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Multi-Hazard Warning

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9 March 2025

Why do we need standardised multi-hazard early warning systems?

Standardised multi-hazard early warning systems (MHEWS) are essential in meteorology for several critical reasons. These systems provide a coordinated and efficient approach to addressing multiple hazards, which is crucial in a world where climate-related disasters are increasing in frequency and intensity.

MHEWS enable timely and accurate warnings for various weather-related threats, allowing individuals, communities, governments, and businesses to take appropriate action to reduce disaster risks. 

By integrating data from diverse sources and leveraging advanced technologies, including artificial intelligence, MHEWS offer more precise and comprehensive risk assessments. This standardised approach enhances the efficiency and consistency of warnings across different hazards, improving public safety and reducing economic losses.

Furthermore, MHEWS support a people-centred approach to disaster risk reduction, empowering vulnerable populations and promoting more effective disaster preparedness and response strategies. 

As climate change continues to exacerbate weather-related risks, standardised MHEWS become increasingly vital for adapting to and mitigating the impacts of extreme weather events on a global scale. 

How does EUMETNET contribute to standardised MHEWS?

The EUMETNET European Multiservice Meteorological Awareness (EMMA) Programme and the accompanying dissemination system for multi-hazard early warnings, called “MeteoAlarm”, represent one of the most visible achievements of EUMETNET.
In recent years, EMMA has significantly contributed to enhancing MHEWS by developing standards and fostering close cooperation among participating National Meteorological Services (NMSs). 

EMMA’s primary objective is to provide the public with multilingual awareness information from participating NMSs through MeteoAlarm, enhancing preparedness by using an easily understandable colour code and offering impact scenarios and advisories. EMMA emphasises impact-oriented warnings and the harmonisation of warnings among the NMSs. 

Furthermore, MeteoAlarm aggregates and accessibly provides warnings through the MeteoAlarm Feeds, facilitating the dissemination of awareness information of NMSs through national and international redistributors, further empowering individuals to take early action. 

Who’s leading this EUMETNET activity?

The EMMA Programme is led by the National Meteorological Service (NMS) of Austria (GeoSphere Austria).

Programme Manager: Johannes Fleisch (GeoSphere Austria)  
Email address: johannes.fleisch[at]eumetnet.eu  
Email address for support queries: meteoalarm[at]geosphere.at

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MeteoAlarm Website

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MeteoAlarm Feeds

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MeteoAlarm APIs

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Early Warnings for All

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Short-Range NWP

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Why do we need Short-Range Numerical Weather Prediction?

Short-range numerical weather prediction (SRNWP) systems are crucial for providing accurate and timely forecasts that are essential for public safety, economic planning, and resource management. These systems excel at predicting weather conditions from a few hours to a few days ahead, offering a level of precision that is vital for issuing warnings about severe weather events, optimising energy distribution, and supporting industries such as agriculture and transportation. In the context of climate change, where extreme weather events are becoming more frequent, SRNWP systems play an increasingly important role in community preparedness and response. They are also cost-effective, leveraging advanced data assimilation techniques to incorporate diverse observational data, including satellite information, which is particularly valuable in regions with limited ground-based weather stations. By enabling more informed decision-making across various sectors, SRNWP systems contribute significantly to public safety, economic efficiency, and adaptive strategies in the face of changing climate patterns. 

How does EUMETNET contribute to the coordination of Short-Range NWP?

EUMETNET’s Coordination on Short-Range Numerical Weather Prediction (C-SRNWP) module facilitates communication between the European National Meteorological Services (NMSs) and modelling consortia involved in short-range numeric weather prediction (SRNWP). It aims to coordinate and harmonise their activities and development plans for mutual benefit, ensuring efficient investment of resources and exchange of information regarding scientific, technical, and operational aspects of SRNWP. It also focuses on the challenges of developing next-generation forecasting systems – very high spatial resolution modelling, including Digital Twins of the European Commission’s Destination Earth initiative, as well as Artificial Intelligence/Machine Learning-based methods that promote a beneficial interaction with traditional numerical weather prediction (NWP) approaches. Additionally, the C-SRNWP module addresses the representation of forecast uncertainties through ensemble methods in collaboration with the SRNWP-EPS module. 
One of the main activities in the C-SRNWP module is the organisation of the annual EWGLAM/SRNWP (European Working Group on Limited Area Modelling / Short Range Numerical Weather Prediction) meeting. At these meetings, the scientists exchange recent results, achievements and plans to improve their understanding and establish collaboration in SRNWP. The C-SRNWP website contains all the relevant information and presentations of the meetings.

Who’s leading this EUMETNET activity?

The C-SRNWP module is coordinated by the National Meteorological Service of Germany (DWD). 
Module manager: Christoph Schraff (DWD)
Email address: Christoph.Schraff[at]dwd.de

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Ensemble Prediction Systems (EPS)

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Why are Ensemble Prediction Systems (EPS) important?

Ensemble Prediction Systems (EPS) are crucial in modern meteorology for their ability to quantify uncertainty and improve forecast accuracy. By running multiple simulations with slightly varied initial conditions, EPS account for the chaotic nature of the atmosphere, providing a range of possible weather outcomes. This approach not only enhances the overall accuracy of predictions, especially for medium to long-range forecasts, but also allows meteorologists to estimate the likelihood of specific weather events. EPS are particularly valuable for extending forecast usefulness, calculating probabilities for various weather conditions, and adapting predictions to specific applications like renewable energy or aviation. The ensemble mean often outperforms single deterministic forecasts, especially beyond a few days, making EPS indispensable for risk assessment and decision-making across various sectors. By offering a more comprehensive view of potential weather scenarios and their associated probabilities, EPS significantly enhance the value and actionability of weather forecasts. This capability supports better decision-making in diverse fields and contributes to improved public safety, making EPS an essential tool in contemporary weather prediction and climate analysis. 

How does EUMETNET contribute to the Ensemble Prediction Systems (EPS)?

EUMETNET’s Short-Range Numerical Weather Prediction Ensemble Systems (SRNWP-EPS) module aims to develop, enhance, and promote the use of high-resolution ensemble systems in Europe. These systems are designed to resolve convection-permitting scale phenomena, enabling the capture of small-scale weather events such as individual thunderstorms. 

A key objective of the SRNWP-EPS module is to improve the prediction of high-impact weather events by advancing convection-permitting Limited Area Model Ensemble Prediction System (LAM-EPS) capabilities across Europe. This goal is pursued through coordinated efforts of Expert Teams (ETs) focusing on critical LAM-EPS research challenges, including the refinement of model uncertainty representations through perturbation testing. 

The module’s scope encompasses the development of new products and methodologies for LAM-EPS calibration. It puts a particular emphasis on extreme weather events. It also aims to create probabilistic predictions for specific phenomena such as thunderstorms and fog. Furthermore, the module investigates the sensitivity of LAM-EPS to soil conditions and planetary boundary layer effects  and their influence on weather event forecasting.

By fostering collaboration and shared research initiatives, the SRNWP-EPS module significantly contributes to the advancement of high-resolution ensemble forecasting capabilities across Europe. This collaborative approach ultimately leads to more accurate and reliable weather predictions, enhancing the overall quality of meteorological services. 

Who’s leading this EUMETNET activity?

