Related papers: Early Prediction of Geomagnetic Storms by Machine …
Rising global energy demand from population growth raises concerns about the sustainability of fossil fuels. Consequently, the energy sector has increasingly transitioned to renewable energy sources like solar and wind, which are naturally…
The Earth's magnetosphere is formed as a consequence of interaction between the planet's magnetic field and the solar wind, a continuous plasma stream from the Sun. A number of different solar wind phenomena have been studied over the past…
Predicting the intensity and amount of sunlight as a function of location and time is an essential component in identifying promising locations for economical solar farming. Although weather models and irradiance data are relatively…
Modern economies depend critically on high-voltage power transmission networks. Yet this infrastructure is routinely disrupted by natural hazards ranging from earthquakes and floods to tornadoes and geomagnetic storms. Risk assessments have…
Since the late 1950s, when the first artificial satellite was launched, the number of Resident Space Objects has steadily increased. It is estimated that around one million objects larger than one cm are currently orbiting the Earth, with…
Records of Dst, Kp and Sym-H indexes are analyzed looking for evidences of possible precursors for magnetic storms. To accomplish this task the main magnetic storms were located and some periods immediately before storms and some periods…
Models based on neural networks and machine learning are seeing a rise in popularity in space physics. In particular, the forecasting of geomagnetic indices with neural network models is becoming a popular field of study. These models are…
We present a novel algorithm that predicts the probability that the time derivative of the horizontal component of the ground magnetic field $dB/dt$ exceeds a specified threshold at a given location. This quantity provides important…
The forecast method introduced by Kors\'os et al.(2014) is generalised from the horizontal magnetic gradient (GM), defined between two opposite polarity spots, to all spots within an appropriately defined region close to the magnetic…
Quantifying the impacts of anthropogenic global warming requires accurate Earth system model (ESM) simulations. Statistical bias correction and downscaling can be applied to reduce errors and increase the resolution of ESMs. However,…
With the rise of electronic data, particularly Earth observation data, data-based geospatial modelling using machine learning (ML) has gained popularity in environmental research. Accurate geospatial predictions are vital for domain…
On the approach to minimum of Solar Cycle 24, on 26 August 2018, an unexpectedly strong geomagnetic storm (GMS) suddenly occurred. Its Dst index reached -174 nT, that is the third of the most intense storms during the cycle. The analysis…
Short-term forecasting of solar photovoltaic energy (PV) production is important for powerplant management. Ideally these forecasts are equipped with error bars, so that downstream decisions can account for uncertainty. To produce…
Content. Solar flares are often used as precursors of geomagnetic storms. In particular, Howard and Tappin (2005) recently published in A&A a dependence between X-ray class of solar flares and Ap and Dst indexes of geomagnetic storms which…
Global medium-range weather forecasting is critical to decision-making across many social and economic domains. Traditional numerical weather prediction uses increased compute resources to improve forecast accuracy, but cannot directly use…
The application of reliable structural health monitoring (SHM) technologies to operational wind turbine blades is a challenging task, due to the uncertain nature of the environments they operate in. In this paper, a novel SHM methodology,…
While machine learning (ML) post-processing of convection-allowing model (CAM) output for severe weather hazards (large hail, damaging winds, and/or tornadoes) has shown promise for very short lead times (0-3 hours), its application to…
Prediction of the Solar Energetic Particle (SEP) events garner increasing interest as space missions extend beyond Earth's protective magnetosphere. These events, which are, in most cases, products of magnetic reconnection-driven processes…
Solar irradiance is considered one of the main natural factors affecting terrestrial climate, and its variations are included in most numerical models estimating the effects of natural versus anthropogenic factors for climate change. Solar…
Space weather phenomena such as solar flares, have massive destructive power when reaches certain amount of magnitude. Such high magnitude solar flare event can interfere space-earth radio communications and neutralize space-earth…