相关论文: Deep Learning Based Reconstruction of Total Solar …
The Sun is the primary source of energy for Earth and one of the main external drivers of its climate. Solar irradiance -- the radiative power emitted by the Sun and received at 1-AU -- varies on all observable timescales. It is measured as…
Solar irradiance measurements are limited to the last few decades, requiring reconstructions to assess solar variability on longer timescales and its impact on Earth's climate. We present the first physics-based reconstruction of total…
Changes in solar irradiance and in its spectral distribution are among the main natural drivers of the climate on Earth. However, irradiance measurements are only available for less than four decades, while assessment of solar influence on…
Solar irradiance variations across various timescales, from minutes to centuries, represents a potential natural driver of past regional and global climate cold phases. To accurately assess the Sun's effect on climate, particularly during…
The variation of total solar irradiance (TSI) has been measured since 1978 and that of the spectral irradiance for an even shorter amount of time. Semi-empirical models are now available that reproduce over 80% of the measured irradiance…
The Sun is the primary source of energy for the Earth. The small changes in total solar irradiance (TSI) can affect our climate in the longer timescale. In the evolutionary timescale, the TSI varies by a large amount and hence its influence…
Aims. We present a physically consistent reconstruction of the total solar irradiance for the Holocene. Methods. We extend the SATIRE models to estimate the evolution of the total (and partly spectral) solar irradiance over the Holocene.…
Reliable historical records of total solar irradiance (TSI) are needed for climate change attribution and research to assess the extent to which long-term variations in the Sun's radiant energy incident on the Earth may exacerbate (or…
Context: The study of variations in total solar irradiance (TSI) is important for understanding how the Sun affects the Earth's climate. Aims: Full-disk continuum images and magnetograms are now available for three full solar cycles. We…
The variation in the radiative output of the Sun, described in terms of solar irradiance, is important to climatology. A common assumption is that solar irradiance variability is driven by its surface magnetism. Verifying this assumption…
Knowledge of solar irradiance variability is critical to Earth's climate models and understanding the solar influence on Earth's climate. Direct solar irradiance measurements are only available since 1978. Reconstructions of past…
Reconstructions of solar spectral irradiance - especially in the ultraviolet (UV) range - are crucial for understanding Earth's climate system. Although total solar irradiance (TSI) has been thoroughly investigated, the spectral composition…
The total solar irradiance (TSI) varies on timescales of minute to centuries. On short timescales it varies due to the superposition of intensity fluctuations produced by turbulent convection and acoustic oscillations. On longer scale…
The Sun is the main energy source to Earth, and understanding its variability is of direct relevance to climate studies. Measurements of total solar irradiance exist since 1978, but this is too short compared to climate-relevant time…
The constant improvement of astronomical instrumentation provides the foundation for scientific discoveries. In general, these improvements have only implications forward in time, while previous observations do not benefit from this trend.…
Total and spectral solar irradiance are key parameters in the assessment of solar influence on changes in the Earth's climate. We present a reconstruction of daily solar irradiance obtained using the SATIRE-S model spanning 1974 to 2013…
Among several heliophysical and geophysical quantities, the accurate evolution of the solar irradiance is fundamental to forecast the evolution of the neutral and ionized components of the Earth's atmosphere.We developed an artificial…
Deep learning models have gained increasing prominence in recent years in the field of solar pho-tovoltaic (PV) forecasting. One drawback of these models is that they require a lot of high-quality data to perform well. This is often…
Ahead-of-time forecasting of incident solar-irradiance on a panel is indicative of expected energy yield and is essential for efficient grid distribution and planning. Traditionally, these forecasts are based on meteorological physics…
The global transition towards cleaner and more sustainable energy production is a major challenge. We present an innovative solution by utilizing smartphone light sensors to measure direct normal solar irradiance, the primary component of…