Related papers: Solar Cycle Prediction Using TCN Deep Learning Mod…
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…
We consider the statistical relationship between the growth rate of activity in the early phase of a solar cycle with its subsequent amplitude on the basis of four datasets of global activity indices (Wolf sunspot number, group sunspot…
Solar energetic particle (SEP) events are one of the most crucial aspects of space weather that require continuous monitoring and forecasting. Their prediction depends on various factors including source eruptions. In the present work, we…
We propose a forecasting approach for solar flares based on data from Solar Cycle 24, taken by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) mission. In particular, we use the Space-weather HMI…
The concept of degree of similarity ({\eta}) is proposed to quantitatively describe the similarity of a parameter (e.g. the maximum amplitude Rmax) of a solar cycle relative to a referenced one, and the prediction method of similar cycles…
The growth rate of solar activity in the early phase of a solar cycle has been known to be well correlated with the subsequent amplitude (solar maximum). It provides very useful information for a new solar cycle as its variation reflects…
Sunspot Cycle 25 over 3 years past the cycle minimum of December 2019. At this point, curve-fitting becomes reliable and consistently indicates a maximum sunspot number of 135+/-10 - slightly larger than Cycle 24's maximum of 116.4, but…
Traditional methods for enhancing tropical cyclone (TC) intensity from climate model outputs or projections have primarily relied on either dynamical or statistical downscaling. With recent advances in deep learning (DL) techniques, a…
The energy output a photo voltaic(PV) panel is a function of solar irradiation and weather parameters like temperature and wind speed etc. A general measure for solar irradiation called Global Horizontal Irradiance (GHI), customarily…
In this work we predict the maximum amplitude, its time of occurrence, and the total length of Solar Cycle 24 by linear regression to the curvature (second derivative) at the preceding minimum of a smoothed version of the sunspots time…
The solar magnetic field, thought to be generated by the motion of plasma within the Sun, alternates on the order of 11-year cycles and is incompletely understood. Industries rely on accurate forecasts of solar activity, but can solar…
Regional solar power forecasting, which involves predicting the total power generation from all rooftop photovoltaic systems in a region holds significant importance for various stakeholders in the energy sector. However, the vast amount of…
The F10.7 and F30 solar indices are the solar radio fluxes measured at wavelengths of 10.7 cm and 30 cm, respectively, which are key indicators of solar activity. F10.7 is valuable for explaining the impact of solar ultraviolet (UV)…
The so-called solar cycle is generally characterized by the quasi-periodic oscillatory evolution of the photospheric spots number. This quasi-periodic pattern has always been an intriguing question. Several physical models were proposed to…
We propose a simple method for prediction of the 11-year solar cycle maximum that is based on two relations. One of them is well known Waldmeier's rule that binds the amplitude of a cycle and the length of its ascending phase. The second…
The solar activity in the current, that is, the 24-th, sunspot cycle is analyzed. Cyclic variations in the sunspot number (SSN) and radiation fluxes in various spectral ranges have been estimated in comparison with the general level of the…
We present a comprehensive analysis of Solar Cycle 25 aimed at precisely constraining the interval of its activity maximum using multiple observational parameters: sunspot number (SSN), Wolf number, the 10.7 cm solar radio flux (F10.7), the…
Using solar power in the process industry can reduce greenhouse gas emissions and make the production process more sustainable. However, the intermittent nature of solar power renders its usage challenging. Building a model to predict…
Solar flares occur in complex sunspot groups, but it remains unclear how the probability of producing a flare of a given magnitude relates to the characteristics of the sunspot group. Here, we use Geostationary Operational Environmental…
Analyzing big geophysical observational data collected by multiple advanced sensors on various satellite platforms promotes our understanding of the geophysical system. For instance, convolutional neural networks (CNN) have achieved great…