Related papers: Predictive Modeling of Coronal Hole Areas Using Lo…
This paper reviews the current state of our understanding of high-speed solar wind acceleration in coronal holes. Observations by SOHO, coupled with interplanetary particle measurements going back several decades, have put strong…
The continuous observation of the magnetic field by Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) produces numerous image sequences in time and space. These sequences provide data support for predicting the…
We developed Long Short-Term Memory (LSTM) models to predict the formation of active regions (ARs) on the solar surface. Using the Doppler shift velocity, the continuum intensity, and the magnetic field observations from the Solar Dynamics…
We investigate the relationship between solar coronal holes and open-field regions using three-dimensional radiative magnetohydrodynamic (MHD) simulations combined with remote-sensing observations from the Solar Dynamics Observatory (SDO).…
Global magnetic field models use as input synoptic data, which usually show "aging effects" as the longitudinal 360{\deg} information is not obtained simultaneously. Especially during times of increased solar activity, the evolution of the…
The coronal magnetic field directly or indirectly affects a majority of the phenomena studied in space physics. It provides energy for coronal heating, controls the release of coronal mass ejections (CMEs), and drives heliospheric and…
This paper reviews our growing understanding of the physics behind coronal heating (in open-field regions) and the acceleration of the solar wind. Many new insights have come from the last solar cycle's worth of observations and theoretical…
The occlusion of the sun by clouds is one of the primary sources of uncertainties in solar power generation, and is a factor that affects the wide-spread use of solar power as a primary energy source. Real-time forecasting of cloud movement…
Coronal holes (CH) are regions of open magnetic fields that appear as dark areas in the solar corona due to their low density and temperature compared to the surrounding quiet corona. To date, accurate identification and segmentation of CHs…
Solar radio flux along with geomagnetic indices are important indicators of solar activity and its effects. Extreme solar events such as flares and geomagnetic storms can negatively affect the space environment including satellites in…
The present paper discusses results of a statistical study of the characteristics of coronal hole (CH) rotation in order to find connections to the internal rotation of the Sun. The goal is to measure CH rotation rates and study their…
We develop a reliable, fully automatic method for the detection of coronal holes, that provides consistent full-disk segmentation maps over the full solar cycle and can perform in real-time. We use a convolutional neural network to identify…
Studying solar wind conditions is central to forecasting impact of space weather on Earth. Under the assumption that the structure of this wind is constant in time and corotates with the Sun, solar wind and thereby space weather forecasts…
With the advent of deep learning for computer vision tasks, the need for accurately labeled data in large volumes is vital for any application. The increasingly available large amounts of solar image data generated by the Solar Dynamic…
Solar wind models predict that the mass flux carried away from the Sun in the solar wind should be extremely sensitive to the temperature in the corona, where the solar wind is accelerated. We perform a direct test of this prediction in…
Downflows on the solar surface are suspected to play a major role in the dynamics of the convection zone. We investigate the existence of the long-lasting downflows whose effects influence the interior of the Sun and the outer layers. We…
Energy stored in the magnetic field in the solar atmosphere above active regions is a key driver of all solar activity (e.g., solar flares and coronal mass ejections), some of which can affect life on Earth. Radio observations provide a…
For the years 2001-2008, we use full-disk, SOHO/EIT 195 $\AA$ calibrated images to determine latitudinal and day to day variations of the rotation rates of coronal holes. We estimate the weighted average of heliographic coordinates such as…
A deep learning model is often considered a black-box model, as its internal workings tend to be opaque to the user. Because of the lack of transparency, it is challenging to understand the reasoning behind the model's predictions. Here, we…
Current coronal holes segmentation methods typically rely on image thresholding and require non-trivial image pre- and post-processing. We have trained a neural network that accurately isolates CHs from SDO/AIA 193 Angstrom solar disk…