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2022 Training Courses: registrations close soon

Sarah Keeley, Becky Hemingway

 

For the coming spring training season at ECMWF, we have expanded our training opportunities. All training for the new year is planned to be at the ECMWF headquarters in Reading. However, as the last two COVID‑19 years have shown, we will have to adapt plans to the global situation nearer the time. We will also continue the two-level access pilot scheme for our Parametrization and Predictability courses so that it is possible to register as just a virtual attendee. The new ‘Hands-on introduction to numerical weather prediction models’ will be expanded to a five-day course this year after the positive feedback we received from participants.

There will be two new elements in 2022. As the new supercomputer system comes online in Bologna, there will be high-performance computer training for the Atos machine, which will run in March. In addition, a four-day machine learning course is being run for the first time in May. It will focus on machine learning for weather prediction.

The deadline for applications is fast approaching (29 October), so please apply soon. You can do so by accessing the ‘Registration’ page for the relevant course, a full online list of which can be found here: https://events.ecmwf.int/category/1/. We aim to process the applications with Member State endorsements by December so that people have enough time to make travel arrangements. We hope to be able to welcome you in person to a training event in 2022!

07 Feb – 10 FebUse and interpretation of ECMWF products
28 Feb – 04 MarData assimilation
07 Mar – 11 MarEUMETSAT/ECMWF NWP-SAF satellite data assimilation
14 Mar – 18 MarHigh-performance computing – Atos
21 Mar – 25 MarPredictability and ensemble forecast systems
28 Mar – 01 AprParametrization of subgrid physical processes
25 Apr – 29 AprAdvanced numerical methods for Earth system modelling 
03 May – 06 MayMachine learning for weather prediction
16 May – 20 MayA hands-on introduction to numerical weather prediction models: understanding and experimenting
03 Oct – 06 Oct Use and interpretation of ECMWF products