Future projections of wind energy potentials in the arctic for the 21st century under the RCP8.5 scenario from regional climate models (Arctic-CORDEX)

Akperov, Mirseid; Eliseev, Alexey V.; Rinke, Annette; Mokhov, Igor I.; Semenov, Vladimir A.; Dembitskaya, Mariya; Matthes, Heidrun; Adakudlu, Muralidhar; Boberg, Fredrik; Christensen, Jens H.; Dethloff, Klaus; Fettweis, Xavier; Gutjahr, Oliver; Heinemann, Günther; Koenigk, Torben; Sein, Dmitry; Laprise, René; Mottram, Ruth; Nikiéma, Oumarou; Sobolowski, Stefan; Winger, Katja; Zhang, Wenxin

doi:10.1016/j.ancene.2023.100402

Cited by 2 publications

(1 citation statement)

References 73 publications

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“…where Γ is the gamma function. In many studies (e.g., Li et al 2019, Akperov et al 2022, Akperov et al 2023, the parameters k and c were calculated separately for each month. However, due to limited yearround data at stations (except Zvenigorod), we initially calculated these parameters for the entire data series rather than for each month.…”

Section: Bias Correction Methodsmentioning

confidence: 99%

Relevance Of Era5 Reanalysis For Wind Energy Applications: Comparison With Sodar Observations

Shestakova,

Fedotova,

Lyulyukin

2024

GES

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ERA5 reanalysis is one of the most trusted climate data sources for wind energy modeling. However, any reanalysis should be verified through comparison with observational data to detect biases before further use. For wind verification at heights close to typical wind turbine hub heights (i.e. about 100 m), it is preferable to use either in-situ measurements from meteorological towers or remote sensing data like acoustic and laser vertical profilers, which remain independent of reanalysis. In this study, we validated the wind speed data from ERA5 at a height of 100 m using data from four sodars (acoustic profilers) located in different climatic and natural vegetation zones across European Russia. The assessments revealed a systematic error at most stations; in general, ERA5 tends to overestimate wind speed over forests and underestimate it over grasslands and deserts. As anticipated, the largest errors were observed at a station on the mountain coast, where the relative wind speed error reached 45%. We performed the bias correction which reduced absolute errors and eliminated the error dependence on the daily course, which was crucial for wind energy modeling. Without bias correction, the error in the wind power capacity factor ranged from 30 to 50%. Hence, it is strongly recommended to apply correction of ERA5 for energy calculations, at least in the areas under consideration..

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Section: Bias Correction Methodsmentioning

confidence: 99%