New open dataset enables the research of ensemble prediction
Open dataset called ”OpenEnsemble 1.0” provides unparalleled possibility for the academic research community to participate in the research of ensemble and probabilistic weather forecasts. Newly opened dataset includes a set of perturbed initial conditions that enables ensemble forecasting and helps to acknowledge also the alternative but equally plausible future evolutions of the atmospheric state.
Ensemble forecasting provides researchers a key to e.g. understand, how are the uncertainties and errors in weather forecasts depend on the errors in the initial conditions of the atmospheric state used in the weather prediction models. Dataset has been compiled in 2019–2020 by the Finnish Meteorological Institute, University of Helsinki and European Centre for Medium-Range Weather Forecasts (ECMWF).
Postdoctoral Researcher Pirkka Ollinaho, firstname.lastname@example.org, Finnish Meteorological Institute
Scientific article: Ollinaho, P., Carver, G. D., Lang, S. T. K., Tuppi, L., Ekblom, M., and Järvinen, H.: Ensemble prediction using a new dataset of ECMWF initial states – OpenEnsemble 1.0, Geosci. Model Dev., 14, 2143–2160, https://doi.org/10.5194/gmd-14-2143-2021, 2021.