Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 541243
Title Evaluation of three mainstream numerical weather prediction models with observations from meteorological mast IJmuiden at the North Sea
Author(s) Kalverla, Peter; Steeneveld, Gert Jan; Ronda, Reinder; Holtslag, Albert A.M.
Source Wind Energy 22 (2019)1. - ISSN 1095-4244 - p. 34 - 48.
Department(s) Meteorology and Air Quality
Publication type Refereed Article in a scientific journal
Publication year 2019
Keyword(s) Met mast IJmuiden - Model evaluation - North Sea - Numerical weather prediction

Numerical weather prediction models play an important role in the field of wind energy, for example, in power forecasting, resource assessment, wind farm (wake) simulations, and load assessment. Continuous evaluation of their performance is crucial for successful operations and further understanding of meteorology for wind energy purposes. However, extensive offshore observations are rarely available. In this paper, we use unique met mast and Lidar observations up to 315 m from met mast “IJmuiden,” located in the North Sea 85 km off the Dutch coast, to evaluate the representation of wind and other relevant variables in three mainstream meteorological models: ECMWF-IFS, HARMONIE-AROME, and WRF-ARW, for a wide range of weather conditions. Overall performance for hub-height wind speed is found to be comparable between the models, with a systematic wind speed bias <0.5 m/s and random wind speed errors (centered RMSE) <2 m/s. However, the model performance differs considerably between cases, with better performance for strong wind regimes and well-mixed wind and potential temperature profiles. Conditions characterized by moderate wind speeds combined with stable stratification, which typically produce substantial wind shear and power fluctuations, lead to the largest misrepresentations in all models.

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