Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

EUMETNET Nowcasting Programme

View through CrossRef
One major task of the National Meteorological and Hydrological Services (NMHS) is the provision of consistent and integrated forecasting products from minutes to several days ahead (seamless forecasting). The former EUMETNET (European Meteorological Services’ Network) project ASIST (Application oriented analysis and very short-range forecast environment) which started in 2015 focused on the nowcasting and very short range forecasting. Then, it was extended to the EUMETNET Nowcasting Programme (E-NWC) which started in 2019 and will last until the end of 2023 with focus on nowcasting and also on seamless prediction. In this presentation, the main objectives of the E-NWC Programme will be introduced. E-NWC supports NMHS in sharing expertise, experiences and best practices for developing and implementing nowcasting, very short-range forecasting and seamless prediction systems. Key activities lie in the exchange of information and experiences with the users during e.g. the every two years European Nowcasting Conference and the strong cooperation with the World Meteorological Organization (WMO) and EUMETSAT, and in summarizing the relevant findings in project reports and joint peer-reviewed papers. Highlights of this contribution comprehend a few results from studies and surveys carried out recently.
Title: EUMETNET Nowcasting Programme
Description:
One major task of the National Meteorological and Hydrological Services (NMHS) is the provision of consistent and integrated forecasting products from minutes to several days ahead (seamless forecasting).
The former EUMETNET (European Meteorological Services’ Network) project ASIST (Application oriented analysis and very short-range forecast environment) which started in 2015 focused on the nowcasting and very short range forecasting.
Then, it was extended to the EUMETNET Nowcasting Programme (E-NWC) which started in 2019 and will last until the end of 2023 with focus on nowcasting and also on seamless prediction.
In this presentation, the main objectives of the E-NWC Programme will be introduced.
E-NWC supports NMHS in sharing expertise, experiences and best practices for developing and implementing nowcasting, very short-range forecasting and seamless prediction systems.
Key activities lie in the exchange of information and experiences with the users during e.
g.
the every two years European Nowcasting Conference and the strong cooperation with the World Meteorological Organization (WMO) and EUMETSAT, and in summarizing the relevant findings in project reports and joint peer-reviewed papers.
Highlights of this contribution comprehend a few results from studies and surveys carried out recently.

Related Results

Towards a data-driven nowcasting of severe weather based on geostationary satellite data
Towards a data-driven nowcasting of severe weather based on geostationary satellite data
<p>Nowcasting severe weather is crucial not only to mitigate the effects of extreme weather events like storms and flash floods but also to support decision-makers on...
Skillful deep learning-based precipitation nowcasting based on new AI-synthetic radar data
Skillful deep learning-based precipitation nowcasting based on new AI-synthetic radar data
Accurate and timely rainfall nowcasting is important for protecting the public from heavy rainfall-induced disasters. In recent years, deep-learning models have been demonstrated t...
Precipitation Nowcasting using Data-driven Reduced-order Model
Precipitation Nowcasting using Data-driven Reduced-order Model
Radar-based precipitation nowcasting refers to predicting rain for a short period of time using radar reflectivity images. For dynamic nowcasting, motion fields can be extrapolated...
Precipitation Nowcasting using Data-driven Reduced-order Model
Precipitation Nowcasting using Data-driven Reduced-order Model
<div>Radar-based precipitation nowcasting refers to predicting rain for a short period of time using radar reflectivity images. For dynamic nowcasting, motion fields can be e...
Quantifying the analysis uncertainty for nowcasting application
Quantifying the analysis uncertainty for nowcasting application
Abstract. This study proposes a method to quantify the uncertainty of the error in the very high–resolution analysis in near–surface level for nowcasting application. We perturbed ...
Machine learning analysis and nowcasting of marine fog visibility using FATIMA Grand Banks campaign measurements
Machine learning analysis and nowcasting of marine fog visibility using FATIMA Grand Banks campaign measurements
Introduction: This study presents the application of machine learning (ML) to evaluate marine fog visibility conditions and nowcasting of visibility based on the FATIMA (Fog and tu...
Deep learning-based precipitation nowcasting integrating radar echoes and rain gauge data
Deep learning-based precipitation nowcasting integrating radar echoes and rain gauge data
For flood protection and disaster mitigation, reliable and accurate short-term heavy rainfall forecasts are essential. However, precipitation nowcasting is a very difficult task du...
An exploration into students' perceptions regarding dropout within the chiropractic programme at a University of Technology
An exploration into students' perceptions regarding dropout within the chiropractic programme at a University of Technology
Introduction: Chiropractic is a health profession specialising in the diagnosis, treatment and prevention of disorders affecting the bones, joints, muscles and nerves in the body. ...

Back to Top