The SRNWP-EPS module is led by the National Meteorological Service (NMS) of Germany (DWD), supported by the NMSs of Spain (AEMET) and Italy (ItAF-AVIAMM).

Module manager: TBD (DWD)

Co-manager: Alfons Callado Pallares (AEMET) 
Email address: Alfons.Callado[at]aemet.es

Co-manager: Francesca Marcucci (ItAF-AVIAMM) 
Email address: francesca.marcucci[at]eumetnet.eu 

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Post-Processing

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Why do we need Post-Processing in meteorology?

Post-processing plays an important role in meteorology by significantly improving the accuracy, reliability, and usability of weather forecasts. These techniques are essential for reducing systematic biases and errors inherent in numerical weather prediction (NWP) models, transforming raw model outputs into more precise and actionable weather information. By quantifying forecast uncertainty and refining predictions, post-processing enables meteorologists to provide more reliable and locally relevant forecasts that better match observed weather patterns. The method is particularly valuable in extending the useful lead time of forecasts, especially for extreme weather events, and in adapting predictions to specific applications such as renewable energy, aviation, and agriculture. Post-processing techniques integrate multiple data sources, compensate for model limitations, and help address challenges related to resolution and parameterisation. This approach allows meteorological services to transform complex model outputs into more understandable and practical information for end users. As weather prediction technologies continue to advance, post-processing remains a critical tool in bridging the gap between complex computational models and the practical need for accurate, localised, and actionable weather forecasts. 

How does EUMETNET contribute to Post-Processing?

National Meteorological Services (NMSs) aim to provide users with consistent and reliable forecasts, but while each NMS has some resources to support developments in post-processing, they lack sufficient capacity to undertake all these activities independently. Combining the expertise and knowledge of the different organisations within EUMETNET benefits all members.  
The EUMETNET Post-Processing module addresses three main goals: identifying best practices, demonstrating the benefits, and developing new methods and tools for post-processing. 
Statistical post-processing involves improving weather forecasts by comparing past forecasts with actual observations. To foster collaborations on this topic, the Post-Processing module organises workshops for scientists from participating NMSs.  
 
Furthermore, the post-processing module, together with experts, coordinates a comparison of different post-processing methods in close collaboration with other EUMETNET activities in the area of short-range numerical weather prediction. The topics covered by the Post-Processing module are post-processing of deterministic and ensemble numerical weather predictions with an emphasis on extreme events, post-processing based on analogues, and the application of innovative methods for post-processing (e.g. deep learning), etc. 

Who’s leading this EUMETNET activity?

The Post-Processing module is led by the National Meteorological Service (NMS) of Belgium (RMI).

Module Manager: Stéphane Vannitsem (RMI)  
Email address: stephane.vannitsem[at]eumetnet.eu

Principal investigator: Jonathan Demaeyer  (RMI) 
Email address: Jonathan.Demaeyer[at]eumetnet.eu

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Post-Processing Benchmark

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Benchmark Datasets

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Publications

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Climate

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Why do we need climate coordination?

Collaboration in the field of climate across Europe is critical for addressing the complex, transboundary challenges posed by climate change. Effective cooperation enables European National Meteorological Services (NMSs) to align their strategies, share knowledge and resources, and implement cohesive policies that can achieve greater impact than isolated national efforts. By working in concert, European organisations can leverage their collective expertise, negotiate more effectively on the global stage, and drive forward ambitious climate targets. Moreover, unified action helps to prevent policy fragmentation, reduces inefficiencies, and ensures a more equitable distribution of both the burdens and benefits of climate mitigation and adaptation measures. Ultimately, a well-synchronised European approach to climate change is essential for fostering innovation, accelerating the transition to a low-carbon economy, and building climate resilience across the continent. 

How does EUMETNET contribute to climate coordination?

The EUMETNET Climate programme provides a collaborative framework for EUMETNET members to engage and exchange within the field of climate. Its primary goal is to facilitate diverse opportunities for cooperation and information sharing among EUMETNET members, with European organisations dealing with climate services, and with the scientific community.

The Climate programme organises regular meetings to share best practices, discuss needs, and explore opportunities for collaboration regarding climate services. These meetings foster the exchange of information among the EUMETNET members and cooperation with European organisations dealing with climate services. Additionally, EUMETNET organises workshops and supports climate-related conferences to facilitate interaction with a wider scientific community. The Climate programme also facilitates the exchange of climate-related data within Europe, including historical weather and phenological observations.  

Who’s leading this EUMETNET activity?

The Climate programme is led by the National Meteorological Service (NMS) of Austria (GeoSphere Austria) supported by the NMS of Hungary (HungaroMet). 

Programme manager: Barbara Chimani (GeoSphere Austria)
Support team: Monika Lakatos (HungaroMet) 
Email address: barbara.chimani[at]eumetnet.eu  

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Pan-European Phenological Database (PEP725)

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Nowcasting

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6 March 2025

Why nowcasting is important?

Nowcasting refers to predicting weather conditions in the very short term, typically within the next few hours. It represents the first component of so-called seamless forecasting, which links forecasts with different lead times from minutes to several days.
 
Nowcasting plays a vital role in meteorology by providing crucial short-term weather predictions that are essential for public safety, economic efficiency, and effective risk management. This technique offers highly accurate and localised predictions that are invaluable for issuing timely warnings about imminent severe weather events such as storms, flash floods, and extreme precipitation. Nowcasting’s importance extends to various sectors of the economy, including agriculture, transportation, energy management, and outdoor event planning, where immediate weather information can significantly impact operations and decision-making. As climate change increases the frequency and intensity of extreme weather events, nowcasting becomes even more critical for community preparedness and response. It is particularly valuable in specialised applications such as aviation, marine safety, and resource management. Recent technological advancements, including improved data collection methods, artificial intelligence, and communication technologies, have greatly enhanced nowcasting capabilities, making it an indispensable tool in modern meteorology. By bridging the gap between current observations and longer-term forecasts, nowcasting provides the detailed, location-specific predictions necessary for adapting to rapidly changing weather conditions and mitigating potential risks. 

How does EUMETNET contribute to coordination on nowcasting ?

The EUMETNET Nowcasting module (E-NWC) facilitates the exchange of experiences in user applications related to nowcasting and seamless prediction systems. It further aims to demonstrate the benefits of extensive data exchange between National Meteorological and Hydrological Services (NMHS) and provide guidelines for developing nowcasting and seamless prediction systems.
The E-NWC module promotes cooperation in nowcasting and seamless forecasting by facilitating joint projects, organising short-term scientific missions and conferences (such as the European Nowcasting and Weather Forecasting Conference), and working closely with related EUMETNET programmes and modules. In addition, it coordinates training sessions focused on nowcasting and seamless forecasting and liaises with the World Meteorological Organization (WMO) Programmes involved in similar topics. 

Who’s leading this EUMETNET activity?

The E-NWC module is led by the National Meteorological Service (NMS) of Austria (GeoSphere Austria).

Module Manager: Franziska Schmid (GeoSphere Austria) 
Email address: franziska.schmid[at]eumetnet.eu

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European Nowcasting Conferences (ENC)

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Cooperation with WMO

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Publications

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In the RODEO Project, new Application Programming Interfaces (APIs) are being developed for MeteoAlarm. These APIs enable access to multi-hazard early warnings through cross-border queries and bulk downloads for archived warnings. The goal is to improve the sharing and accessibility of warnings by integrating these capabilities into MeteoAlarm, including Near-Real-Time, Archived Warning, and Storm Name APIs. 

