Statistical Modeling for Improvement of Numerical-Model-Based Solar Radiation Forecasts

0477273 - ÚI 2019 RIV CH eng C - Conference Paper (international conference)
Brabec, Marek - Eben, Kryštof - Pelikán, Emil - Krč, Pavel - Resler, Jaroslav - Juruš, Pavel
Statistical Modeling for Improvement of Numerical-Model-Based Solar Radiation Forecasts.
Proceedings of the Third International Afro-European Conference for Industrial Advancement - AECIA 2016. Cham: Springer, 2018 - (Abraham, A.; Haqiq, A.; Ella Hassanien, A.; Snášel, V.; Alimi, A.), s. 248-257. Advances in Intelligent Systems and Computing, 565. ISBN 978-3-319-60833-4. ISSN 2194-5357.
[AECIA 2016. International Afro-European Conference for Industrial Advancement /3./. Marrakesh (MA), 21.11.2016-26.11.2016]
R&D Projects: GA ČR GA13-34856S
Institutional support: RVO:67985807
Keywords : generalized additive model * numerical weather forecast model * global solar radiation * calibration * semiparametric modeling
OECD category: Statistics and probability
https://link.springer.com/chapter/10.1007/978-3-319-60834-1_26

ZÁKLADNÍ ÚDAJE: Proceedings of the Third International Afro-European Conference for Industrial Advancement - AECIA 2016. Cham: Springer, 2018 - (Abraham, A., Haqiq, A., Ella Hassanien, A., Snášel, V., Alimi, A.), s. 248-257. Advances in Intelligent Systems and Computing, 565. ISBN 978-3-319-60833-4. ISSN 2194-5357. [AECIA 2016. International Afro-European Conference for Industrial Advancement /3./. Marrakesh (MA), 21.11.2016-26.11.2016]. Podpora: GA13-34856S. ANOTACE: We first analyze some features of numerical weather predictions (NWP) for global solar radiation and notice that they are undersmooth. This finding opens a way to improvements via various smoothing strategies. Then we introduce a statistical modeling framework based on modern semiparametric regression. We use a numerical weather prediction (NWP) model output as one of the inputs for our statistical model. The statistical model is build on the modern regression formalism, utilizing nonparametric B-splines for nonlinear parts whose exact shape is unknown a priori (apart from physically motivated smoothness). Then we illustrate its abilities for systematic development of strategies for NWP calibration and further development. The results are useful both for practical forecasting and as a source of feedback for NWP modelers.
Permanent Link: http://hdl.handle.net/11104/0273655