scholarly journals Fast calculation of the fractions skill score

MAUSAM ◽  
2021 ◽  
Vol 66 (3) ◽  
pp. 457-466
Author(s):  
NATHAN FAGGIAN ◽  
BELINDA ROUX ◽  
PETER STEINLE ◽  
BETH EBERT
Keyword(s):  
2021 ◽  
Author(s):  
Nicola Cortesi ◽  
Verónica Torralba ◽  
Llorenó Lledó ◽  
Andrea Manrique-Suñén ◽  
Nube Gonzalez-Reviriego ◽  
...  

AbstractIt is often assumed that weather regimes adequately characterize atmospheric circulation variability. However, regime classifications spanning many months and with a low number of regimes may not satisfy this assumption. The first aim of this study is to test such hypothesis for the Euro-Atlantic region. The second one is to extend the assessment of sub-seasonal forecast skill in predicting the frequencies of occurrence of the regimes beyond the winter season. Two regime classifications of four regimes each were obtained from sea level pressure anomalies clustered from October to March and from April to September respectively. Their spatial patterns were compared with those representing the annual cycle. Results highlight that the two regime classifications are able to reproduce most part of the patterns of the annual cycle, except during the transition weeks between the two periods, when patterns of the annual cycle resembling Atlantic Low regime are not also observed in any of the two classifications. Forecast skill of Atlantic Low was found to be similar to that of NAO+, the regime replacing Atlantic Low in the two classifications. Thus, although clustering yearly circulation data in two periods of 6 months each introduces a few deviations from the annual cycle of the regime patterns, it does not negatively affect sub-seasonal forecast skill. Beyond the winter season and the first ten forecast days, sub-seasonal forecasts of ECMWF are still able to achieve weekly frequency correlations of r = 0.5 for some regimes and start dates, including summer ones. ECMWF forecasts beat climatological forecasts in case of long-lasting regime events, and when measured by the fair continuous ranked probability skill score, but not when measured by the Brier skill score. Thus, more efforts have to be done yet in order to achieve minimum skill necessary to develop forecast products based on weather regimes outside winter season.


2021 ◽  
Vol 11 (5) ◽  
pp. 2150
Author(s):  
Claudio Rossi ◽  
Alessio Pilati ◽  
Marco Bertoldi

This paper deals with the digital implementation of a motor control algorithm based on a unified machine model, thus usable with every traditional electric machine type (induction, brushless with interior permanent magnets, surface permanent magnets or pure reluctance). Starting from the machine equations in matrix form in continuous time, the paper exposes their discrete time transformation, suitable for digital implementation. Since the solution of these equations requires integration, the virtual division of the calculation time in sub-intervals is proposed to make the calculations more accurate. Optimization of this solver enables faster runs and higher precision especially when high rotating speed requires fast calculation time. The proposed solver is presented at different implementation levels, and its speed and accuracy performance are compared with standard solvers.


2021 ◽  
Vol 42 (11) ◽  
pp. 787-792
Author(s):  
Alexei Nikitin ◽  
Vladislava Milchevskaya ◽  
Alexander Lyubartsev

Author(s):  
Hermann Anetzberger ◽  
Stephan Reppenhagen ◽  
Hansjörg Eickhoff ◽  
Franz Josef Seibert ◽  
Bernd Döring ◽  
...  

2003 ◽  
Author(s):  
Daniel B. Russakoff ◽  
Torsten Rohlfing ◽  
Daniel Rueckert ◽  
Ramin Shahidi ◽  
Daniel Kim ◽  
...  

2013 ◽  
Vol 28 (3) ◽  
pp. 802-814 ◽  
Author(s):  
Timothy W. Armistead

Abstract The paper briefly reviews measures that have been proposed since the 1880s to assess accuracy and skill in categorical weather forecasting. The majority of the measures consist of a single expression, for example, a proportion, the difference between two proportions, a ratio, or a coefficient. Two exemplar single-expression measures for 2 × 2 categorical arrays that chronologically bracket the 130-yr history of this effort—Doolittle's inference ratio i and Stephenson's odds ratio skill score (ORSS)—are reviewed in detail. Doolittle's i is appropriately calculated using conditional probabilities, and the ORSS is a valid measure of association, but both measures are limited in ways that variously mirror all single-expression measures for categorical forecasting. The limitations that variously affect such measures include their inability to assess the separate accuracy rates of different forecast–event categories in a matrix, their sensitivity to the interdependence of forecasts in a 2 × 2 matrix, and the inapplicability of many of them to the general k × k (k ≥ 2) problem. The paper demonstrates that Wagner's unbiased hit rate, developed for use in categorical judgment studies with any k × k (k ≥ 2) array, avoids these limitations while extending the dual-measure Bayesian approach proposed by Murphy and Winkler in 1987.


Sign in / Sign up

Export Citation Format

Share Document