Removing local variability from Potential Gradient data – the Carnegie filter
- 1University of Reading, Meteorology, Reading, United Kingdom of Great Britain – England, Scotland, Wales (r.g.harrison@reading.ac.uk)
- 2School of Environmental Sciences, University of East Anglia. Norwich, Norfolk, NR4 7TJ, UK
- 3National Centre for Atmospheric Science, Department of Meteorology, University of Reading, UK
Measurements of atmospheric electricity have been made at many sites over a long time, with the vertical Potential Gradient (PG) the most commonly observed quantity. In general, the PG responds to local influences from weather, aerosol effects on charge exchange, and variability in the global atmospheric electric circuit. Different methods have been used to classify PG data, for example through identifying days when conditions were considered relatively undisturbed, or by using meteorological information to identify days on which weather-related variability was negligible. Nevertheless, local effects can persist, especially in data obtained at continental sites. Hence, if long term changes in the global atmospheric electric circuit are to be investigated, the local effects need first to be reduced or, ideally, removed.
Recent work has demonstrated a close relationship between the PG at some sites and ocean temperatures modulated by the El Niño Southern Oscillation, through the associated changes in the global atmospheric electric circuit ([1],[2], [3]). The expectation of such a relationship can be used to test methods of removing and reducing local effects in PG data. A method based on the Carnegie curve – the hourly variation known to be present in the global circuit – is discussed here. Through comparison of hourly PG data from a site with the Carnegie curve, outlier values lying beyond the usual range of global circuit changes can be identified and removed. The remaining data can then be used to construct new daily or monthly averages with reduced local variability, evaluated by comparison with global circuit changes associated with the El Niño Southern Oscillation.
References
[1] R.G. Harrison, K.A. Nicoll, M. Joshi, E. Hawkins: Empirical evidence for multidecadal scale Global Atmospheric Electric Circuit modulation by the El Niño-Southern Oscillation Environ Res Lett 17, 124048 (2022) https://iopscience.iop.org/article/10.1088/1748-9326/aca68c
[2] N.N. Slyunyaev, N.V.I lin, , E.A. Mareev,.G. Price: A new link between El Nino - Southern Oscillation and atmospheric electricity, Environ. Res. Lett., 16, (2021) https://doi.org/10.1088/1748-9326/abe908
[3] R.G. Harrison, M. Joshi, K. Pascoe: Inferring convective responses to El Niño with atmospheric electricity measurements at Shetland Environ Res Lett 6 (2011) 044028 http://iopscience.iop.org/1748-9326/6/4/044028/
How to cite: Harrison, R. G., Nicoll, K., Joshi, M., and Hawkins, E.: Removing local variability from Potential Gradient data – the Carnegie filter, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14440, https://doi.org/10.5194/egusphere-egu23-14440, 2023.