The CBCF is a collaborative forecast that provides EUROCONTROL’s Network Manager (NM), participating Air Navigation Service Providers (ANSPs), and other aviation stakeholders with strategic planning information about convective weather across European airspace. NM and the attached ATM-units use this information to coordinate with impacted Air Traffic Control Centres (ACCs) across Europe to minimise flight delays and improve aviation safety. The EUMETNET CBCF module comprises:

- the operational framework to produce a collaborative weather chart 
- the organisational environment enabling the production and development of the forecast service in line with users’ requirements  
- the designation of roles, responsibilities and interfaces amongst all stakeholders

CBCF participating MET ANSPs

CBCF domain in 2025

The eGAFOR forecast (eGAFOR Viewer) supports private pilots in central and south-eastern Europe with a uniform, harmonised, probabilistic, graphical, colour-coded Low-Level Forecast (LLF) for flights following visual flight rules. The service includes the assessment of the impact of the meteorological phenomena on flight routes.

The MET ANSPs participating in eGAFOR are:

- ARSO (Slovenia) 
- BHANSA (Bosnia and Herzegovina) 
- CCL (Croatia) 
- HungaroMet (Hungary) 
- ROMATSA (Romania) 
- SHMÚ (Slovakia) 
- SMATSA (Serbia and Montenegro) 
- BULATSA (Bulgaria) 

EUROCONTROL’s Network Manager (NM) is designated by Single European Sky (SES) legislation to manage the European airspace, linking together the elements of the European Air Traffic Management (ATM) system. Focusing on the performance of the European network, NM ensures that flights reach their destination safely, on time, with the least possible impact on the environment, and in a cost-efficient manner.

EUMETNET regularly liaises with the Network Manager on a wide range of aviation meteorological topics, with the long-term goal of delivering a consistent network view of the weather conditions affecting the network at airport, regional and continental scales. This work requires proactive coordination between the European MET ANSPs and collaborative efforts with EUROCONTROL and the European Union Aviation Safety Agency (EASA) to work towards the vision of a better-connected Europe under the SES. 

The E-AI programme will enhance the value of earth observations, gridded observational datasets, model fields and further datasets by making them AI-ready. The goal is to define and prepare a collection of datasets and develop appropriate interfaces and tools to make these data easily available for development, retraining, and operational use of AI/ML methods. Image sources: ESA (European Space Agency), EUMETSAT, DWD, Reinhardt et al. (https://doi.org/10.1175/AIES-D-22-0025.1) published under CC BY-SA 3.0 IGO

The SESAR (Single European Sky ATM Research) programme is one of the most ambitious research and development projects that the European Union has launched. The programme is the technological and operational dimension of the Single European Sky (SES) initiative to meet future capacity and air safety needs. Coordination on cross-border digital services is a key component of the SESAR programme, and meteorology is a key factor in enabling System Wide Information Management (SWIM) services to be delivered to all aviation stakeholders. 
EUMETNET supports the deployment of new pan-European harmonised SWIM products. You can register and gain access to these new MET SWIM Services via the SWIM Registry. In addition, EUMETNET and the ASP are helping participating MET ANSPs comply with the Common Project Regulation, which mandates the development and issuance of SWIM services. 

Why do we need a phenological database?  
Phenology – the timing of natural events in the life cycles of animals and plants – is perhaps the simplest process to track changes in the ecology of species in response to climate change (IPCC 2007). In most European countries, different governmental and non-governmental organisations have routinely carried out phenological observations for more than 50 years following different observation guidelines. Having the phenological data spread over many network operators made access difficult and hampered large-scale studies.
 
How does it work? 
The main objective of EUMETNET’s phenology network (PEP725) is to build and maintain a European-wide phenological database with open, unrestricted data access for science, research and education. So far, 27 European meteorological services and seven partners from different phenological network operators have joined PEP725. Open data access advertises the PEP725 dataset for the climate impact community and encourages scientific work based on it.

The PEP725 database is regularly updated with new data provided by EUMETNET members and their partners. The National Meteorological Service of Austria (GeoSphere Austria) manages the PEP725 database, which is freely available for education and research. Downloads and requests for data, as well as the number of peer-reviewed publications based on the PEP725 dataset, have been increasing steadily.  
Phenological data may be downloaded directly from the PEP725 home page (www.pep725.eu).

Who’s in charge? 
The PEP725 database is maintained and developed by the NMS of Austria (GeoSphere Austria).

PEP725 Module Manager: Hans Ressl (GeoSphere Austria) 
Email address: hans.ressl[at]geosphere.at  

MeteoGate Community components are needed to deliver shared capabilities, e.g. a data catalogue or access management. They will be established and operated by EUMETNET or its members and useable by data publishers and consumers inside and outside the hydro-meteorological community. 

1- A shared Data Catalogue defining and describing data assets and data collections, indexed, linked, and searchable to support data discovery and usage.

2- A Message Broker with a subscription service for notifications about the updates to both discovery metadata and the data.

3- Identity & Access management to control user and system access to platforms and platform services.

4- API management providing the interface between data consumers and underlying data stores, enabling managed access and usage of data and data products.

5- An Insights service reporting on data discovery and publication transactions for Data Publishers to derive management information.  

1- MeteoGate will enable the sharing of hydrological and meteorological data holdings both within the European Meteorological Infrastructure (EMI) and between the EMI and external stakeholders (global WMO community, public and private sector bodies, research institutions, citizens, etc.). The MeteoGate System will be part of the WMO Information System and will implement the WIS 2.0 principles.

2- The initial scope of MeteoGate includes sharing the following categories of data: Core Data (WMO Unified Data Policy), Meteorological High-Value Data (EU Regulation 2019/1024), and Data for Official Duty1. The MeteoGate System will be extensible so that additional functions can be incorporated as user requirements emerge.

3- MeteoGate will enable data sharing in a manner that is compliant with national and international legislation, regulation, and policy commonly applicable to the EMI, with priority given to obligatory requirements.

4- MeteoGate will support the data-sharing policies commonly used within the EMI, including but not limited to free and open data exchange. 

5- MeteoGate will neither affect ownership of shared data holdings nor impose additional conditions on data sharing.

6- The ownership, origin and license / usage terms of data holdings shared via MeteoGate will be visible to all stakeholders.

7- Policies and technical standards ensuring interoperability and consistency of operation among components of the MeteoGate will be mutually agreed and maintained by European NMHSs, EUMETSAT and ECMWF under the auspices of EUMETNET.

8- MeteoGate will be comprised of multiple components (e.g. data sharing platforms and systems), each owned and operated by constituents of the EMI and conforming with the mutually agreed policies and technical standards. Providers of MeteoGate components are encouraged to develop and/or operate them in a manner that supports the community. MeteoGate components may form part of national data-sharing infrastructures and vice versa.

9- MeteoGate will build upon existing data-sharing infrastructures, incorporating them when they conform to the mutually agreed policies and standards. MeteoGate will undergo continuous development as needs arise in the EMI.

