相关论文: Short-term Classification of Strong Solar Energeti…

Knowing the behavior of solar radiation at a geographic location is essential for the use of energy from the sun using photovoltaic systems; however, the number of stations for measuring meteorological parameters and for determining the…

The challenges in applications of solar energy lies in its intermittency and dependency on meteorological parameters such as; solar radiation, ambient temperature, rainfall, wind-speed etc., and many other physical parameters like dust…

Over the past few decades, many applications of physics-based simulations and data-driven techniques (including machine learning and deep learning) have emerged to analyze and predict solar flares. These approaches are pivotal in…

In this work, more than a dozen solar energetic particle (SEP) events are identified where the source region is magnetically well-connected to at least one spacecraft at 1~au. The observed intensity-time profiles, for all available proton…

During mid-May 2024, active region (AR) 13664 produced a series of M- and X-class flares along with several coronal mass ejections (CMEs) that resulted in exceptionally strong aurora at Earth. This study presents in-situ solar energetic…

The CLEAR Space Weather Center of Excellence's solar energetic particle (SEP) model, SOlar wind with FIeld lines and Energetic particles (SOFIE), was run and evaluated on-site during the Space Weather Prediction Testbed (SWPT) exercise at…

Extreme weather events have significant consequences, dominating the impact of climate on society. While high-resolution weather models can forecast many types of extreme events on synoptic timescales, long-term climatological risk…

In this work, a gradual solar energetic particle (SEP) event observed by multispacecraft has been simulated. The time profiles of SEP fluxes accelerated by an interplanetary shock in the three-dimensional interplanetary space are obtained…

The CLEAR Space Weather Center of Excellence (CLEAR center) is a five year project that is funded by the NASA Space Weather Center of Excellence program. The CLEAR center will build a comprehensive prediction framework for solar energetic…

We consider forecasting functional time series of extreme values within a generalised extreme value distribution (GEV). The GEV distribution can be characterised using the three parameters (location, scale and shape). As a result, the…

The Sun is an effective particle accelerator producing solar energetic particle (SEP) events during which particles up to several GeVs can be observed. Those events observed at Earth with the neutron monitor network are called ground level…

The PAMELA satellite experiment is providing first direct measurements of Solar Energetic Particles (SEPs) with energies from about 80 MeV to several GeV in near-Earth space, bridging the low energy data by other space-based instruments and…

Based on energetic particle observations made at $\approx$1 AU, we present a catalogue of 46 wide-longitude (>45{\deg}) solar energetic particle (SEP) events detected at multiple locations during 2009-2016. The particle kinetic energies of…

Despite the significant progress achieved in recent years, the physical mechanisms underlying the origin of solar energetic particles (SEPs) are still a matter of debate. The complex nature of both particle acceleration and transport poses…

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…

Geomagnetic storms (GS) occur when solar winds disrupt Earth's magnetosphere. GS can cause severe damages to satellites, power grids, and communication infrastructures. Estimate of direct economic impacts of a large scale GS exceeds $40…

Intense solar energetic particle (SEP) events data, associated with ground level enhancements (GLEs), occurred during 1989 to 2006 have been obtained from the spectrometers on board GOES spacecraft in the energy range 10-100 MeV. The…

Probabilistic forecasts of renewable energy production provide users with valuable information about the uncertainty associated with the expected generation. Current state-of-the-art forecasts for solar irradiance have focused on producing…

We present a scalable machine learning framework for analyzing Parker Solar Probe (PSP) solar wind data using distributed processing and the quantum-inspired Kernel Density Matrices (KDM) method. The PSP dataset (2018--2024) exceeds 150 GB,…

The sunspot number (SSN), the total solar irradiance (TSI), a TSI reconstruction, and the solar flare index (SFI), are analyzed for long-range persistence (LRP). Standard Hurst analysis yields $H \approx 0.9$, which suggests strong LRP.…