time: Thu, 8 Sep 08:00–Fri, 9 Sep 14:00

Posters: Thu, 8 Sep, 14:00–15:30 | b-IT poster area

Chairpersons: Andrew Eccleston, Willie McCairns
Onsite presentation
Jelmer Jeuring and Anders Sivle

Risk management for wind farms has become more standardized in terms of calculating acceptable risk criteria, but so far the communication of possible risks and their consequences for societal actors has not evolved into a validated set of best practices. The current state of knowledge about best practices for ice throw/fall risk communication is still in an exploratory phase, and empirical research on this is fragmented. The main attempt toward a consolidation of best practices in ice throw/fall risk communication has been part of the IEA Wind TCP Task 19 work. Its mandate is to provide international guidelines for ice risk assessment. A report that was published in 2018 (Krenn et al., 2018) is currently being updated. The work reported in this presentation is part of the project ‘Wind Energy in Icing Climates’, funded by the Norwegian Research Council and wind farm operators in Norway. The Norwegian Meteorological Institute has executed a national survey with the specific aim to develop recommendations for communication of the risk of ice throw from turbines in Norwegian wind farms. The survey aimed at getting insight into perceptions of the general public in Norway about ice-throw risk, and the perceived value of different communication tools and formats of ice-throw risk information for Norwegian wind farms. We discuss findings on a range of topics, including people’s familiarity with wind turbine parks, their weather risk information seeking patterns, people’s understanding of impact-based warnings for ice-throw risk, and their behavioural capacity to mitigate possible negative impacts emerging from ice throw risks. Based on the survey findings, we provide a systematic set of recommendations regarding communication and formatting of ice throw risk warning information.

How to cite: Jeuring, J. and Sivle, A.: Perceptions of impact-based warning information for ice-throw risk: A Norwegian survey, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-153, https://doi.org/10.5194/ems2022-153, 2022.

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