Improving solar wind forecasts using data assimilation

Lang, Matthew; Owens, M. J.; Lawless, Amos S.

doi:10.5194/egusphere-egu2020-10909

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…Examples of these fields are meteorology and oceanography, and, in space sciences, ionospheric and radiation belt physics (Bennett, 1992;Ghil and Malanotte-Rizzoli, 1991;Egbert and Bennett, 1996;Kalnay, 2003;Rigler et al, 2004;Schunk et al, 2004;Kondrashov et al, 2007). Examples of DA applications targeting specifically the interplanetary space environments are Schrijver and DeRosa (2003), Mendoza et al (2006), , Innocenti et al (2011), Skandrani et al (2014), Lang and Owens (2019), and Lang et al (2020).…”

Section: Fundingmentioning

confidence: 99%

Data-driven MHD: Novel Applications to the Solar Atmosphere

2021

Frontiers Research Topics

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Frontiers is more than just an open-access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers Journal SeriesThe Frontiers Journal Series is a multi-tier and interdisciplinary set of open-access, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. At the same time, the Frontiers Journal Series operates on a revolutionary invention, the tiered publishing system, initially addressing specific communities of scholars, and gradually climbing up to broader public understanding, thus serving the interests of the lay society, too. Dedication to QualityEach Frontiers article is a landmark of the highest quality, thanks to genuinely collaborative interactions between authors and review editors, who include some of the world's best academicians. Research must be certified by peers before entering a stream of knowledge that may eventually reach the public -and shape society; therefore, Frontiers only applies the most rigorous and unbiased reviews. Frontiers revolutionizes research publishing by freely delivering the most outstanding research, evaluated with no bias from both the academic and social point of view. By applying the most advanced information technologies, Frontiers is catapulting scholarly publishing into a new generation.

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Section: Fundingmentioning

confidence: 99%

Data-driven MHD: Novel Applications to the Solar Atmosphere

2021

Frontiers Research Topics

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“…Examples of these fields are meteorology and oceanography, and, in space sciences, ionospheric and radiation belt physics (Bennett, 1992;Ghil and Malanotte-Rizzoli, 1991;Egbert and Bennett, 1996;Kalnay, 2003;Rigler et al, 2004;Schunk et al, 2004;Kondrashov et al, 2007). Examples of DA applications targeting specifically the interplanetary space environments are Schrijver and DeRosa (2003); Mendoza et al (2006); Arge et al (2010); Innocenti et al (2011); Skandrani et al (2014); ; ; Lang et al (2020).…”

Section: Introductionmentioning

confidence: 99%

Domain of Influence analysis: implications for Data Assimilation in space weather forecasting

Millas¹,

Innocenti²,

Laperre³

et al. 2020

Preprint

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Solar activity, ranging from the background solar wind to energetic coronal mass ejections (CMEs), is the main driver of the conditions in the interplanetary space and in the terrestrial space environment, known as space weather. A better understanding of the Sun-Earth connection carries enormous potential to mitigate negative space weather effects with economic and social benefits. Effective space weather forecasting relies on data and models. In this paper, we discuss some of the most used space weather models, and propose suitable locations for data gathering with space weather purposes. We report on the application of Representer analysis (RA) and Domain of Influence (DOI) analysis to three models simulating different stages of the Sun-Earth connection: the OpenGGCM and Tsyganenko models, focusing on solar wind -magnetosphere interaction, and the PLUTO model, used to simulate CME propagation in interplanetary space. Our analysis is promising for space weather purposes for several reasons. First, we obtain quantitative information about the most useful locations of observation points, such as solar wind monitors. For example, we find that the absolute values of the DOI are extremely low in the magnetospheric plasma sheet. Since knowledge of that particular sub-system is crucial for space weather, enhanced monitoring of the region would be most beneficial. Second, we are able to better characterize the models. Although the current analysis focuses on spatial rather than temporal correlations, we find that time-independent models are less useful for Data Assimilation activities than time-dependent models. Third, we take the first steps towards the ambitious goal of identifying the most relevant heliospheric parameters for modelling CME propagation in the heliosphere, their arrival time, and their geoeffectiveness at Earth.

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Improving solar wind forecasts using data assimilation

Cited by 2 publications

References 33 publications

Data-driven MHD: Novel Applications to the Solar Atmosphere

Data-driven MHD: Novel Applications to the Solar Atmosphere

Domain of Influence analysis: implications for Data Assimilation in space weather forecasting

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