This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.
Downloads
Supplementary Files
Authors
Abstract
Time series analysis developed in the previous report [1] for UK mean summer temperature has been applied to further examples of weather trends, including temperature, rainfall and Sahara dust, and so at global, regional, national and local levels, in an attempt to assess whether wind power is having a deleterious effect on weather patterns.
The analysis involves detrending weather data by calculating first differences and then computing the cross-correlation function, or CCF with wind power capacity. The calculations are benchmarked using atmospheric CO2 concentration. The consistency of a significant correlation is tested by detrending using linear residuals and then calculating the CCF on the basis of the residuals, corrected for autocorrelation using the Cochrane-Orcutt procedure [4].
In four cases, where the data were reliable, the analysis provided a clear distinction in favour of wind power as a putative cause of the weather trends, in preference to atmospheric CO2 concentration. Where the quality of the data was less reliable, the outcome was inconclusive. Nevertheless, it would seem that our efforts to mitigate anthropogenic global warning with wind power might well be having a deleterious effect on weather patterns
DOI
https://doi.org/10.31223/X5J13V
Subjects
Climate
Keywords
climate change, wind power, time series analysis, weather trends, Berkeley GMST, Sahara dust, Cross-correlation, CCF, autocorrelation, Cochrane-Orcutt
Dates
Published: 2024-12-04 14:00
Last Updated: 2024-12-04 19:00
License
CC BY Attribution 4.0 International
Additional Metadata
Conflict of interest statement:
None
There are no comments or no comments have been made public for this article.