PREDSTORM AND SOLARWIND2GIC: FORECASTING OF SPACE WEATHER EFFECTS AND GICS WITH PYTHON

Rachel Louise Bailey; C Möstl; U. V. Amerstorfer; T.  Amerstorfer; A. J.  Weiss; J. Hinterreiter; M. A.  Reiss; Dennis Albert

PREDSTORM AND SOLARWIND2GIC: FORECASTING OF SPACE WEATHER EFFECTS AND GICS WITH PYTHON

Rachel Louise Bailey, C Möstl, U. V. Amerstorfer, T. Amerstorfer, A. J. Weiss, J. Hinterreiter, M. A. Reiss, Dennis Albert

Institute of Electrical Power Systems (4320)

Research output: Contribution to conference › Poster › peer-review

Abstract

PREDSTORM is a package developed as part of the project “Enhanced
lead time for geomagnetic storms”. The aim is to build a framework that
will provide a forecast of the solar wind at the L1 point using a
combination of empirical and machine learning methods. Among the
properties that can then be predicted from the L1 data are the
geomagnetic Dst index and the magnitudes of GICs in power grids.

Original language	English
Number of pages	1
Publication status	Published - 2019
Event	Machine Learning in Heliophysics - The Royal Tropical Institute - Koninklijk Instituut voor de Tropen (KIT), Amsterdam, Netherlands Duration: 16 Sept 2019 → 20 Sept 2019 https://ml-helio.github.io/

Conference

Conference	Machine Learning in Heliophysics
Abbreviated title	ML-Helio
Country/Territory	Netherlands
City	Amsterdam
Period	16/09/19 → 20/09/19
Internet address	https://ml-helio.github.io/

Keywords

Solar Wind
Space Weather
Forecast
GIC
Geomagnetically Induced Currents
Low Frequency Currents
LFC

ASJC Scopus subject areas

Earth and Planetary Sciences(all)

Treatment code (Nähere Zuordnung)

Application

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

1 Finished

Nf-Sternpunkt 2 - Low-frequency transformer neutral currents
Renner, H., Schachinger, P., Wohlfart, P. & Albert, D.
1/06/19 → 31/05/22
Project: Research project

3 Workshop, seminar or course (Participation in/Organisation of)
2 Poster presentation
1 Invited talk

Space Weather Workshop 2021
Dennis Albert (Participant), Philipp Schachinger (Participant) & Rachel Louise Bailey (Participant)
20 Apr 2021 → 22 Apr 2021
Activity: Participation in or organisation of › Workshop, seminar or course (Participation in/Organisation of)
ETG Kongress 2021
Dennis Albert (Participant)
18 May 2021 → 19 May 2021
Activity: Participation in or organisation of › Workshop, seminar or course (Participation in/Organisation of)
Geomagnetically Induced Currents and Space Weather Prediction in Austria
Dennis Albert (Speaker), Philipp Schachinger (Speaker) & Rachel Louise Bailey (Speaker)
22 Apr 2021
Activity: Talk or presentation › Poster presentation › Science to science

Elektrische Netze: Stürmische Gefahr für das Stromnetz
Dennis Albert
23/12/20
1 item of Media coverage
Press/Media: Press / Media

Cite this

@conference{0cd6311439604a778865021db35deb34,

title = "PREDSTORM AND SOLARWIND2GIC: FORECASTING OF SPACE WEATHER EFFECTS AND GICS WITH PYTHON",

abstract = "PREDSTORM is a package developed as part of the project “Enhancedlead time for geomagnetic storms”. The aim is to build a framework thatwill provide a forecast of the solar wind at the L1 point using acombination of empirical and machine learning methods. Among theproperties that can then be predicted from the L1 data are thegeomagnetic Dst index and the magnitudes of GICs in power grids.",

keywords = "Solar Wind, Space Weather, Forecast, GIC, Geomagnetically Induced Currents, Low Frequency Currents, LFC",

author = "Bailey, {Rachel Louise} and C M{\"o}stl and Amerstorfer, {U. V.} and T. Amerstorfer and Weiss, {A. J.} and J. Hinterreiter and Reiss, {M. A.} and Dennis Albert",

year = "2019",

language = "English",

note = "Machine Learning in Heliophysics, ML-Helio ; Conference date: 16-09-2019 Through 20-09-2019",

url = "https://ml-helio.github.io/",

}

TY - CONF

T1 - PREDSTORM AND SOLARWIND2GIC: FORECASTING OF SPACE WEATHER EFFECTS AND GICS WITH PYTHON

AU - Bailey, Rachel Louise

AU - Möstl, C

AU - Amerstorfer, U. V.

AU - Amerstorfer, T.

AU - Weiss, A. J.

AU - Hinterreiter, J.

AU - Reiss, M. A.

AU - Albert, Dennis

PY - 2019

Y1 - 2019

N2 - PREDSTORM is a package developed as part of the project “Enhancedlead time for geomagnetic storms”. The aim is to build a framework thatwill provide a forecast of the solar wind at the L1 point using acombination of empirical and machine learning methods. Among theproperties that can then be predicted from the L1 data are thegeomagnetic Dst index and the magnitudes of GICs in power grids.

AB - PREDSTORM is a package developed as part of the project “Enhancedlead time for geomagnetic storms”. The aim is to build a framework thatwill provide a forecast of the solar wind at the L1 point using acombination of empirical and machine learning methods. Among theproperties that can then be predicted from the L1 data are thegeomagnetic Dst index and the magnitudes of GICs in power grids.

KW - Solar Wind

KW - Space Weather

KW - Forecast

KW - GIC

KW - Geomagnetically Induced Currents

KW - Low Frequency Currents

KW - LFC

M3 - Poster

T2 - Machine Learning in Heliophysics

Y2 - 16 September 2019 through 20 September 2019

ER -

PREDSTORM AND SOLARWIND2GIC: FORECASTING OF SPACE WEATHER EFFECTS AND GICS WITH PYTHON

Abstract

Conference

Keywords

ASJC Scopus subject areas

Treatment code (Nähere Zuordnung)

UN SDGs

Fingerprint

Projects

Nf-Sternpunkt 2 - Low-frequency transformer neutral currents

Activities

Space Weather Workshop 2021

ETG Kongress 2021

Geomagnetically Induced Currents and Space Weather Prediction in Austria

Press/Media

Elektrische Netze: Stürmische Gefahr für das Stromnetz

Cite this