Preprints
https://doi.org/10.5194/nhess-2017-367
https://doi.org/10.5194/nhess-2017-367
07 Nov 2017
 | 07 Nov 2017
Status: this discussion paper is a preprint. It has been under review for the journal Natural Hazards and Earth System Sciences (NHESS). The manuscript was not accepted for further review after discussion.

Defining scale thresholds for geomagnetic storms through statistics

Judith Palacios, Antonio Guerrero, Consuelo Cid, Elena Saiz, and Yolanda Cerrato

Abstract. Geomagnetic storms, as part of the Sun-Earth relations, are continuously monitored with different indices and scales. These indices have some scale thresholds to quantify the severity or risk of geomagnetic disturbances. However, the most usual scale thresholds are arbitrarily chosen. In this work we aim to quantify the range of the thresholds through a new method. These new thresholds are based on statistical distribution fitting.

The data used are from a regional real-time high-cadence geomagnetic index, named LDiñ, and its derivative, LCiñ. We considered the negative part of LDiñ, as significant for geomagnetic disturbances; and the absolute value of LCiñ, significant for geomagnetically induced currents. Then we look for the best fit for different statistical continuous distributions applied to these indices.

The method yields that the beta prime is the most suitable functions for negative values of LDiñ, whereas power-law and Johnson-SU are the best fits for LCiñ and the whole distribution, respectively. We define new thresholds for intense, very intense and extreme geomagnetic disturbances as the intersects between these best fit distributions and the index complementary cumulative distribution function.

Then, thresholds for the negative part of LDiñ, are −100 nT, −205 and −475 nT. The thresholds for the absolute value of LCiñ, are 6, 18 and 32 nT min−1. The thresholds defined here provide criteria to assess the vulnerability to geomagnetic activity on design or mitigation purposes.

These threshold definitions will be applied for different products in the Spanish Space Weather Service (SeNMEs) website http://www.senmes.es/index-en.php.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Judith Palacios, Antonio Guerrero, Consuelo Cid, Elena Saiz, and Yolanda Cerrato
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Judith Palacios, Antonio Guerrero, Consuelo Cid, Elena Saiz, and Yolanda Cerrato
Judith Palacios, Antonio Guerrero, Consuelo Cid, Elena Saiz, and Yolanda Cerrato

Viewed

Total article views: 1,211 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
813 341 57 1,211 71 71
  • HTML: 813
  • PDF: 341
  • XML: 57
  • Total: 1,211
  • BibTeX: 71
  • EndNote: 71
Views and downloads (calculated since 07 Nov 2017)
Cumulative views and downloads (calculated since 07 Nov 2017)

Viewed (geographical distribution)

Total article views: 1,163 (including HTML, PDF, and XML) Thereof 1,158 with geography defined and 5 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 17 Nov 2024
Download
Short summary
Geomagnetic storms are continuously monitored with different indices and scales. These indices have some scale thresholds to quantify the severity or risk of geomagnetic disturbances. However, the most usual scale thresholds are arbitrarily chosen. In this work we aim to quantify the range of the storm thresholds through a new method. These new thresholds are based on statistical distribution fitting. The provided insight can improve risk assessment on this particular natural hazard.
Altmetrics