Articles | Volume 16
https://doi.org/10.5194/asr-16-39-2019
https://doi.org/10.5194/asr-16-39-2019
08 Apr 2019
 | 08 Apr 2019

Using the ECMWF OpenIFS model and state-of-the-art training techniques in meteorological education

Gabriella Szépszó, Victoria Sinclair, and Glenn Carver

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Cited articles

Balsamo, G. and Belward, A.: Lakes in weather prediction: a moving target, ECMWF Newsletter, 150, p. 6, available at: https://www.ecmwf.int/en/newsletter/150/news/lakes-weather-prediction-moving-target (last access: 2 April 2019), 2017. 
Balsamo, G., Viterbo, P., Beljaars, A., van den Hurk, B., Hirschi, M., Betts, A. K., and Scipal, K.: A revised hydrology for the ECMWF model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrometeorol., 10, 623–643, https://doi.org/10.1175/2008JHM1068.1, 2009. 
Bauer, P. and Richardson, D., New model cycle 40r1, ECMWF Newsletter, 138, p. 3, available at: https://www.ecmwf.int/en/elibrary/14581-newsletter-no-138-winter-2013-14 (last access: 2 April 2019), 2014. 
Buizza, R., Miller, M., and Palmer, T. N.: Stochastic representation of model uncertainties in the ECMWF Ensemble Prediction System, Q. J. Roy. Meteor. Soc., 125, 2887–2908, https://doi.org/10.1002/qj.49712556006, 1999. 
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Short summary
The OpenIFS programme of ECMWF maintains a version of the ECMWF forecast model for use in education and research at universities, national meteorological services and other institutes. Application of OpenIFS as a training tool is wide ranging. The OpenIFS user meetings and training events demonstrate advanced and easy-to-use graphical tools and training technologies, e.g. OpenIFS and Metview “virtual machines”. This paper shows the education activity in the OpenIFS programme with some examples.