Three-model ensemble wind prediction in southern Italy
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Published:2016-03-21
Issue:3
Volume:34
Page:347-356
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ISSN:1432-0576
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Container-title:Annales Geophysicae
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language:en
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Short-container-title:Ann. Geophys.
Author:
Torcasio Rosa ClaudiaORCID, Federico StefanoORCID, Calidonna Claudia RobertaORCID, Avolio ElenioORCID, Drofa Oxana, Landi Tony Christian, Malguzzi Piero, Buzzi Andrea, Bonasoni Paolo
Abstract
Abstract. Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council – Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.
Publisher
Copernicus GmbH
Subject
Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Geology,Astronomy and Astrophysics
Reference32 articles.
1. Alessandrini, S., Pinson, P., Hagedorn, R., Decimi, G., and Sperati, S.: An application of ensemble/multi model approach for wind power production forecasting, Adv. Sci. Res., 6, 35–37, https://doi.org/10.5194/asr-6-35-2011, 2011. 2. Alessandrini, A., Sperati, S., and Pinson, P.: A comparison between the ECMWF and COSMO Ensemble Prediction Systems applied to short-term wind power forecasting on real data, Appl. Energy, 107, 271–280, 2013. 3. Bolle, H. J.: Mediterranean Climate, trends and variability, Springer, Berlin, 384 pp., 2012. 4. Carter, G. M., Dallavalle, J. P., and Glahn, H. R.: Statistical forecasts based on the National Meteorological Center's numerical weather prediction system, Weather Forecast., 4, 401–412, 1989. 5. Chen, C. and Cotton, W. R.: A One-Dimensional Simulation of the Stratocumulus-Capped Mixed Layer, Bound.-Lay. Meteorol., 25, 289–321, 1983.
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