10- MeteoGate will provide access to data holdings in-situ where local capability exists to do so. Moving data to a remote system only to support data sharing should be avoided.

11- MeteoGate will have a single catalogue describing all its data holdings and will provide mechanisms to enable users to search for the data they need. MeteoGate will make metadata contribution to the catalogue easy; aiming to avoid duplicate effort where data providers contribute to multiple data sharing initiatives. 

First meteorological data from aircrafts were taken in the early beginning of aircraft era. Following development of the concept for transmitting aircraft temperature and wind information to the ground in real-time by the Australian Bureau of Meteorology in the 1980’s, Europena National Met Services (NMHS) started developing their own individual AMDAR Programmes with their National carriers. Each NMHS was then responsible for data insertion to the GTS.

Initial airlines and start dates:

KLM (1993)Air France (1995)British Airways (1998)SAS (1998)Lufthansa (1999)

Met Office (UK) developed an automated data processing system to handle its British Airways data and so the opportunity arose to provide a single processing system for all European AMDAR data.

The European operational network was therefore established in June 2009 by the Met Office with 10 National Met Services (EUMETNET Members) agreeing to contribute and this Programme “Pilot Phase” extended to 2002.

The management team The Management team (Operational Service Manager and Technical Co-ordinator) are both full-time employees of the Met Office that reside within the Operations and Services Directorate of the Met Office; within the Observations programme that also provides the necessary administrative support and back-up.

“Early Warnings for All is a groundbreaking initiative to ensure that everyone on Earth is protected from hazardous weather, water, or climate events through life-saving early warning systems by the end of 2027."

The EMMA Programme supports these activities within the WMO Regional Association VI (Europe) by providing life-saving multi-hazard early warnings to the public across 38 European countries, with the potential to extend its capacities to other countries as the initiative progresses. 

The figure below shows the active GNSS stations currently providing data to E-GVap

In E-GVap, we aim to densify the network of GNSS receivers, providing us with valuable ZTD data. Several EUMETNET members run global weather forecasting models; for that reason,  data from outside Europe is also important. 

The MeteoAlarm Feeds provide a thorough summary of active multi-hazard early warnings, aggregated according to each NMS contributing to MeteoAlarm. Subscriptions to Atom and RSS Feeds are easy to access.

Information necessary for redistributing warnings from the contributing NMSs is accessible in the Redistribution Hub on the MeteoAlarm Website. It includes the MeteoAlarm Redistribution Guide, the MeteoAlarm Common Alerting Protocol (CAP) Profile, the Service Level Agreements (SLAs), and other relevant documentation. 

38 European National Meteorological Services contribute to the consistent visualisation of weather awareness information, thereby ensuring coherent interpretation of multi-hazard early warnings throughout Europe. 
Visit the MeteoAlarm Website for the latest weather-related awareness situation and further information. 

Several international meteorological organisations collaborated on a research project examining nowcasting capabilities and Early Warning Systems across different global regions. Working groups from the World Meteorological Organization's World Weather Research Programme and EUMETNET's Nowcasting module led this initiative.

More details can be found here: https://wwrp-nowcastingcapabilities.com/  

Bojinski S, Blaauboer D, Calbet X, de Coning E, Debie F, Montmerle T, Nietosvaara V, Norman K, Banon L, Schmid F, Strelec Mahovic N, Wapler K, 2023: Review: Towards Nowcasting in Europe in 2030, Meteorological Applications, https://doi.org/10.1002/met.2124  
 
Special Issue in Meteorologische Zeitschrift, Development and Application of Seamless Prediction Systems 
Part I: https://www.schweizerbart.de/papers/metz/list/29#issue3
Part II: https://www.schweizerbart.de/papers/metz/list/29#issue4  
 
Sivle A, Agersten S, Schmid F, Simon A, 2022: Use and perception of weather forecast information across Europe, Meteorological Applications, https://doi.org/10.1002/met.2053
 
Schmid F, Wang Y, Harou A, 2019: Nowcasting Guidelines - A summary, WMO Bulletin 68(2), 63-68; https://library.wmo.int/viewer/38575/?offset=#page=3&viewer=picture&o=bookmarks&n=0&q=  
 
WMO in cooperation with E-NWC, 2017: Guidelines for Nowcasting Techniques, WMO Nr. 1198,  
https://library.wmo.int/records/item/55666-guidelines-for-nowcasting-techniques  

Base dataset – Low-resolution gridded data 
The benchmark base dataset is a low-resolution gridded dataset that covers the European area from 36 to 67° in latitude and from -6 to 17° of longitude, with grid spacing of 0.25°x0.25°.

The benchmark dataset consists of 47 fields, with at least seven requiring post-processing. It includes daily forecasts at midnight, which feature ensemble, control, and high-resolution ECMWF runs, as well as reforecasts twice a week and hourly analysis data. The training set covers 2017 and 2018, while the test set is for 2019. The total size of the gridded benchmark is about 6 terabytes (TB), with the training set being 4.3 TB and the test set 1.6 TB. This dataset provides a solid basis for evaluating and comparing different post-processing methods used by National Meteorological Services.

More details about the base dataset can be found at https://eupp-benchmark.github.io/EUPPBench-doc/files/base_datasets.html.

EUPPBench datasets 
In addition to the base dataset, specific datasets for statistical and machine learning over a smaller domain have been designed. The EUPPBench datasets are available over a smaller area within Europe, stored in Zarr format for easy access. The forecasts and observations datasets are already paired together, providing analysis-ready data for post-processing benchmarking purposes. 

The EUPPBench datasets also include station data all over the selected domain and ECMWF forecasts and reforecasts from the nearest grid point.  
With these datasets, the first benchmark of several post-processing methods was conducted and published in Earth System Science Data (ESSD). More details on the EUPPBench datasets and this first benchmark can be found at https://essd.copernicus.org/articles/15/2635/2023/.

An example of deterministic IFS forecast for 100m u wind and the corresponding gridded observations in the EUPPBench dataset.

The benchmark is a key deliverable of the EUMETNET Post-Processing module, designed to provide high-quality benchmark datasets and infrastructures for comparing the various methods used to post-process forecasts in National Meteorological Services.

The benchmark is composed of two components: gridded post-processing, which requires gridded observations, forecasts, and reforecasts; and station-based post-processing, which requires station observations and forecasts and reforecasts at the nearest point.

For more information on the benchmark activities of the PP module, you can visit our website:
https://eupp-benchmark.github.io

Technical details and relevant codes are developed on GitHub:
https://github.com/orgs/EUPP-benchmark 

Between 2019 and 2023, the OPERA data centre (ODYSSEY) was gradually upgraded with three new production lines (CUMULUS/STRATUS, CIRRUS, and NIMBUS).

Figure: The schematic structure of the new OPERA data production. 

