Evaluating the performance of numerical models in retrieving wind speeds at greater heights

Presentation at the EAWE PhD Seminar 2021 Understanding the in-situ wind conditions and climatology of a region is a fundamental requirement for the successful development of new offshore wind farms. However, meteorological (met) mast measurement campaigns are expensive, and the availability of high-reliable offshore observations is still scarce [1]. Consequently, numerical models have been widely used as an alternative by the wind industry to investigate wind resources at offshore sites. On the one hand, they are able to satisfactorily resolve the most relevant features of the marine atmospheric boundary layer. On the other hand, they provide wind and atmospheric parameters within a wide time and spatial range, and thus, they can address issues like the evaluation of wind climatology. Mesoscale model outputs have been extensively compared with experimental data in onshore and near-shore locations. However, further evaluations of the performance of the numerical models are still needed to better understand the capabilities and limitations of the modeled data in offshore sites. Furthermore, this fact is highlighted when considering heights above a few hundred meters, out of reach of the vast majority of measuring devices traditionally used for wind resource characterization. With this idea, the investigation presented here focuses on comparing one of the most widely used reanalyses within the wind energy industry, ERA5 (ECMWF Reanalysis 5th Generation) [2], with the observations of a long-range Doppler lidar. For this, data retrieved during the execution of a ship-based measurement campaign as part of the EUREC4A [3] project will be used. In this experiment, a Leosphere Windcube (WLS70) vertical profiler was installed onboard the research vessel Meteor, retrieving wind data up to 2,000 m height over the central Atlantic Ocean. With this comparison, we aim to investigate the performance of ERA5 in the offshore environment along the region covered by the vessel route, as well as to evaluate the potential influence of the elevation in the capabilities of this reanalysis dataset. References: [1] A. M. Sempreviva; R. J. Barthelmie; S. C. Pryor (2008): Review of Methodologies for Offshore Wind Resource Assessment in European Seas. In Surv Geophys 29 (6), pp. 471–497. DOI: 10.1007/s10712-008-9050-2. [2] Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS). https://cds.climate.copernicus.eu/cdsapp#!/home [3] B. Stevens; S. Bony; D. Farrell; F. Ament; A. Blyth; C. Fairall et al. (2021): Eurec4A. In Earth System Science Data 132 (8), pp. 4067-4119. DOI: 10.5194/essd-13-4067-202