An upgrade of the solar-wind-driven empirical model for the middle latitude ionospheric storm-time response

Tsagouri, I.; Belehaki, Anna

doi:10.1016/j.jastp.2008.09.010

Cited by 38 publications

(34 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To analyse the effect of geomagnetic storms on LDM-TEC time disturbances, we investigated the differences between our climatological LDM-TEC model and the observations for the 69 storm onsets identified (Tsagouri & Belehaki 2008) during the period 1998-2005 (Fig. 13).…”

Section: Effect Of Geomagnetic Storms On the Tecmentioning

confidence: 99%

“…Red: when the leastsquares adjustment is performed for the different solar cycle phases. & Belehaki 2008;Tsagouri et al 2009). According to these results, the geomagnetic storm onset follows the storm onset at L1 point with a delay that ranges from 2 to 12 h, while the ionospheric disturbances may last from 10 to 40 h depending on the local time of the observation point at the storm onset.…”

Section: Effect Of Geomagnetic Storms On the Tecmentioning

confidence: 99%

See 1 more Smart Citation

The influence of space weather on ionospheric total electron content during the 23rd solar cycle

Bergeot

Tsagouri

Bruyninx

et al. 2013

J. Space Weather Space Clim.

View full text Add to dashboard Cite

This paper presents a new empirical model for predicting the daily mean ionospheric Total Electron Content (TEC) at a given latitude from only one solar index as input. For the development of the model we take advantage of the availability of 15 years of global GNSS-based TEC information and solar indices (Sunspot Number, F10.7 and derived F10.7P) including the 23rd solar cycle. Among all the tests, our preferred ionospheric climatological model to predict daily mean TEC presents yearly median differences with observed values of 1.4 ± 0.9 TECu (11.5 ± 2.9% for the relative differences) with no significant degradation during the different phases of the solar cycle. To realize this empirical model we used a least-square adjustment with (1) a combination of linear, annual and semi-annual terms between the TEC and F10.7P; (2) a discretization with respect to the phases of the solar cycle. The main differences between the modelled and the observed TEC occur during identified geomagnetic storms: the maximum differences (À3.2 ± 1.5 TECu) and relative differences (À19.6 ± 15.0%) occur one day after the storm onset. The typical time to retrieve the pre-storm conditions is 3-4 days after the onset. These results show a global picture of the effect of extreme Space Weather events on the Earth's upper atmosphere.

show abstract

Section: Effect Of Geomagnetic Storms On the Tecmentioning

confidence: 99%

Section: Effect Of Geomagnetic Storms On the Tecmentioning

confidence: 99%

The influence of space weather on ionospheric total electron content during the 23rd solar cycle

Bergeot

Tsagouri

Bruyninx

et al. 2013

J. Space Weather Space Clim.

View full text Add to dashboard Cite

show abstract

“…a general probabilistic forecast on the likelihood of solar events given the current Solar Weather conditions). In addition, Solar Weather ESC products are often digested by other Centres that, based on their subsequent expertise in the physical systems impacted, further specify and predict the more precise characteristics of these impacts [16][17][18][19][20]. …”

Section: Services and User Typesmentioning

confidence: 99%

“…[14], Upper right: NMA S4 map [15], lower left: NMA TEC map [15], lower right: NOA Now-cast foF2 map [16][17][18]. Figure 12 shows an illustration included in the space weather bulletin tailored for the Venus Express aero braking operations.…”

Section: Tailoring Of Space Weather Productsmentioning

confidence: 99%

Services for Space Mission Support Within The ESA Space Situational Awareness Space Weather Service Network

Donder¹,

Crosby²,

Kruglanski³

et al. 2017

J Aeronaut Aerospace Eng

View full text Add to dashboard Cite

Spacecraft operations are by nature complex and every satellite's operational environment poses a range of potential risks, often a unique combination for a given orbit. The implications of interruptions of operations, data transfer and service provision, are serious, both in terms of cost and capability, thus it is imperative to mitigate against all operational risks to the fullest extent possible.In the frame of its Space Situational Awareness (SSA) programme, the European Space Agency (ESA) is establishing a Space Weather Service Network to support end-users, in a wide range of affected sectors, in mitigating the effects of space weather on their systems, reducing costs and improving reliability. This service network is currently in a test and validation phase and encourages user engagement and feedback.The network is organised around five Expert Service Centres (ESCs) focusing on Solar Weather, Heliospheric Weather, Space Radiation Environment, Ionospheric Weather and Geomagnetic Conditions. Each ESC is connecting different expert groups, federating their space weather products, and ensuring the quality and consistency of the provided information. The service network also includes a central Data Centre and the SSA Space Weather Coordination Centre (SSCC).In this presentation we give an overview of the current status of the network (http://swe.ssa.esa.int/), the targeted end-user groups and Expert Service Centres with a focus on the space community.

show abstract

“…Recent studies encourage the involvement of more efficient physical drivers like AE or IMF‐Bz component in ionospheric forecasting modeling [ Mikhailov et al , 2007]. In this framework, the combination of TSAR's predictions with the output of the empirical Storm Time Ionospheric Model (STIM) recently proposed by Tsagouri and Belehaki [2008, 2006] can yield improved results especially for storm time predictions more than one hour ahead. STIM is designed to introduce a storm time correction factor to the quiet diurnal ionospheric variation, based on the solar wind conditions in the Earth's vicinity monitored by NASA Advance Composition Explorer (ACE) spacecraft.…”

Section: Introductionmentioning

confidence: 99%

Ionospheric foF2 forecast over Europe based on an autoregressive modeling technique driven by solar wind parameters

2009

Self Cite

View full text Add to dashboard Cite

[1] The development of a new ionospheric forecasting algorithm, called the Solar Wind driven autoregression model for Ionospheric short-term Forecast (SWIF) is presented. SWIF combines historical and real-time ionospheric observations with solar wind parameters obtained in real time at the L1 point. This is achieved through the cooperation of an autoregression forecasting algorithm, called Time Series AutoRegressive (TSAR), with the empirical Storm Time Ionospheric Model that formulates the ionospheric storm time response based on solar wind input. The evaluation of SWIF's predictions was principally focused on its performance during selected storm time intervals over Europe. The results demonstrate significant improvement of SWIF's prediction capability over its predecessor, TSAR, significant improvement over climatology and evidence of SWIF's efficiency compared to other forecasting methods. Moreover, the evaluation of SWIF's output over long time periods, that include a wide range of geophysical conditions, suggests that SWIF can be used for prediction up to 24 h ahead.Citation: Tsagouri, I., K. Koutroumbas, and A. Belehaki (2009), Ionospheric foF2 forecast over Europe based on an autoregressive modeling technique driven by solar wind parameters, Radio Sci., 44, RS0A35,

show abstract

An upgrade of the solar-wind-driven empirical model for the middle latitude ionospheric storm-time response

Cited by 38 publications

References 51 publications

The influence of space weather on ionospheric total electron content during the 23rd solar cycle

The influence of space weather on ionospheric total electron content during the 23rd solar cycle

Services for Space Mission Support Within The ESA Space Situational Awareness Space Weather Service Network

Ionospheric foF2 forecast over Europe based on an autoregressive modeling technique driven by solar wind parameters

Contact Info

Product

Resources

About