The three new production lines are:

• CUMULUS/STRATUS, a real-time data hub providing the incoming data to members in close to real-time for their own processing (e.g. production of regional composites or NWP assimilation) and to the other two production lines (CIRRUS and NIMBUS). This production line has been operational since mid-2021. 
• CIRRUS produces a 5-minute instantaneous maximum reflectivity composite (dBZ) for current weather, severe weather alerts and aviation needs. It replaced the old ODYSSEY maximum reflectivity composite with improved spatial (now with 1 km gridding) and temporal resolution (from 15 minutes to 5 minutes).  The production has been operational since early 2024. Documentation on the CIRRUS maximum reflectivity product and its differences compared to the ODYSSEY maximum reflectivity product can be found here:

–       OPERA_Max Reflectivity_Product Sheet_Ed-2.0.pdf
–       OPERA5_Report_Cirrus-vs-Odyssey_Ed-2.0.pdf

• NIMBUS produces the quality-controlled products centrally: instantaneous rain rate (mm/h) and 1-hour accumulation (mm) composites, wind profiles (expected in late 2025), and the quality-controlled volume data for NWP assimilation. It replaces the old ODYSSEY production for the above-mentioned products. The NIMBUS production has been operational since mid-2024. Documentation regarding the NIMBUS composites and their differences compared to the corresponding ODYSSEY can be found here:

–      NIMBUS_datasheet_composites_1.0_13062024.pdf 
–      NIMBUS_composite_vs_ODYSSEY_1.0_19062024.pdf

OPERA support can be reached by email at support.opera[at]eumetnet.eu. Responses from the service desk are provided on a best-effort basis.

Access to data 
EUMETNET members may use the composites for their official duties without a separate license. Their Numerical Weather Prediction (NWP) modelers obtain the quality-controlled volume data directly from the NIMBUS production line.

The OPERA products are also available under license to Third parties:

- For national meteorological services not participating in the OPERA programme that want to use the products for their official duties, contact info[at]eumetnet.eu
- For a research and education license, contact info[at]eumetnet.eu. 
- For a license to exploit the OPERA products commercially, contact one of the EUMETNET members’ contact points (https://www.ecomet.eu/contact/members) or send an email to the EUMETNET Secretariat using the email address: info[at]eumetnet.eu 

What is E-AMDAR
E-AMDAR is EUMETNETs contribution to the World Meteorological Organization (WMO) Aircraft Meteorological Data Relay (AMDAR) observing system. E-AMDAR facilitates the fully automated collection and transmission of weather observations from commercial aircraft. The E-AMDAR programme is an integrated component of the WMO Global Observing System (GOS) of the World Weather Watch (WWW) Programme . The system is operated by EUMETNET Member NMHS in collaboration and cooperation with partner airlines.

The AMDAR Observing System
The figure below provides a general depiction of the AMDAR system in which onboard sensors, computers and communications systems collect, process, format and transmit the data to ground stations via satellite and VHF radio links. The transmission of this data is most often performed by the aircraft’s ACARS (Aircraft Communications Addressing and Reporting System) system. Once on the ground, the data is then relayed to the global network of national meteorological services and other authorised users.

Currently 14 airlines are participating in E-ABO, more than 1000 planes are equipped for transmitting the meteorological data.

http://www.planespotters.net/Airline/Country

In the Implementing Regulation of the revised Open Data Directive, the European Union has defined a set of High-Value Datasets (HVDs). These are data that have high value for the community. One of the sets defined by the Regulation concerns meteorological data: weather observations, climate time series, warnings, weather radar data and numerical weather prediction (NWP) data.

Following the regulation, these data should be available free of charge, under an open license, in a machine-readable format using Application Programming Interface (API), and bulk downloadable.

Further information on EUMETNET’s response to the High-Value Datasets Regulation can be found under the RODEO page. 

Over the years, the OPERA community has produced an impressive library of documents, recommendations, and definitions. Many of the early technical documents are now more of historical value.

Selected publications of OPERA 6 (2024 -2028) 
ODIM version 2.41 (2024 -for older versions, see software documentation) 
 
Selected publications of OPERA 5 (2019-2023)

- Best practices for calibration and monitoring 25 October 2020 
- ODIM version 2.4 (2021) 
- OPERA-4: On the coexistence of weather radars and wind turbines, 25 February 2022

Selected publications of OPERA 4 (2013-2018)

- OPERA the Radar Project, article in Atmosphere, 12 June 2019 (https://www.mdpi.com/478188) 
- Frequently asked questions about radars, 26 January 2016 
- Best practices for calibration and monitoring 19 January 2019 
- ODIM version 2.3 (9 January 2019) 
- BUFR format and graphical format for polar volume data submitted to and composites produced by the OPERA, version dated 12 March 2012 
- The Operational Weather Radar Network in Europe – article in Bull.Am.Met.Soc. 2014 (https://journals.ametsoc.org/view/journals/bams/95/6/bams-d-12-00216.1.xml) 
- The Threat to Weather Radars by Wireless Technology – article in Bull.Am.Met.Soc. July 2016 (https://journals.ametsoc.org/view/journals/bams/97/7/bams-d-15-00048.1.xml) 
- Maintenance keeps radars running – article in Bull.Am.Met.Soc. 2017 (https://journals.ametsoc.org/view/journals/bams/98/9/bams-d-16-0095.1.xml#:~:text=Most%20radars%20are%20equipped%20with,%2C%20the%20emergency%20power%20generator).
- Quality of the composites – report of a study 
- Monitoring rain rates – report of a study 
- Daily convective precipitation – report of a study 
- Cost-benefit of dual-pol exchange – report of survey in 2016 
- Improvement of rain rates using water phase (snow or rain) – report of a study

Selected Deliverables of OPERA 3 (2007-2012)

- Status of use of polarimetric C and S band radars (2012) 
- Status of use of polarimetric X band radars (2012) 
- Radar site selection and protection (2010) 
- Impact study of radar observations by wind turbines (2010) 
- Statement on wind turbines (2010) 
- Statement of the OPERA group on processing RLAN interferences (2009) 
- Recommendation on coexistence with 5 GHz RLAN (2008) 
- Harmonised production practices for volume data, low-level reflectivity, and wind profiles (2008) 

Meteo-France has developed a set of quality control tools to monitor the status of the E-SurfMar observation networks: https://esurfmar.meteo.fr/qctools/. Primarily based on comparisons of observations with model results, these tools may be used to monitor any surface marine observation platform in the world that reports data onto the GTS.Every month, the performances of the networks in matters of data availability, timeliness, and quality are assessed and compared to previous months and targets. 

Between 2019 and 2023, the OPERA data centre (ODYSSEY) was gradually upgraded with three new production lines (CUMULUS/STRATUS, CIRRUS, and NIMBUS).

Figure: The schematic structure of the new OPERA data production. 

The three new production lines are:

• CUMULUS/STRATUS, a real-time data hub providing the incoming data to members in close to real-time for their own processing (e.g. production of regional composites or NWP assimilation) and to the other two production lines (CIRRUS and NIMBUS). This production line has been operational since mid-2021. 
• CIRRUS produces a 5-minute instantaneous maximum reflectivity composite (dBZ) for current weather, severe weather alerts and aviation needs. It replaced the old ODYSSEY maximum reflectivity composite with improved spatial (now with 1 km gridding) and temporal resolution (from 15 minutes to 5 minutes).  The production has been operational since early 2024. Documentation on the CIRRUS maximum reflectivity product and its differences compared to the ODYSSEY maximum reflectivity product can be found here:

–       OPERA_Max Reflectivity_Product Sheet_Ed-2.0.pdf
–       OPERA5_Report_Cirrus-vs-Odyssey_Ed-2.0.pdf

• NIMBUS produces the quality-controlled products centrally: instantaneous rain rate (mm/h) and 1-hour accumulation (mm) composites, wind profiles (expected in late 2025), and the quality-controlled volume data for NWP assimilation. It replaces the old ODYSSEY production for the above-mentioned products. The NIMBUS production has been operational since mid-2024. Documentation regarding the NIMBUS composites and their differences compared to the corresponding ODYSSEY can be found here:

–      NIMBUS_datasheet_composites_1.0_13062024.pdf 
–      NIMBUS_composite_vs_ODYSSEY_1.0_19062024.pdf

OPERA support can be reached by email at support.opera[at]eumetnet.eu. Responses from the service desk are provided on a best-effort basis.

