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Harrison, Giles, Nicoll, Keri, Joshi, Manoj 
ORCID: https://orcid.org/0000-0002-2948-2811 and Hawkins, Ed
(2022)
Empirical evidence for multidecadal scale global atmospheric electric circuit modulation by the El Niño-southern oscillation.
Environmental Research Letters, 17 (12).
ISSN 1748-9326
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Abstract
The El Niño-Southern Oscillation (ENSO) modifies precipitation patterns across the planet. Charge separation in disturbed weather and thunderstorms drives the global atmospheric electric circuit (GEC), hence ENSO-induced precipitation changes are anticipated to affect the global circuit. By analysing historical atmospheric electricity data using a new data processing procedure based on the Carnegie curve, signals correlated with ENSO sea surface temperature (SST) anomalies are revealed. These demonstrate a persistent ENSO-GEC relationship for the majority of the twentieth century, in potential gradient data from Lerwick, Shetland and Watheroo, W. Australia. The recovered data is weighted towards the first half of the UTC day, giving a GEC sensitivity up to ∼5% °C-1 of SST anomaly in the Niño 3.4 and 4 regions of the Pacific Ocean. Transferring ENSO variability by electrical means represents an unexplored teleconnection, for example, through proposed GEC effects on stratiform cloud microphysics. The strong ENSO-GEC relationship also provides a quality test for historical atmospheric electricity data, and encourages their use in reducing SST reconstruction uncertainties.
| Item Type: | Article |
|---|---|
| Additional Information: | Data availability statement: The data that support the findings of this study are openly available, at https://doi.org/10.17864/1947.000409. The Pacific Ocean temperature anomalies were from https://climexp.knmi.nl/selectindex.cgi, data for figure 1(b) from Harrison (2013, 2022), and for figure 1(d) from NOAA/ESRL Physical Sciences Laboratory, Boulder, Colorado (http://psl.noaa.gov//). The Met Office and the Carnegie Institution of Washington originally obtained the PG data. Hasbur Yahaya helped with earlier analysis. R was used for the analysis (R Core Team 2021), with surrogateCor from the astrochron package used for statistical significance calculations. Funding Information: EH acknowledges support from the National Centre for Atmospheric Science and the NERC GloSAT project. |
| Uncontrolled Keywords: | enso,atmospheric electricity,potential gradient,teleconnection,renewable energy, sustainability and the environment,environmental science(all),public health, environmental and occupational health ,/dk/atira/pure/subjectarea/asjc/2100/2105 |
| Faculty \ School: | Faculty of Science > School of Environmental Sciences University of East Anglia Research Groups/Centres > Theme - ClimateUEA |
| UEA Research Groups: | University of East Anglia Schools > Faculty of Science > Tyndall Centre for Climate Change Research Faculty of Science > Research Centres > Tyndall Centre for Climate Change Research Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences Faculty of Science > Research Groups > Climatic Research Unit |
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| Depositing User: | LivePure Connector |
| Date Deposited: | 15 Dec 2022 03:57 |
| Last Modified: | 14 Jun 2023 14:11 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/90106 |
| DOI: | 10.1088/1748-9326/aca68c |
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