Cookies?
Library Header Image
LSE Research Online LSE Library Services

Using the aa index over the last 14 solar cycles to characterize extreme Geomagnetic activity

Chapman, S.C., Horne, R.B and Watkins, Nicholas W. ORCID: 0000-0003-4484-6588 (2020) Using the aa index over the last 14 solar cycles to characterize extreme Geomagnetic activity. Geophysical Research Letters, 47 (3). ISSN 0094-8276

[img] Text (Using the aa index over the last 14 solar cycles to characterize extreme Geomagnetic activity) - Published Version
Available under License Creative Commons Attribution.

Download (4MB)
Identification Number: 10.1029/2019GL086524

Abstract

Geomagnetic indices are routinely used to characterize space weather event intensity. The DST index is well resolved but is only available over five solar cycles. The aa index extends over 14 cycles but is highly discretized with poorly resolved extremes. We parameterize extreme aa activity by the annual-averaged top few percent of observed values, show that these are exponentially distributed, and they track annual DST index minima. This gives a 14-cycle average of ∼4% chance of at least one great (DST < −500 nT) storm and ∼28% chance of at least one severe (DST < −250 nT) storm per year. At least one DST = −809 [−663, −955] nT event in a given year would be a 1:151 year event. Carrington event estimate DST ∼−850nT is within the same distribution as other extreme activity seen in aa since 1868 so that its likelihood can be deduced from that of more moderate events. Events with DST ≲−1,000nT are in a distinct class, requiring special conditions.

Item Type: Article
Official URL: https://agupubs.onlinelibrary.wiley.com/journal/19...
Additional Information: © 2020 The Authors
Divisions: Centre for Analysis of Time Series
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Date Deposited: 14 Feb 2020 10:54
Last Modified: 16 Apr 2024 21:57
URI: http://eprints.lse.ac.uk/id/eprint/103389

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics