An Extended Analysis of Temperature Prediction in Italy: From Sub-Seasonal to Seasonal Timescales

Giuseppe Giunta, Alessandro Ceppi () and Raffaele Salerno
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Giuseppe Giunta: Facilities Technical Authority Department, Eni S.p.A, San Donato Milanese, 20097 Milan, Italy
Alessandro Ceppi: Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milan, Italy
Raffaele Salerno: Meteo Expert, Segrate, 20054 Milan, Italy

Forecasting, 2023, vol. 5, issue 4, 1-16

Abstract: Earth system predictions, from sub-seasonal to seasonal timescales, remain a challenging task, and the representation of predictability sources on seasonal timescales is a complex work. Nonetheless, advances in technology and science have been making continuous progress in seasonal forecasting. In a previous paper, a performance for temperature prediction by a modelling system named e-kmf ® was carried out in comparison with observations and climatology for a year of data; a low level of predictability in the sub-seasonal range, particularly in the second month, was observed over the Italian peninsula. Therefore, in this study, we focus our investigations specifically on the performance between the fifth and the eighth week of temperature forecasts over six years of simulations (2012–2018) to investigate the capability of the weather model to better reproduce the behavior of temperatures in the second month of the forecast. Although some differences in seasons are present, results have globally shown how temperature predictions have the potential to be quite skillful, with an average skill score of about 68%, with climatology used as reference; additionally, an overall anomaly correlation coefficient equal to 0.51 was shown, providing useful information for applications in planning, sales, and supply of natural energy resources.

Keywords: sub-seasonal prediction; temperature forecasts; model performance; benchmark analysis; applied climatology; statistical indexes (search for similar items in EconPapers)
JEL-codes: A1 B4 C0 C1 C2 C3 C4 C5 C8 M0 Q2 Q3 Q4 (search for similar items in EconPapers)
Date: 2023
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