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is suitable for those who have a genuine interest in ECMWF forecasting products and want to exploit fully the potential of these products in their daily duties, whether they are producing forecast bulletins or taking decisions that are affected by weather phenomena. |
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| The course is a mixture of standard classroom lectures and practical activities where real weather cases are analysed in details and attendees are expected to report on at the end of the training week. Networking among the attendees is encouraged by allocating time for the participants to present their work and share their previous experience with ECMWF products. The |
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aim of the course is to provide the students with background knowledge to help them to make an informed use of ECMWF NWP products and to introduce students to novel products At the end of the course, the participants will be able: - to master to use of ensemble forecasts
- to understand potentials and weaknesses of NWP products
- to use novel forecast products
- to use ECMWF products for forecast guidance
- to make use of ECMWF products in decision making
The course is assessed by means of an online survey which allows the participants to include their feedback and suggestions for improvements. The learning outcomes are assessed separately using a self-evaluation method. |
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- Forum
- Exercises: Homework no.1
- Students' presentation: guidance
- Suggested readings
- Training course timetable
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EUMETCAL e-training modules:
The following modules will help you to learn about verification techniques for deterministic and probability forecast. Following the link below and complete the modules. There will be a 'Taking stock' session during the training week when verification techniques will be discussed starting from the exercises you have done in the modules:
VERIFICATION METHODS
WEBCASTs
if you cannot play it, please download the MP4 file (right click and choose 'Save link as' ) and play it locally with Windows media player, or quicktime or VLC (free software)
This video was recorded during a lecture on Operational forecasting at ECMWF. It discusses briefly the components of the ECMWF forecasting system and products (about 20 minutes)
This lecture describes the monitoring system for conventional (in situ) observations. These observations are assimilated in the forecasting system and therefore an assessment of their quality is crucial to guarantee the best quality of initial conditions for the model forecast (about 50 minutes)
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Case studies
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Pre-course programmeAll pre-course activities are on the Learning Portal (learning.ecmwf.int). Please note that these activities are integral part of the course and by completing them you will be able to get the most benefit out of the training week. The pre-course learning and activities will take around 12 hours to complete.
ProgrammeThe programme for the course is available on the Learning Portal (learning.ecmwf.int). The February 2021 course will be fully virtual and held via Zoom. All details can be found in the Learning Portal.
Virtual Laboratory GroupsDuring the Virtual Laboratory work attendees will be split into groups. The Breakout Groups function in Zoom will be utilised with participants encouraged to share screens and docments to complete the work. We have created a Confluence page for each Group to facilitate the sharing of information / images / documents etc however please feel free to use other methods of sharing if you prefer. Workspace for Group 1 - Fernando Workspace for Group 2 - Linus Workspace for Group 3 - Mohamed Workspace for Group 4 - Ivan Workspace for Group 5 - Tim |
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dashedGENERAL INFORMATION for participants250 |
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You will be able to download lectures from here. Just click on the title!
Lecturer | Title | Lecturer | Title |
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E. Andersson | Introducing ECMWF | L. Isaksen | Data assimilation |
P. Bechtold | Model Physics | F. Prates | Forecasting tropical cyclones in the medium range |
J. Bidlot | Wave forecasting | D. Richardson | Ensemble forecasts: can they help making decisions? |
M. Dahoui | Use of satellite observations | I. Tsonevsky | Forecasting extreme events (Webinar) |
L. Ferranti | - Monthly Forecast (Webinar)
- Seasonal forecasting
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