On the Evaluation of the Extremality Index EFI

• Published in: Russian meteorology and hydrology Vol. 45; no. 1; pp. 1 - 12
• Main Authors: Kiktev, D. B., Kruglova, E. N., Kulikova, I. A.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 2020; Springer Nature B.V
• Subjects: Air temperature; Anomalies; Atmospheric Sciences; Computation; Earth and Environmental Science; Earth Sciences; Heat waves; Histograms; Hydrodynamic models; Hydrodynamics; Interpolation; Meteorology; Statistical methods; Statistical tests; Temperature anomalies; Weather forecasting; forecast skill score; 2-m air temperature anomaly; Extreme Forecast Index (EFI); heat wave; Extreme weather events
• ISSN: 1068-3739; 1934-8096
• DOI: 10.3103/S106837392001001X

The Extreme Forecast Index (EFI) calculations are performed using the ECMWF 2-m air temperature forecasts produced in the framework of the Subseasonal to Seasonal (S2S) Prediction Project. Four computation schemes are implemented using empirical and theoretical distributions of heat wave characteristics as well as the one-dimensional test statistics of histograms and linear interpolation formulas. Case studies (for different initial dates and regions) characterized by the significant air temperature anomalies in Northern Eurasia are performed using traditional forecast skill scores and the spatial verification methods to evaluate the efficiency of the proposed schemes for different threshold values of EFI. It is shown that the forecast quality can be considered satisfactory in most cases. The dependence of forecast skill on the intensity, spatial scales, and duration of temperature anomalies is revealed. Further studies should be carried out using larger samples based on several hydrodynamic models and the multimodel approach.