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The Making of the New European Wind Atlas, Pt.2: Production and Evaluation

: Dörenkämper, Martin; Olsen, Bjarke T.; Witha, Björn; Hahmann, Andrea N.; Davis, Neil N.; Barcons, Jordi; Ezber, Yasemin; Garcia-Bustamante, Elena; Gonazales-Rouco, J. Fidel; Navarro, Jorge; Sastre-Marugan, Mariano; Sile, Tija; Trei, Wilke; Zagar, Mark; Badger, Jake; Gottschall, Julia; Sanz Rodrigo, Javier; Mann, Jakob

Volltext ()

Geoscientific model development : GMD 13 (2020), Nr.10, S.5079-5102
ISSN: 1991-959X
ISSN: 1991-9603
Bundesministerium fur Wirtschaft und Energie BMWi (Deutschland)
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer IWES ()

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.