scholarly journals Solar wind-magnetosphere-ionosphere coupling: Signal arrival time and perturbation relations

2002 ◽  
Vol 107 (A11) ◽  
Author(s):  
P. Song
Keyword(s):  
Solar Wind ◽  
Arrival Time ◽  
Signal Arrival

scholarly journals An operational solar wind prediction system transitioning fundamental science to operations

2018 ◽  
Vol 8 ◽  
pp. A39 ◽  
Author(s):  
Jingjing Wang ◽  
Xianzhi Ao ◽  
Yuming Wang ◽  
Chuanbing Wang ◽  
Yanxia Cai ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Solar Wind ◽  
Arrival Time ◽  
Space Environment ◽  
Maximum Speed ◽  
Source Surface ◽  
Prediction System ◽  
Fundamental Science ◽  
Cone Model ◽  
The Mean

We present in this paper an operational solar wind prediction system. The system is an outcome of the collaborative efforts between scientists in research communities and forecasters at Space Environment Prediction Center (SEPC) in China. This system is mainly composed of three modules: (1) a photospheric magnetic field extrapolation module, along with the Wang-Sheeley-Arge (WSA) empirical method, to obtain the background solar wind speed and the magnetic field strength on the source surface; (2) a modified Hakamada-Akasofu-Fry (HAF) kinematic module for simulating the propagation of solar wind structures in the interplanetary space; and (3) a coronal mass ejection (CME) detection module, which derives CME parameters using the ice-cream cone model based on coronagraph images. By bridging the gap between fundamental science and operational requirements, our system is finally capable of predicting solar wind conditions near Earth, especially the arrival times of the co-rotating interaction regions (CIRs) and CMEs. Our test against historical solar wind data from 2007 to 2016 shows that the hit rate (HR) of the high-speed enhancements (HSEs) is 0.60 and the false alarm rate (FAR) is 0.30. The mean error (ME) and the mean absolute error (MAE) of the maximum speed for the same period are −73.9 km s−1 and 101.2 km s−1, respectively. Meanwhile, the ME and MAE of the arrival time of the maximum speed are 0.15 days and 1.27 days, respectively. There are 25 CMEs simulated and the MAE of the arrival time is 18.0 h.

scholarly journals Validation of Coronal Mass Ejection Arrival-Time Forecasts by Magnetohydrodynamic Simulations based on Interplanetary Scintillation Observations

2020 ◽  
Author(s):  
Kazumasa Iwai ◽  
Daikou Shiota ◽  
Munetoshi Tokumaru ◽  
Ken'ichi Fujiki ◽  
Mitsue Den ◽  
...  
Keyword(s):  
Solar Wind ◽  
Arrival Time ◽  
Interplanetary Space ◽  
Three Dimensional ◽  
Space Environment ◽  
Environmental Research ◽  
Interplanetary Scintillation ◽  
Arrival Times ◽  
Mhd Simulations ◽  
Magnetohydrodynamic Simulations

Abstract Coronal mass ejections (CMEs) cause various disturbances of the space environment; therefore, forecasting their arrival time is very important. However, forecasting accuracy is hindered by limited CME observations in interplanetary space. This study investigates the accuracy of CME arrival times at the Earth forecasted by three-dimensional (3D) magnetohydrodynamic (MHD) simulations based on interplanetary scintillation (IPS) observations. In this system, CMEs are approximated as spheromaks with various initial speeds. Ten MHD simulations with different CME initial speed are tested, and the density distributions derived from each simulation run are compared with IPS data observed by the Institute for Space-Earth Environmental Research (ISEE), Nagoya University. The CME arrival time of the simulation run that most closely agrees with the IPS data is selected as the forecasted time. We then validate the accuracy of this forecast using 12 halo CME events. The average absolute arrival-time error of the IPS-based MHD forecast is approximately 5.0 h, which is one of the most accurate predictions that ever been validated, whereas that of MHD simulations without IPS data, in which the initial CME speed is derived from white-light coronagraph images, is approximately 6.7 h. This suggests that the assimilation of IPS data into MHD simulations can improve the accuracy of CME arrival-time forecasts. The average predicted arrival times are earlier than the actual arrival times. These early predictions may be due to overestimation of the magnetic field included in the spheromak and/or underestimation of the drag force from the background solar wind, the latter of which could be related to underestimation of CME size or background solar wind density.

scholarly journals Validation of Coronal Mass Ejection Arrival-time Forecasts by Magnetohydrodynamic Simulations Based on Interplanetary Scintillation Observations

2020 ◽  
Author(s):  
Kazumasa Iwai ◽  
Daikou Shiota ◽  
Munetoshi Tokumaru ◽  
Ken'ichi Fujiki ◽  
Mitsue Den ◽  
...  
Keyword(s):  
Solar Wind ◽  
Arrival Time ◽  
Interplanetary Space ◽  
Three Dimensional ◽  
Space Environment ◽  
Environmental Research ◽  
Interplanetary Scintillation ◽  
Arrival Times ◽  
Mhd Simulations ◽  
Magnetohydrodynamic Simulations

