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

Authors :
de Baar, Jouke H. S.
van der Schrier, Gerard
van den Besselaar, Else J. M.
Garcia‐Marti, Irene
de Valk, Cees
Source :
International Journal of Climatology; Nov2023, Vol. 43 Issue 13, p6083-6100, 18p
Publication Year :
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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08998418
Volume :
43
Issue :
13
Database :
Complementary Index
Journal :
International Journal of Climatology
Publication Type :
Academic Journal
Accession number :
173485684
Full Text :
https://doi.org/10.1002/joc.8191