Access to data 
EUMETNET members may use the composites for their official duties without a separate license. Their Numerical Weather Prediction (NWP) modelers obtain the quality-controlled volume data directly from the NIMBUS production line.

The OPERA products are also available under license to Third parties:

- For national meteorological services not participating in the OPERA programme that want to use the products for their official duties, contact info[at]eumetnet.eu
- For a research and education license, contact info[at]eumetnet.eu. 
- For a license to exploit the OPERA products commercially, contact one of the EUMETNET members’ contact points (https://www.ecomet.eu/contact/members) or send an email to the EUMETNET Secretariat using the email address: info[at]eumetnet.eu 

E-Profile's wind network consists of about 30 radar wind profilers, about 100 weather radars providing wind profiles and new Doppler lidars. All radars send processed vertical wind profile data to E-Profile. According to the operating frequency of the radar, the derived wind profiles cover the atmospheric boundary layer (up to about 3 km), full troposphere (up to about 12 km), or troposphere and lower stratosphere (up to about 20 km). Lidar data are processed centrally using the Doppler lidar toolbox developed by the National Meteorological Service of Germany (DWD). The range of the Doppler lidars depends on the presence of aerosols and is typically limited to the atmospheric boundary layer. 
E-Profile maintains a list of recommended stations for data assimilation into numerical weather prediction models based on the EUCOS (EUMETNET Composite Observing System) monitoring results and considering data quality and timeliness. 
Please contact e-profile[at]meteoswiss.ch to get the current list of the E-Profile stations.


Wind profiler at Lindenberg, Germany. 

Data download (CEDA archive, registration required):  
Wind profiler network

The E-GVap programme exemplifies the synergy between geodesy and meteorology. Through partnerships with geodetic organisations such as EUREF (the Reference Frame Sub-Commission for Europe of the International Association of Geodesy (IAG)), EUPOS (European Position Determination System) , and EPOS (European Plate Observing System), EUMETNET has access to crucial GNSS data.

Geodesists primarily use GNSS receivers for precise positioning and view atmospheric delay—particularly from water vapour—as “noise” to be eliminated. In contrast, meteorologists recognize this "noise" as valuable information about atmospheric water vapour content. Zenith Total Delay (ZTD) estimates provided by geodetic institutions play a key role in improving positioning accuracy. This atmospheric delay, which geodesists seek to remove, contains data that is essential for some meteorological applications.

This collaboration allows both fields to benefit, advancing their respective goals while contributing to a broader understanding of atmospheric processes.

The participating GNSS analysis centres are:

- AUT Aristotle University of Thessaloniki, Greece 
- ASI e-geos/Telespazio, Italy 
- BKG Federal Agency for Cartography and geodesy 
- BMEG Budapest University of Technology and Economics, Hungary 
- CONH UCAR, USA 
- GA01 Geoscience, Australia 
- GFZ Helmholtz Centre Potsdam, GFZ German Research Center for Geosciences 
- GOPE Geodetic Observatory Pecny, Czech Republic 
- IGE Instituto Geografica National, Spain 
- IMO Icelandic Met Office, Iceland 
- KNMI Royal Meteorological Institute of the Netherlands 
- LPT SwissTope, Switzerland 
- METO UK Met Office 
- NGA Lantmateriet (Swedish Mapping, Cadestre and Land Regi. Authority), Sweden 
- ROB Royal Observatory of Belgium 
- SGN Institut Geographique National, France 
- SGOB Satellite Geodetic Observatory, IGCRS + Technical Univ. Budapest, Hungary 
- TUWN Technical University Vienna, Austria 
- UL01 Univ. of Luxembourg, Faculty of Science and Communication, Luxembourg 
- WLIT Lithuania, set up and run by WUEL 
- WTWN Taiwan, set up and run by WUEL 
- WUEL Wroclaw University + Institute of Geodesy and Geoinformatics, Poland 
- WUHN GNSS research Center, Wuhan University, China 

AutoPollen programme participants come from 25 institutes and associations from 22 countries that are either EUMETNET members or cooperating third parties. An extensive list of participants, as well as a list of publications and links to projects and networks across Europe, can be found on the AutoPollen website along with relevant data.

Furthermore, the AutoPollen programme collaborates with several European-level projects and organisations, including: Horizon Europe Project SYLVA (A SYstem for ReaL-Time ObserVation of Aeroallergens), Copernicus Atmospheric Monitoring Services (CAMS), the COST Action ADOPT (New Approaches in Detection of Pathogens and Aeroallergens – CA18226), EURAMET on the BioAirMet project, and Working Group 39 of the European Normalisation Committee (CEN - Technical Committee 264). 

The coverage for the EUMETNET-derived data network from the European Meteorological Aircraft Derived Data Centre for a typical day is shown on the map below. This shows how tens of millions of observations are collected daily, with the highest concentrations indicated by the red colours.

Total Coverage
Number of derived obs in [0.5x0.5]° - 15/01/2025

La couverture du réseau AMDAR d'EUMETNET pour une journée type est illustrée sur la carte ci-dessous. Les tracés jaunes indiquent les observations prises en route, les tracés rouges et verts représentant les profils de montée et de descente des avions. 

Data Publishers such as National Meteorological Services (NMSs) will need to create and operate (potentially in collaboration) several MeteoGate Local components to exploit the system’s benefits. They can choose the level of maturity of the solutions they want to implement – from manual to fully automated. There are collaborative options that allow the reduction of the costs of developing Local components; most of them are needed for NMSs’ obligations towards WMO and its WIS2.0.

- Persistence to store and allow for shared data to be accessed through APIs 
- Data Processing in line with WMO regulations and MeteoGate Policies, Standards and Processes (PSPs) to standardise and productise data so that it can be shared using APIs 
- Local Broker to send change notifications to the WMO Global Broker of news and updates to discovery metadata and shared data  
- Metadata Management to create, publish and maintain the discovery and provenance metadata to share changes with the Global Discovery Catalogue. 
- Data Access to expose data to MeteoGate users using interactive APIs through the API Gateway 

MeteoGate Community components are needed to deliver shared capabilities, e.g. a data catalogue or access management. They will be established and operated by EUMETNET or its members and useable by data publishers and consumers inside and outside the hydro-meteorological community. 

1- A shared Data Catalogue defining and describing data assets and data collections, indexed, linked, and searchable to support data discovery and usage.

2- A Message Broker with a subscription service for notifications about the updates to both discovery metadata and the data.

3- Identity & Access management to control user and system access to platforms and platform services.

4- API management providing the interface between data consumers and underlying data stores, enabling managed access and usage of data and data products.

