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

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.

Charge generation by passive plant leaf motion at low wind speeds: design and collective behavior of plant-hybrid energy harvesters

“…The daily mean wind speeds in Europe are typically below 3-4 m s −1 especially on lower heights (e.g. 10 m above ground level) [31] and leaves show significant motion already at 1 m s −1 [32]. Thus, four designs leading to different dynamic responses have been assembled, installed on N. oleander leaves and exposed to low wind speeds of up to 3.3 m s −1 in a phytochamber equipped with a tunable wind tunnel; energy conversion and leaf motion were tracked.…”