Inhaltsbereich

EMER-Met StArt

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Projektanfang 01.01.2019
Projektende 31.12.2021
Themen Mess- und Prognosesysteme
Region Schweiz
Status Aktuelle Projekte

MeteoSwiss, the Federal Nuclear Safety Inspectorate and the Federal Office for Civil Protection teamed up in an innovative project to upgrade the system for the meteorological surveillance of nuclear power plants to meet highest standards. This includes the extension of the remote sensing network with new wind measurements, the integration of high resolution data into the numerical weather prediction model and the implementation of uncertainty bounds for the dispersion forecasts.

     

The current system is an integrated analysis and forecasting system combining a dedicated measurement network with high resolution numerical weather prediction (NWP). Three measurement sites equipped with remote sensing instruments provide profiles of wind, temperature and humidity in real-time. Every three hours, the NWP model is adjusted to the wind measurements and generates analysis and forecast of the required 3D fields. Temperature and humidity profiles are used for verification to ensure the required quality.

The system is modernized in the EMER-Met StArt (2019-2021) project. Three new features are implemented:

a) Extension of the measurement network with additional remote sensing instruments for wind data close to the surface, i.e. below 2000 m above ground level (Doppler lidars and Microwave Radiometers);

b) Integration of additional wind, temperature and humidity data into the NWP model;

c) Provision of a dispersion ensemble forecast including forecast uncertainties.

Status of the project

The project started on 1 January 2019 and ends 31 December 2021. The implementation phase will end in Summer 2021 followed by a transition phase to make the new components operational.

Project Structure and Contact

The project is structured into three sub-projects dedicated to the development of the dispersion ensemble, to the data assimilation and to the extension of the remote sensing network, respectively.

The Project leader is Alexander Haefele.