Winter Subseasonal Wind Speed Forecasts for Finland from ECMWF
-
Published:2021-08-04
Issue:
Volume:18
Page:127-134
-
ISSN:1992-0636
-
Container-title:Advances in Science and Research
-
language:en
-
Short-container-title:Adv. Sci. Res.
Author:
Hyvärinen OttoORCID, Laurila Terhi K.ORCID, Räty Olle, Korhonen Natalia, Vajda Andrea, Gregow Hilppa
Abstract
Abstract. The subseasonal forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts) were used to construct weekly mean wind speed forecasts for the spatially aggregated area in Finland.
Reforecasts for the winters (November, December and January) of 2016–2017 and 2017–2018 were analysed.
The ERA-Interim reanalysis was used as observations and climatological forecasts.
We evaluated two types of forecasts, the deterministic forecasts and the probabilistic forecasts.
Non-homogeneous Gaussian regression was used to bias-adjust both types of forecasts.
The forecasts proved to be skilful until the third week, but the longest skilful lead time
depends on the reference data sets and the verification scores used.
Funder
Academy of Finland
Publisher
Copernicus GmbH
Reference33 articles.
1. Baran, S. and Lerch, S.: Mixture EMOS model for calibrating ensemble forecasts
of wind speed, Environmetrics, 27, 116–130, https://doi.org/10.1002/env.2380, 2016. a 2. Buizza, R. and Leutbecher, M.: The forecast skill horizon, Q. J.
Roy. Meteor. Soc., 141, 3366–3382, https://doi.org/10.1002/qj.2619,
2015. a 3. Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler,
M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J.,
Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N.,
and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of
the data assimilation system, Q. J. Roy. Meteor.
Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a 4. ECMWF: IFS documentation, CY43R2, Part V: Ensemble Prediction System,
ECMWF, available at:
https://www.ecmwf.int/sites/default/files/elibrary/2016/17118-part-v-ensemble-prediction-system.pdf (last access: 2 August 2021),
2016. a 5. Ervasti, T., Gregow, H., Vajda, A., Laurila, T. K., and Mäkelä, A.: Mapping users' expectations regarding extended-range forecasts, Adv. Sci. Res., 15, 99–106, https://doi.org/10.5194/asr-15-99-2018, 2018. a
|
|