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Journal Article

A new E‐OBS gridded dataset for daily mean wind speed over Europe

Jouke H. S. de Baar; Gerard van der Schrier; Else J. M. van den Besselaar; Irene Garcia‐Marti; Cees de Valk
International Journal of Climatology · Vol. 43, Issue 13 · pp. 6083-6100 · 2023

Abstract

In this paper we present daily mean wind speed as a new variable in the publicly accessible E‐OBS gridded datasets. Each of the variables in the E‐OBS dataset is provided at a spatial resolution of 0.1° × 0.1° and 0.25° × 0.25°. The variable “daily mean wind speed” starts from 1980 and is updated every month. The main method that we apply is the use of adaptive covariate selection to model the monthly mean wind speed as a function of covariates, like altitude, distance to coast and surface roughness. Then, we use Gaussian process regression to interpolate the daily anomalies from the station locations to the grid locations. In addition, we develop ensemble dispersion improvement auto‐tune (EDIT) to improve the reliability of the local ensemble spread. In order to communicate the methodological uncertainty in the resulting dataset, the E‐OBS wind speed grid is provided as a 20‐member ensemble of random realizations. As part of a preliminary analysis, we investigate the hypothesized wind speed stilling effect in recent decades. Indeed, we do find a small yet significant wind speed stilling effect in the E‐OBS dataset.

Bibliographic Information

JournalInternational Journal of Climatology
PublisherWiley
Publication Date2023-11-15
Publication Year2023
Volume43
Issue13
Pages6083-6100
Document TypeJournal Article
Print ISSN0899-8418
eISSN1097-0088
DOI10.1002/joc.8191
SubjectAtmospheric Sciences

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NARA Access Coverage1996-01-01~Current
Journal Homepagehttps://rmets.onlinelibrary.wiley.com/loi/10970088
Publisher PageOpen Publisher Page
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