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Advances in Science and Research The open-access proceedings of the European Meteorological Society (EMS)

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Adv. Sci. Res., 14, 85-88, 2017
http://www.adv-sci-res.net/14/85/2017/
doi:10.5194/asr-14-85-2017
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
18 Apr 2017
CNR-ISAC 2 m temperature monthly forecasts: a first probabilistic evaluation
Daniele Mastrangelo and Piero Malguzzi

Data sets

The Subseasonal to Seasonal (S2S) Prediction Project Database
F. Vitart, C. Ardilouze, A. Bonet, A. Brookshaw, M. Chen, C. Codorean, M. Déqué, L. Ferranti, E. Fucile, M. Fuentes, H. Hendon, J. Hodgson, H. S. Kang, A. Kumar, H. Lin, G. Liu, X. Liu, P. Malguzzi, I. Mallas, M. Manoussakis, D. Mastrangelo, C. MacLachlan, P. McLean, A. Minami, R. Mladek, T. Nakazawa, S. Najm, Y. Nie, M. Rixen, A. W. Robertson, P. Ruti, C. Sun, Y. Takaya, M. Tolstykh, F. Venuti, D. Waliser, S. Woolnough, T. Wu, D. J. Won, H. Xiao, R. Zaripov, and L. Zhang
doi:10.1175/BAMS-D-16-0017.1
Publications Copernicus
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Short summary
The probabilistic evaluation of 2 m temperature forecast of about one year of monthly ensemble forecasts, issued on a monthly basis, is provided. The ranked probability skill score, averaged over all the available cases, shows that the system has a residual predictive skill beyond week 2 on some peculiar regions. Reliability diagrams show that, in general, the probability forecasts of above-normal observed temperature are more reliable than below-normal temperature.
The probabilistic evaluation of 2 m temperature forecast of about one year of monthly ensemble...
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