5- An Insights service reporting on data discovery and publication transactions for Data Publishers to derive management information.  

1- MeteoGate will enable the sharing of hydrological and meteorological data holdings both within the European Meteorological Infrastructure (EMI) and between the EMI and external stakeholders (global WMO community, public and private sector bodies, research institutions, citizens, etc.). The MeteoGate System will be part of the WMO Information System and will implement the WIS 2.0 principles.

2- The initial scope of MeteoGate includes sharing the following categories of data: Core Data (WMO Unified Data Policy), Meteorological High-Value Data (EU Regulation 2019/1024), and Data for Official Duty1. The MeteoGate System will be extensible so that additional functions can be incorporated as user requirements emerge.

3- MeteoGate will enable data sharing in a manner that is compliant with national and international legislation, regulation, and policy commonly applicable to the EMI, with priority given to obligatory requirements.

4- MeteoGate will support the data-sharing policies commonly used within the EMI, including but not limited to free and open data exchange. 

5- MeteoGate will neither affect ownership of shared data holdings nor impose additional conditions on data sharing.

6- The ownership, origin and license / usage terms of data holdings shared via MeteoGate will be visible to all stakeholders.

7- Policies and technical standards ensuring interoperability and consistency of operation among components of the MeteoGate will be mutually agreed and maintained by European NMHSs, EUMETSAT and ECMWF under the auspices of EUMETNET.

8- MeteoGate will be comprised of multiple components (e.g. data sharing platforms and systems), each owned and operated by constituents of the EMI and conforming with the mutually agreed policies and technical standards. Providers of MeteoGate components are encouraged to develop and/or operate them in a manner that supports the community. MeteoGate components may form part of national data-sharing infrastructures and vice versa.

9- MeteoGate will build upon existing data-sharing infrastructures, incorporating them when they conform to the mutually agreed policies and standards. MeteoGate will undergo continuous development as needs arise in the EMI.

10- MeteoGate will provide access to data holdings in-situ where local capability exists to do so. Moving data to a remote system only to support data sharing should be avoided.

11- MeteoGate will have a single catalogue describing all its data holdings and will provide mechanisms to enable users to search for the data they need. MeteoGate will make metadata contribution to the catalogue easy; aiming to avoid duplicate effort where data providers contribute to multiple data sharing initiatives. 

Over the year, the OPERA community has developed several software packages to exchange radar data from different sources and manufacturers.  
Data exchange in OPERA is currently conducted using files in the Hierarchical Data Format version 5 (HDF5), following the internally developed OPERA Data Information Model (ODIM). ODIM has been widely adopted and implemented both within and beyond the OPERA community, and it is continuously updated. 
Software documentation:

- ODIM version 2.41 (2024) 
- ODIM version 2.4 (2021) 
- ODIM version 2.3 (2019)  
- ODIM version 2.2 (2014) 
- ODIM version 2.1
- ODIM version 2.01

Example file of ODIM 2.4: T_PAZA41_C_LPMG_20241205100002.h5.gz 

The E-AI programme is structured in three modules: a) Data Curation, b) Analysis, Modelling and Post-Processing, and c) Products and Services. By working together on overarching Workflows, AI/ML can be used effectively across the entire value chain while also addressing necessary technical, administrative, and structural requirements. Moreover, the programme offers Communication and Training opportunities to ensure an efficient flow of information on AI/ML developments within and beyond the E-AI programme.

  

Voluntary Observing Ships (VOS) are a vital part of the global weather observation system, providing essential meteorological and oceanographic observations at sea. Weather stations managed by National Meteorological Services and installed on board VOS  typically record and transmit data on surface wind speed and direction, air temperature, humidity, sea surface temperature (SST), atmospheric sea level pressure (SLP), cloud characteristics, visibility, wave and swell parameters, and overall present weather status. The VOS data are crucial for real-time weather forecasting and historical climate studies, especially in data-sparse regions like the Arctic. They contribute significantly to our understanding of atmosphere-ocean interactions, which is essential for addressing global warming and improving long-range weather forecasts.

There are two main types of VOS: conventional VOS, where sailors make observations and record data in meteorological logbooks, and VOS with automated systems that use electronic logbooks for streamlined reporting.

The NMS of the Netherlands (KNMI) has developed the Turbowin software package to enhance data acquisition, quality and quantity from conventional VOS.

Turbowin+ software

 
The number of VOS with automated weather stations (AWS) has increased, resulting in more frequent marine observations, usually with hourly transmissions. In 2024, more than 265 operational AWS units have reported data on the Global Telecommunication System (GTS) from ships recruited by several NMSs. A common AWS, called EUCAWS, was developed in 2017 under E-SurfMar and has been installed by national meteorological services on several VOS since then.  
In 2022-2023, E-SurfMar developed a new mini automatic weather station for installation on board vessels. This mini station offers a wide range of possibilities for connecting sensors and sending messages. Power consumption is low, installation is easy, and its cost is low. This station is now operational and about ten have already been installed on European vessels.

Moored buoys are anchored at fixed locations and regularly collect observations from various atmospheric and oceanographic sensors. These buoys measure a wide range of parameters crucial for operational applications, including both meteorological and oceanographic data. The meteorological parameters typically measured by moored buoys are air temperature, humidity, atmospheric pressure, and wind speed and direction. Oceanographic measurements generally include sea surface temperature and, in some cases, ocean currents and salinity. Sea state (the general condition of the ocean surface with respect to wind waves and swell at a specific location and time), is also of significant interest for many applications.

Wave parameters are measured by tracking the buoy's displacement, assuming it responds to waves without affecting the measurement. Modern moored buoys transmit wave parameters and spectral data through the Global Telecommunication System (GTS). The quality of the data from these buoys is considered amongst the finest available from surface marine stations. These measurements are vital for weather forecasting, maritime safety and scientific research, whilst also serving as crucial reference points for calibrating and verifying satellite measurements and numerical atmospheric and ocean models. Moored buoys can be fitted with additional sensors to meet specific research or operational requirements. Some are capable of measuring parameters throughout the water column, which is the vertical section of water from surface to seabed. This provides valuable data on subsurface conditions at various depths, offering a comprehensive view of oceanic processes from top to bottom. 

More than 150 E-SurfMar drifting buoys are permanently operating in the EUMETNET Composite Observing System (EUCOS) area. E-SurfMar relies on partner institutions in The Netherlands, Portugal, UK, France, Italy, Germany, Canada and the United States to deploy and maintain the drifting buoy network.

Deployments are carried out using various vessels, including container ships, expedition sailboats, and racing yachts. Our goal is to optimise our networks for consistent spatial and temporal coverage. Drifting buoys, designed to track surface currents, have a hemispheric shape and include a holey sock drogue (sea anchor) at a standard depth of 15 metres below the surface. These buoys use GPS to measure their position and transmit surface air pressure and sea surface temperature data in real time via the Iridium satellite communication system. By analysing multiple reports from different positions, we can estimate near-surface ocean currents. The average operational lifespan of a drifting buoy is approximately 600 days. While sea surface temperature (SST) is important, we primarily focus on atmospheric surface pressure, as this parameter cannot be measured by satellites.

A drifting buoy with the drogue (credit Lagrangian drifting laboratory) 

OPERA maintains a database of radar metadata provided by members. It is divided into active radars and archived information (radars no longer part of OPERA).

