Using the Twentieth Century Reanalysis to assess climate variability for the European wind industry

TL;DR

This study uses 142 years of reanalysis data, calibrated against higher-resolution datasets, to analyze long-term wind variability in Europe, aiding wind energy planning by incorporating multidecadal climate fluctuations.

Contribution

It introduces a calibration method linking low-resolution 20CR data to ERAI, enabling long-term wind variability analysis for wind energy applications.

Findings

Many regions show weak long-term trends but significant multidecadal variability.

Calibrated 20CR data can extend wind climate assessments beyond typical short-term datasets.

Results help reduce investment risks by accounting for decadal wind variability.

Abstract

We characterise the long-term variability of European near-surface wind speeds using 142 years of data from the Twentieth Century Reanalysis (20CR), and consider the potential of such long-baseline climate data sets for wind energy applications. The low resolution of the 20CR would severely restrict its use on its own for wind farm site-screening. We therefore perform a simple statistical calibration to link it to the higher-resolution ERA-Interim data set (ERAI), such that the adjusted 20CR data has the same wind speed distribution at each location as ERAI during their common period. Using this corrected 20CR data set, wind speeds and variability are characterised in terms of the long-term mean, standard deviation, and corresponding trends. Many regions of interest show extremely weak trends on century timescales, but contain large multidecadal variability. Since reanalyses such as ERAI are often used to provide the background climatology for wind farm site assessments, but contain only a few decades of data, our results can be used as a way of incorporating decadal-scale wind climate variability into such studies, allowing investment risks for wind farms to be reduced.