Publication: The Making of the New European Wind Atlas - Part 2: production and evaluation
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2020-10-27
Authors
González Rouco, J. Fidel
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Copernicus Gesellschaft MBH
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Abstract
This is the second of two papers that document the creation of the New European Wind Atlas (NEWA). In Part 1, we described the sensitivity experiments and accompanying evaluation done to arrive at the final mesoscale model setup used to produce the mesoscale wind atlas. In this paper, Part 2, we document how we made the final wind atlas product, covering both the production of the mesoscale climatology generated with the Weather Research and Forecasting (WRF) model and the microscale climatology generated with the Wind Atlas Analysis and Applications Program (WAsP). The paper includes a detailed description of the technical and practical aspects that went into running the mesoscale simulations and the downscaling using WAsP. We show the main results from the final wind atlas and present a comprehensive evaluation of each component of the NEWA model chain using observations from a large set of tall masts located all over Europe. The added value of the WRF and WAsP downscaling of wind climatologies is evaluated relative to the performance of the driving ERA5 reanalysis and shows that the WRF downscaling reduces the mean wind speed bias and spread relative to that of ERA5 from −1.50 ± 1.30 to 0.02 ± 0.78 m s^(−1) . The WAsP downscaling has an added positive impact relative to that of the WRF model in simple terrain. In complex terrain, where the assumptions of the linearized flow model break down, both the mean bias and spread in wind speed are worse than those from the raw mesoscale results.
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Artículo firmado por 18 autores. © Author(s) 2020. The computing resources for the calculation of the mesoscale wind atlas were made available through a PRACE grant (project no. 2017174128) between April 2018 and March 2019. The microscale atlas was computed between April 2019 and June 2019 on the DTU “Sophia” HPC cluster. A feasibility study and many tests for the production run were carried out on the HPC cluster EDDY located at the University of Oldenburg and funded by the Federal Ministry for Economic Affairs and Energy under grant no. 0324005. Access to the tall mast data used for the evaluation have kindly been granted by Vestas Wind Systems A/S. The authors are grateful to Yavor Hristov from Vestas for helping to make the mast data available. The WRF model simulations were initialized using ERA5 and OSTIA data downloaded from ECMWF, Copernicus Climate Change Service Climate Data Store, and Copernicus Marine Environment Monitoring Service. The authors are grateful to Mark Kelly from DTU Wind energy for valuable comments and discussions; to the technical staff at PRACE, DTU, and the University of Oldenburg for assistance and maintenance of the systems; and to Nazka Maps for making the NEWA wind atlas website. Data processing and visualization for this study was made using the python programming language and involved extensive use of the following software packages: NumPy (Oliphant, 2006; Van Der Walt et al., 2011), SciPy (Jones et al., 2001), pandas (McKinney, 2010), Dask (Dask Development Team, 2016), xarray (Hoyer and Hamman, 2017), Matplotlib (Hunter, 2007), and scikitlearn (Pedregosa et al., 2011). The authors are grateful for the tools provided by the open-source community, which has benefited the making of this study tremendously. Financial support. The European Commission (EC) partly funded NEWA (NEWA – New European Wind Atlas) through FP7 (topic FP7-ENERGY.2013.10.1.2). The authors of this paper acknowledge the support from the Federal Ministry for the Economic Affairs and Energy, on the basis of the decision by the German Bundestag (grant no. 0325832A/B); the Danish Energy Authority (EUDP 14- II, 64014-0590); Latvijas Zinatnu Akademija (Latvia – grant no. Z/16/1397); the Ministerio de Economía y Competitividad (Spain; grant nos. PCIN-2014-017-C07-03, PCIN-2016-176, PCIN-2014- 017-C07-04, PCIN-2016-009, PCIN-2014-013-C07-04, and PCIN2016-080); the Scientific and Technological Research Council of Turkey (grant no. 215M386). Mariano Sastre-Marugán additionally acknowledges support from the Spanish Ministerio de Educación, Cultura y Deporte through the “José Castillejo” Fellowship (grant no. CAS18/00316).