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Wind speed

The operational meteoblue multimodel mix for the 10 m wind speed is of similar quality as the ERA5 historical reanalysis. Numerical weather forecast models have significantly larger MAE values than ERA5, MOS or the meteoblue multi-model mix. A mean absolute error of smaller than 2 m s-1 was found for 89 % of the meteorological stations by using the meteoblue multimodel mix. For 87% of the meteorological stations the mean absolute error is smaller than 2 m s-1 by using the reanalysis model ERA5, followed by GFS (80%) and NEMS (80%).

Mountainous and continental regions typically show the largest model errors. The regions with the best model quality are Europe and North America, whereas the model accuracy of the wind speed is typically worst close to the equator, in Africa and in Australia.

Mean absolute error (MAE), mean bias error (MBE), root mean square error (RMSE) and standard deviation (stddev) [m s-1] and Pearson correlation coefficient for numerical weather forecast models (GFS, NEMS), the meteoblue multi-model mix and historical reanalysis model ERA5.

MAE [m s-1] MBE [m s-1] RMSE [m s-1] stddev [m s-1] Pearson correlation
meteoblue multimodel mix 1.48 0.13 1.94 1.66 0.67
ERA5 1.49 0.03 1.93 1.62 0.66
GFS 1.69 0.24 2.20 1.87 0.58
NEMS 1.67 -0.05 2.20 1.85 0.60

MAE [m s-1] of meteoblue multimodel mix 10 m wind speed used in operational weather forecast. Verification is based on all hourly data of the year 2017.

MAE [m s-1] of the reanalysis model ERA5 (not available as forecast) used for long term historical analysis. Verification is based on all hourly data of the year 2017.

MAE [m s-1] of wind speed forecasts for ‘stand-alone’ model output as computed by the numerical weather forecast model GFS. Verification is based on all hourly data of the year 2017.

MAE [m s-1] of the 10 m wind speed from the numerical weather forecast model NEMS. Verification is based on all hourly data of the year 2017