Advances in Science and Research
Advances in Science and Research
ASR
Articles | Volume 14
Articles | Volume 14
https://doi.org/10.5194/asr-14-85-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/asr-14-85-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 14
18 Apr 2017
 | 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 https://doi.org/10.1175/BAMS-D-16-0017.1

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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.
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