Abstract Coronal mass ejections (CMEs) cause various disturbances of the space environment; therefore, forecasting their arrivaltime is very important.However,forecasting accuracy is hindered by limited CME observations in interplanetary space. This study investigates the accuracy of CME arrivaltimesat the Earth forecasted by three-dimensional(3D) magnetohydrodynamic (MHD) simulations based on interplanetary scintillation (IPS) observations. In this system, CMEs are approximated as spheromakswith various initial speeds. TenMHD simulations with different CME initial speed are tested, and the density distributions derived from each simulation run are compared with IPS data observed by the Institute for Space-Earth Environmental Research (ISEE), Nagoya University.The CME arrivaltime of the simulation run that most closelyagrees with the IPS data is selected as the forecasted time. We then validate the accuracy of this forecast using 12 halo CME events. The average absolute arrival-time error of theIPS-based MHD forecast is approximately 5.0 h, which is one of the most accurate predictions that ever been validated, whereasthat of MHD simulations without IPS data, in which the initial CME speed isderived from white-light coronagraph images, is approximately6.7 h. This suggests that the assimilation of IPS data into MHD simulations can improve the accuracy of CME arrival-time forecasts. The average predicted arrivaltimes are earlier than the actual arrival times. These early predictions may be duetooverestimation of the magnetic field included in the spheromak and/or underestimation of the drag force from the background solar wind, the latter of which could be related to underestimation of CME size or background solar wind density.

CME arrival time predictions with a deformable front

2021 ◽  
Author(s):  
Jürgen Hinterreiter ◽  
Tanja Amerstorfer ◽  
Martin A. Reiss ◽  
Andreas J. Weiss ◽  
Christian Möstl ◽  
...  
Keyword(s):  
Solar Wind ◽  
Large Scale ◽  
Arrival Time ◽  
Interplanetary Space ◽  
Solar Wind Speed ◽  
Model Combination ◽  
First Results ◽  
Good Agreement ◽  
Ambient Solar Wind

<p>We present the first results of our newly developed CME arrival prediction model, which allows the CME front to deform and adapt to the changing solar wind conditions. Our model is based on ELEvoHI and makes use of the WSA/HUX (Wang-Sheeley-Arge/Heliospheric Upwind eXtrapolation) model combination, which computes large-scale ambient solar wind conditions in the interplanetary space. With an estimate of the solar wind speed and density, we are able to account for the drag exerted on different parts of the CME front. Initially, our model relies on heliospheric imager observations to confine an elliptical CME front and to obtain an initial speed and drag parameter for the CME. After a certain distance, each point of the CME front is propagating based on the conditions in the heliosphere. In this case study, we compare our results to previous arrival time predictions using ELEvoHI with a rigid CME front. We find that the actual arrival time at Earth and the arrival time predicted by the new model are in very good agreement.</p>

Improving CME modelling with data assimilation of Heliospheric Imager observations into the HUXt solar wind numerical model.

2021 ◽  
Author(s):  
Luke Barnard ◽  
Mat Owens ◽  
Chris Scott ◽  
Matt Lang
Keyword(s):  
Solar Wind ◽  
Data Assimilation ◽  
Particle Filter ◽  
Space Weather ◽  
Arrival Time ◽  
Observation Data ◽  
Stereo Mission ◽  
Predictive Skill ◽  
Early Results ◽  
Heliospheric Imager

<p>Coronal Mass Ejections that impact Earth drive the most severe space weather. To better enable effective space weather mitigation plans, there is much interest in improving the quality of CME arrival time predictions, particularly by quantifying and reducing the prediction uncertainty. A limited set of observatories, challenges in interpreting observation data, and limiting assumptions in CME parameterisations all play important roles in the uncertainty of the predicted CME evolution.</p><p>Data assimilation techniques provide a path for improving the predictive skill, by integrating observations into a modelling framework in a way that returns model states that better reflect the true state of a system. Furthermore, such techniques can self-consistently account for uncertainty in the observations, and uncertainty in the models structure and parameterisations.</p><p>We present some early results from our work to build a particle filter data assimilation scheme around the HUXt solar wind model. Assimilating the time-elongation profiles of CME flanks observed by the Heliospheric Imagers on NASAs STEREO mission, we demonstrate that such methods have good potential to improve modelled CME arrival time predictions. Using a simulation study, we present an estimate of the potential CME arrival time prediction improvements gained by using this particle-filter approach with an L5 Heliospheric Imager.</p>

scholarly journals DOI estimation through signal arrival time distribution: a theoretical description including proof of concept measurements

2021 ◽  
Author(s):  
Francis Loignon-Houle ◽  
Stefan Gundacker ◽  
Maxime Toussaint ◽  
Félix Camirand Lemyre ◽  
Etiennette Auffray ◽  
...  
Keyword(s):  
Time Distribution ◽  
Arrival Time ◽  
Theoretical Description ◽  
Arrival Time Distribution ◽  
Proof Of Concept ◽  
Signal Arrival
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