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Abstract
Abstract. We validate a new high-resolution (3 km) numerical mesoscale weather simulation for offshore wind power purposes for the time period 2004–2016 for the North Sea and the Norwegian Sea. The 3 km Norwegian reanalysis (NORA3) is a dynamically downscaled data set, forced with state-of-the-art atmospheric reanalysis as boundary conditions. We conduct an in-depth validation of the simulated wind climatology towards the observed wind climatology to determine whether NORA3 can serve as a wind resource data set in the planning phase of future offshore wind power installations. We place special emphasis on evaluating offshore wind-power-related metrics and the impact of simulated wind speed deviations on the estimated wind power and the related variability. We conclude that the NORA3 data are well suited for wind power estimates but give slightly conservative estimates of the offshore wind metrics. In other words, wind speeds in NORA3 are typically 5 % (0.5 m s−1) lower than observed wind speeds, giving an underestimation of offshore wind power of 10 %–20 % (equivalent to an underestimation of 3 percentage points in the capacity factor) for a selected turbine type and hub height. The model is biased towards lower wind power estimates due to overestimation of the wind speed events below typical wind speed limits of rated wind power (u<11–13 m s−1) and underestimation of high-wind-speed events (u>11–13 m s−1). The hourly wind speed and wind power variability are slightly underestimated in NORA3. However, the number of hours with zero power production caused by the wind conditions (around 12 % of the time) is well captured, while the duration of each of these events is slightly overestimated, leading to 25-year return values for zero-power duration being too high for the majority of the sites. The model performs well in capturing spatial co-variability in hourly wind power production, with only small deviations in the spatial correlation coefficients among the sites. We estimate the observation-based decorrelation length to be 425.3 km, whereas the model-based length is 19 % longer.
Highlights
Exploiting the Norwegian continental shelf for offshore wind power purposes is advantageous due to the excellent wind climate (Zheng et al, 2016) and the recent increase in political engagement
After converting wind speed data to hourly wind power data, we examine the performance of NORA3 related to wind power climatology (Sect. 5), including wind power variables such as median production and capacity factor (CF)
As for the distribution of hourly wind speed ramp rates, the distributions of hourly wind power ramp rates are wider for the observation-based ramp rates than for the model-based ones, illustrating that the hourly estimated wind power variability based on observations is greater than the estimated variability based on NORA3 data
Summary
Exploiting the Norwegian continental shelf for offshore wind power purposes is advantageous due to the excellent wind climate (Zheng et al, 2016) and the recent increase in political engagement. The usefulness of multi-model ensembles has become increasingly clear over the last few decades in research fields such as weather prediction and climate change By this extensive validation of the NORA3 data set and documenting the quality of the simulated wind resource and related wind power estimates from a new model, we wish to contribute to the growing literature on offshore wind resources. A comparison of NORA3 against the host data set (ERA5) is conducted to document the improvement of the downscaling process To our knowledge this is the first peer-review paper focusing on evaluation of simulated wind resource and wind power estimates against offshore observations in the North Sea and ad-. In the last section (Sect. 6) we summarize the validation results
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