[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 …
A computationally efficient, time-dependent model of the solar wind for use as a surrogate to three-dimensional numerical magnetohydrodynamic simulations
Near-Earth solar-wind conditions, including disturbances generated by coronal mass
ejections (CMEs), are routinely forecast using three-dimensional, numerical …
ejections (CMEs), are routinely forecast using three-dimensional, numerical …
[HTML][HTML] HUXt—An open source, computationally efficient reduced-physics solar wind model, written in Python
HUXt is an open source numerical model of the solar wind written in Python. It is based on
the solution of the 1D inviscid Burger's equation. This reduced-physics approach produces …
the solution of the 1D inviscid Burger's equation. This reduced-physics approach produces …
[HTML][HTML] Unifying the validation of ambient solar wind models
MA Reiss, K Muglach, R Mullinix… - Advances in Space …, 2023 - Elsevier
Progress in space weather research and awareness needs community-wide strategies and
procedures to evaluate our modeling assets. Here we present the activities of the Ambient …
procedures to evaluate our modeling assets. Here we present the activities of the Ambient …
A low-rank ensemble Kalman filter for elliptic observations
M Le Provost, R Baptista… - Proceedings of the …, 2022 - royalsocietypublishing.org
We propose a regularization method for ensemble Kalman filtering (EnKF) with elliptic
observation operators. Commonly used EnKF regularization methods suppress state …
observation operators. Commonly used EnKF regularization methods suppress state …
A variational approach to data assimilation in the solar wind
Variational data assimilation (DA) has enabled huge improvements in the skill of operational
weather forecasting. In this study, we use a simple solar‐wind propagation model to develop …
weather forecasting. In this study, we use a simple solar‐wind propagation model to develop …
Improving solar wind forecasting using data assimilation
Data Assimilation (DA) has enabled huge improvements in the skill of terrestrial operational
weather forecasting. In this study, we use a variational DA scheme with a computationally …
weather forecasting. In this study, we use a variational DA scheme with a computationally …
Research on the Effect of Data Assimilation for Three‐Dimensional MHD Simulation of Solar Wind
H Zhang, F Shen, Y Yang - Space Weather, 2023 - Wiley Online Library
As an important part of space weather forecasting, the prediction of solar wind parameters in
the near‐Earth space is particularly significant. The introduction of data assimilation (DA) …
the near‐Earth space is particularly significant. The introduction of data assimilation (DA) …
Ensemble CME modeling constrained by heliospheric imager observations
Predicting the arrival of coronal mass ejections (CMEs) is one key objective of space
weather forecasting. In operational space weather forecasting, solar wind numerical models …
weather forecasting. In operational space weather forecasting, solar wind numerical models …
Ensemble Kalman Filter Data Assimilation into the Surface Flux Transport Model to Infer Surface Flows: An Observing System Simulation Experiment
Abstract Knowledge of the global magnetic field distribution and its evolution on the Sun's
surface is crucial for modeling the coronal magnetic field, understanding the solar wind …
surface is crucial for modeling the coronal magnetic field, understanding the solar wind …