Public information, location and details of the radars can be found here (Link: https://www.eumetnet.eu/wp-content/themes/aeron-child/observations-programme/current-activities/opera/database/OPERA_Database/index.html). 

Over the years, the OPERA community has produced an impressive library of documents, recommendations, and definitions. Many of the early technical documents are now more of historical value.

Selected publications of OPERA 6 (2024 -2028) 
ODIM version 2.41 (2024 -for older versions, see software documentation) 
 
Selected publications of OPERA 5 (2019-2023)

- Best practices for calibration and monitoring 25 October 2020 
- ODIM version 2.4 (2021) 
- OPERA-4: On the coexistence of weather radars and wind turbines, 25 February 2022

Selected publications of OPERA 4 (2013-2018)

- OPERA the Radar Project, article in Atmosphere, 12 June 2019 (https://www.mdpi.com/478188) 
- Frequently asked questions about radars, 26 January 2016 
- Best practices for calibration and monitoring 19 January 2019 
- ODIM version 2.3 (9 January 2019) 
- BUFR format and graphical format for polar volume data submitted to and composites produced by the OPERA, version dated 12 March 2012 
- The Operational Weather Radar Network in Europe – article in Bull.Am.Met.Soc. 2014 (https://journals.ametsoc.org/view/journals/bams/95/6/bams-d-12-00216.1.xml) 
- The Threat to Weather Radars by Wireless Technology – article in Bull.Am.Met.Soc. July 2016 (https://journals.ametsoc.org/view/journals/bams/97/7/bams-d-15-00048.1.xml) 
- Maintenance keeps radars running – article in Bull.Am.Met.Soc. 2017 (https://journals.ametsoc.org/view/journals/bams/98/9/bams-d-16-0095.1.xml#:~:text=Most%20radars%20are%20equipped%20with,%2C%20the%20emergency%20power%20generator).
- Quality of the composites – report of a study 
- Monitoring rain rates – report of a study 
- Daily convective precipitation – report of a study 
- Cost-benefit of dual-pol exchange – report of survey in 2016 
- Improvement of rain rates using water phase (snow or rain) – report of a study

Selected Deliverables of OPERA 3 (2007-2012)

- Status of use of polarimetric C and S band radars (2012) 
- Status of use of polarimetric X band radars (2012) 
- Radar site selection and protection (2010) 
- Impact study of radar observations by wind turbines (2010) 
- Statement on wind turbines (2010) 
- Statement of the OPERA group on processing RLAN interferences (2009) 
- Recommendation on coexistence with 5 GHz RLAN (2008) 
- Harmonised production practices for volume data, low-level reflectivity, and wind profiles (2008) 

Over the year, the OPERA community has developed several software packages to exchange radar data from different sources and manufacturers.  
Data exchange in OPERA is currently conducted using files in the Hierarchical Data Format version 5 (HDF5), following the internally developed OPERA Data Information Model (ODIM). ODIM has been widely adopted and implemented both within and beyond the OPERA community, and it is continuously updated. 
Software documentation:

- ODIM version 2.41 (2024) 
- ODIM version 2.4 (2021) 
- ODIM version 2.3 (2019)  
- ODIM version 2.2 (2014) 
- ODIM version 2.1
- ODIM version 2.01

Example file of ODIM 2.4: T_PAZA41_C_LPMG_20241205100002.h5.gz 

Between 2019 and 2023, the OPERA data centre (ODYSSEY) was gradually upgraded with three new production lines (CUMULUS/STRATUS, CIRRUS, and NIMBUS).

Figure: The schematic structure of the new OPERA data production. 

The three new production lines are:

• CUMULUS/STRATUS, a real-time data hub providing the incoming data to members in close to real-time for their own processing (e.g. production of regional composites or NWP assimilation) and to the other two production lines (CIRRUS and NIMBUS). This production line has been operational since mid-2021. 
• CIRRUS produces a 5-minute instantaneous maximum reflectivity composite (dBZ) for current weather, severe weather alerts and aviation needs. It replaced the old ODYSSEY maximum reflectivity composite with improved spatial (now with 1 km gridding) and temporal resolution (from 15 minutes to 5 minutes).  The production has been operational since early 2024. Documentation on the CIRRUS maximum reflectivity product and its differences compared to the ODYSSEY maximum reflectivity product can be found here:

–       OPERA_Max Reflectivity_Product Sheet_Ed-2.0.pdf
–       OPERA5_Report_Cirrus-vs-Odyssey_Ed-2.0.pdf

• NIMBUS produces the quality-controlled products centrally: instantaneous rain rate (mm/h) and 1-hour accumulation (mm) composites, wind profiles (expected in late 2025), and the quality-controlled volume data for NWP assimilation. It replaces the old ODYSSEY production for the above-mentioned products. The NIMBUS production has been operational since mid-2024. Documentation regarding the NIMBUS composites and their differences compared to the corresponding ODYSSEY can be found here:

–      NIMBUS_datasheet_composites_1.0_13062024.pdf 
–      NIMBUS_composite_vs_ODYSSEY_1.0_19062024.pdf

OPERA support can be reached by email at support.opera[at]eumetnet.eu. Responses from the service desk are provided on a best-effort basis.

Access to data 
EUMETNET members may use the composites for their official duties without a separate license. Their Numerical Weather Prediction (NWP) modelers obtain the quality-controlled volume data directly from the NIMBUS production line.

The OPERA products are also available under license to Third parties:

- For national meteorological services not participating in the OPERA programme that want to use the products for their official duties, contact info[at]eumetnet.eu
- For a research and education license, contact info[at]eumetnet.eu. 
- For a license to exploit the OPERA products commercially, contact one of the EUMETNET members’ contact points (https://www.ecomet.eu/contact/members) or send an email to the EUMETNET Secretariat using the email address: info[at]eumetnet.eu 

Microwave radiometers are passive instruments that measure the natural radiation from the atmosphere. These radiation measurements are presented as “brightness temperatures” in Kelvin units. We use the TROPOe software suite to convert the brightness temperatures into vertical profiles of temperature and humidity. These profiles typically cover the first 2 km of the atmosphere. Both brightness temperatures and profiles are disseminated via the Global Telecommunication System (GTS). In the future, they will also be disseminated via the WIGOS Information System (WIS).

Microwave radiometers at Payerne, Switzerland. 

The aerosol and cloud network consists of more than 450 automatic lidars (light detection and ranging sensors) and ceilometers. The main purpose of the latter is to measure the height of the cloud base, which is important for planning safe navigation in aviation and understanding atmospheric stability and convection that can result in severe weather or favourable conditions for high-air-pollution episodes. The diverse applicability of ceilometer data explains the high density of the ceilometer network. The automatic lidars and ceilometers are centrally calibrated to create profiles showing how much light is scattered back by particles. That light is related to the size and concentration of particles in the atmosphere. Appropriate calibration techniques enable the estimation of the mass concentration of aerosols and their impact on the radiative transfer in the atmosphere. 
An interactive interface to analyse advanced aerosol properties can be found here: https://vprofiles.met.no/.  
Data download (CEDA archive, registration required):  
Aerosol and cloud profiler network
 

Ceilometer and automatic lidar at Hohenpeissenberg, Germany. 

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