Modeling of CME and CIR driven geomagnetic storms by means of artificial neural networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985530%3A_____%2F15%3A00472536" target="_blank" >RIV/67985530:_____/15:00472536 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1515/congeo-2015-0013" target="_blank" >http://dx.doi.org/10.1515/congeo-2015-0013</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1515/congeo-2015-0013" target="_blank" >10.1515/congeo-2015-0013</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Modeling of CME and CIR driven geomagnetic storms by means of artificial neural networks

Popis výsledku v původním jazyce

A model of geomagnetic storms based on the method of artificial neural networks (ANN) combined with an analytical approach is presented in the paper. Two classes of geomagnetic storms, caused by coronal mass ejections (CMEs) and those caused by corotating interaction regions (CIRs), of medium and week intensity are subject to study. As the model input, the hourly solar wind parameters measured by the ACE satellite at the libration point L1 are used. The time series of the Dst index is obtained as the model output. The simulated Dst index series is compared with the corresponding observatory data. The model reliabilty is assessed using the skill scores, namely the correlation coefficient CC and the prediction efficiency PE. The results show that the model performance is better for the CME driven storms than for the CIR driven storms. At the same time, it appears that in the case of medium and weak storms the model performance is worse than in the case of intense storms.

Název v anglickém jazyce

Modeling of CME and CIR driven geomagnetic storms by means of artificial neural networks

Popis výsledku anglicky

A model of geomagnetic storms based on the method of artificial neural networks (ANN) combined with an analytical approach is presented in the paper. Two classes of geomagnetic storms, caused by coronal mass ejections (CMEs) and those caused by corotating interaction regions (CIRs), of medium and week intensity are subject to study. As the model input, the hourly solar wind parameters measured by the ACE satellite at the libration point L1 are used. The time series of the Dst index is obtained as the model output. The simulated Dst index series is compared with the corresponding observatory data. The model reliabilty is assessed using the skill scores, namely the correlation coefficient CC and the prediction efficiency PE. The results show that the model performance is better for the CME driven storms than for the CIR driven storms. At the same time, it appears that in the case of medium and weak storms the model performance is worse than in the case of intense storms.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

DE - Zemský magnetismus, geodesie, geografie

OECD FORD obor

—

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Contributions to Geophysics & Geodesy

ISSN

1335-2806

e-ISSN

—

Svazek periodika

45

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

SK - Slovenská republika

Počet stran výsledku

13

Strana od-do

53-65

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-84947800761