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Pregled bibliografske jedinice broj: 970690

Deterministic Wind Speed Predictions with Analog-Based Methods over Complex Topography


(RAL, NCAR) Plenković, Iris Odak; Delle Monache, Luca; Horvath, Kristian; Hrastinski, Mario
Deterministic Wind Speed Predictions with Analog-Based Methods over Complex Topography // Journal of applied meteorology and climatology, 57 (2018), 9; 2047-2070 doi:10.1175/jamc-d-17-0151.1 (međunarodna recenzija, članak, znanstveni)


Naslov
Deterministic Wind Speed Predictions with Analog-Based Methods over Complex Topography

Autori
Plenković, Iris Odak ; Delle Monache, Luca ; Horvath, Kristian ; Hrastinski, Mario

Kolaboracija
RAL, NCAR

Izvornik
Journal of applied meteorology and climatology (1558-8424) 57 (2018), 9; 2047-2070

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Statistical techniques ; mesoscale forecasting ; numerical weather prediction/forecasting ; Operational forecasting ; statistical forecasting ; model output statistics

Sažetak
The performance of analog-based and Kalman filter (KF) postprocessing methods is tested in climatologically and topographically different regions for point-based wind speed predictions at 10 m above the ground. The results are generated using several configurations of the mesoscale numerical weather prediction model ALADIN. This study shows that deterministic analog-based predictions (ABPs) improve the correlation between predictions and measurements while reducing the forecast error, with respect to both the starting model predictions and the KF-based correction. While the KF generally outperforms the ABPs in bias reduction, the combination of the KF and analog approach can be similarly successful. In the coastal complex area, characterized with a larger frequency of strong wind, the ABPs are more successful in reducing the dispersion error than the KF. The application of the KF algorithm to the analogs in the so-called analog space (KFAS) is the least prone to standard deviation underestimation among the ABPs. All ABPs improve the prediction of larger-than-diurnal motions, and KFAS is superior among all ABPs in predicting alternating wind regimes on time scales shorter than a day. The ABPs better distinguish different wind speed categories in the coastal complex terrain by using a higher-resolution model input. Differences among starting model and postprocessed forecasts in other types of terrain are less pronounced.

Izvorni jezik
Engleski

Napomena
Slobodan pristup na: https://journals.ametsoc.org/doi/abs/10.1175/JAMC-D-17-0151.1



POVEZANOST RADA


Ustanove
Državni hidrometeorološki zavod

Autor s matičnim brojem:
Kristian Horvath, (273211)

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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