Improving the Electron Radiation Belt Nowcast and Forecast Using the SafeSpace Data Assimilation Modeling Pipeline

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378289%3A_____%2F23%3A00575014" target="_blank" >RIV/68378289:_____/23:00575014 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11320/23:10477702

Výsledek na webu

<a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022SW003377" target="_blank" >https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022SW003377</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1029/2022SW003377" target="_blank" >10.1029/2022SW003377</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Improving the Electron Radiation Belt Nowcast and Forecast Using the SafeSpace Data Assimilation Modeling Pipeline

Popis výsledku v původním jazyce

The H2020 SafeSpace project aims at the implementation of a space weather safety prototype, in particular to predict the deep charging hazard. The proposed service is built on a Sun-to-Earth chain of physical codes that propagates physical information and uncertainties in order to model the outer radiation belt dynamics. In this paper, we present the inner magnetosphere section of the SafeSpace pipeline that relies on solar wind driven and hourly updated models that describe the trapped electron environment (VLF waves, cold plasma and seed population densities), as well as the physical processes to which the trapped electrons are subjected to, such as radial diffusion and wave particle interactions. Then, this physical configuration is poured into the Salammbo-EnKF model, a data assimilation radiation belt model which provides a global forecast of the densities across the radiation belts. We have compared the forecasting performance of this new modeling pipeline to a reference model during the St. Patrick's Day storm in 2015. We show that the new SafeSpace implementation shows closer results to the observations in addition to a better forecast within the prediction horizon.

Název v anglickém jazyce

Improving the Electron Radiation Belt Nowcast and Forecast Using the SafeSpace Data Assimilation Modeling Pipeline

Popis výsledku anglicky

The H2020 SafeSpace project aims at the implementation of a space weather safety prototype, in particular to predict the deep charging hazard. The proposed service is built on a Sun-to-Earth chain of physical codes that propagates physical information and uncertainties in order to model the outer radiation belt dynamics. In this paper, we present the inner magnetosphere section of the SafeSpace pipeline that relies on solar wind driven and hourly updated models that describe the trapped electron environment (VLF waves, cold plasma and seed population densities), as well as the physical processes to which the trapped electrons are subjected to, such as radial diffusion and wave particle interactions. Then, this physical configuration is poured into the Salammbo-EnKF model, a data assimilation radiation belt model which provides a global forecast of the densities across the radiation belts. We have compared the forecasting performance of this new modeling pipeline to a reference model during the St. Patrick's Day storm in 2015. We show that the new SafeSpace implementation shows closer results to the observations in addition to a better forecast within the prediction horizon.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10305 - Fluids and plasma physics (including surface physics)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Space Weather-the International Journal of Research and Applications

ISSN

1542-7390

e-ISSN

1542-7390

Svazek periodika

21

Číslo periodika v rámci svazku

8

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

21

Strana od-do

e2022SW003377

Kód UT WoS článku

001050616300001

EID výsledku v databázi Scopus

2-s2.0-85168526994