Ensemble prediction using a new dataset of ECMWF initial states – OpenEnsemble 1.0

Ollinaho, Pirkka; Carver, Glenn D.; Lang, Simon T. K.; Tuppi, Lauri; Ekblom, Madeleine; Järvinen, Heikki

doi:https://doi.org/10.5194/gmd-14-2143-2021

Articles | Volume 14, issue 4

https://doi.org/10.5194/gmd-14-2143-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-14-2143-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 4

Development and technical paper

|

23 Apr 2021

Development and technical paper |

| 23 Apr 2021

Ensemble prediction using a new dataset of ECMWF initial states – OpenEnsemble 1.0

Pirkka Ollinaho, Glenn D. Carver, Simon T. K. Lang, Lauri Tuppi, Madeleine Ekblom, and Heikki Järvinen

Model code and software

pirkkao/OpenEPS: Initial release (Version v0.952) Pirkka Ollinaho https://doi.org/10.5281/zenodo.3759127

pirkkao/OpenEPS_PPro: Tag for Zenodo (Version v0.9) Pirkka Ollinaho https://doi.org/10.5281/zenodo.4001495

pirkkao/nc\_plot: Tag for Zenodo (Version v0.9) Pirkka Ollinaho https://doi.org/10.5281/zenodo.4001516

Short summary

OpenEnsemble 1.0 is a novel dataset that aims to open ensemble or probabilistic weather forecasting research up to the academic community. The dataset contains atmospheric states that are required for running model forecasts of atmospheric evolution. Our capacity to observe the atmosphere is limited; thus, a single reconstruction of the atmospheric state contains some errors. Our dataset provides sets of 50 slightly different atmospheric states so that these errors can be taken into account.