The Geomagnetic Kp Index and Derived Indices of Geomagnetic Activity
J Matzka, C Stolle, Y Yamazaki, O Bronkalla… - Space …, 2021 - Wiley Online Library
The geomagnetic Kp index is one of the most extensively used indices of geomagnetic
activity, both for scientific and operational purposes. This article reviews the properties of the …
activity, both for scientific and operational purposes. This article reviews the properties of the …
Complex systems methods characterizing nonlinear processes in the near-earth electromagnetic environment: Recent advances and open challenges
G Balasis, MA Balikhin, SC Chapman… - Space Science …, 2023 - Springer
Learning from successful applications of methods originating in statistical mechanics,
complex systems science, or information theory in one scientific field (eg, atmospheric …
complex systems science, or information theory in one scientific field (eg, atmospheric …
The challenge of machine learning in space weather: Nowcasting and forecasting
E Camporeale - Space weather, 2019 - Wiley Online Library
The numerous recent breakthroughs in machine learning make imperative to carefully
ponder how the scientific community can benefit from a technology that, although not …
ponder how the scientific community can benefit from a technology that, although not …
Cycle slip detection and repair for undifferenced GPS observations under high ionospheric activity
C Cai, Z Liu, P Xia, W Dai - GPS solutions, 2013 - Springer
We develop a new approach for cycle slip detection and repair under high ionospheric
activity using undifferenced dual-frequency GPS carrier phase observations. A forward and …
activity using undifferenced dual-frequency GPS carrier phase observations. A forward and …
Multiple‐hour‐ahead forecast of the Dst index using a combination of long short‐term memory neural network and Gaussian process
MA Gruet, M Chandorkar, A Sicard… - Space …, 2018 - Wiley Online Library
In this study, we present a method that combines a Long Short‐Term Memory (LSTM)
recurrent neural network with a Gaussian process (GP) model to provide up to 6‐hr‐ahead …
recurrent neural network with a Gaussian process (GP) model to provide up to 6‐hr‐ahead …
[图书][B] Machine learning techniques for space weather
Machine Learning Techniques for Space Weather provides a thorough and accessible
presentation of machine learning techniques that can be employed by space weather …
presentation of machine learning techniques that can be employed by space weather …
The physics of space weather/solar-terrestrial physics (STP): what we know now and what the current and future challenges are
Major geomagnetic storms are caused by unusually intense solar wind southward magnetic
fields that impinge upon the Earth's magnetosphere (Dungey, 1961). How can we predict the …
fields that impinge upon the Earth's magnetosphere (Dungey, 1961). How can we predict the …
Information theoretical approach to discovering solar wind drivers of the outer radiation belt
The solar wind‐magnetosphere system is nonlinear. The solar wind drivers of
geosynchronous electrons with energy range of 1.8–3.5 MeV are investigated using mutual …
geosynchronous electrons with energy range of 1.8–3.5 MeV are investigated using mutual …
Model evaluation guidelines for geomagnetic index predictions
Geomagnetic indices are convenient quantities that distill the complicated physics of some
region or aspect of near‐Earth space into a single parameter. Most of the best‐known …
region or aspect of near‐Earth space into a single parameter. Most of the best‐known …
Neural networks for operational SYM‐H forecasting using attention and SWICS plasma features
In this work, we present an Artificial Neural Network for operational forecasting of the SYM‐H
geomagnetic index up to 2 hr ahead using the Interplanetary Magnetic Field, the solar wind …
geomagnetic index up to 2 hr ahead using the Interplanetary Magnetic Field, the solar wind …