Solar Radiation: Measurements and Model Studies—Progress and Perspectives (2nd Edition)

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: 29 August 2025 | Viewed by 870

Special Issue Editor


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Guest Editor
Department of Mathematics and Sciences, College of Humanities and Science, Ajman University, Ajman P.O. Box 346, United Arab Emirates
Interests: solar radiation; meteorology; atmospheric physics; cosmic rays; seasonal forecast; climatology
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Special Issue Information

Dear Colleagues,

This is the second volume of the Special Issue entitled "Solar Radiation: Measurements and Model Studies—Progress and Perspectives”, which was published in Atmosphere in 2023; the first volume can be found at the following link: (https://www.mdpi.com/journal/atmosphere/special_issues/6955QL3JN0).

It is well known that the need to advance the use of green energy seeks to reduce environmental pollution, achieve economic goals, and undermine the mechanism of climate change. Solar radiation is considered to be one of the cleanest, most accessible, and alternative sources of renewable energy that can meet future energy needs. With recent developments in solar energy projects around the globe, a proper estimation of solar radiation and related parameters is needed.

We invite researchers to contribute original research manuscripts relating to all aspects of solar radiation, measurements, and modelling. Relevant research includes, but is not limited to, the following topics:

  • Radiation studies that present new knowledge of aerosol–cloud–radiation interactions on a regional scale;
  • Characterization of the effects of air pollution processes on radiation;
  • Testing different techniques, measurements, and models for a precise understanding of solar radiation;
  • Solar UV radiation;
  • Optical radiation propagation;
  • Dynamic and microphysics radiation;
  • Electromagnetic radiation—emission, absorption, and scattering rates.

If this topic is of interest to you, please do not hesitate to send your manuscript for review.

Dr. Abd Al Karim Haj Ismail
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • solar radiation
  • meteorology
  • cosmic air showers
  • radioactivity
  • air pollution

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Published Papers (2 papers)

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Research

17 pages, 3375 KiB  
Article
Influence of Clouds and Aerosols on Solar Irradiance and Application of Climate Indices in Its Monthly Forecast over China
by Shuting Zhang and Xiaochun Wang
Atmosphere 2025, 16(6), 730; https://doi.org/10.3390/atmos16060730 - 16 Jun 2025
Viewed by 199
Abstract
Based on the Clouds and the Earth’s Radiant Energy System (CERES) satellite data from 2001 to 2023 and the climate indices from the National Oceanic and Atmospheric Administration (NOAA), this study analyzes the solar irradiance over mainland China and the impacts of clouds [...] Read more.
Based on the Clouds and the Earth’s Radiant Energy System (CERES) satellite data from 2001 to 2023 and the climate indices from the National Oceanic and Atmospheric Administration (NOAA), this study analyzes the solar irradiance over mainland China and the impacts of clouds and aerosols on it and constructs monthly forecasting models to analyze the influence of climate indices on irradiance forecasts. The irradiance over mainland China shows a spatial distribution of being higher in the west and lower in the east. The influence of clouds on irradiance decreases from south to north, and the influence of aerosols is prominent in the east. The average explained variance of clouds on irradiance is 86.72%, which is much higher than that of aerosols on irradiance, 15.62%. Singular Value Decomposition (SVD) analysis shows a high correlation between the respective time series of irradiance and cloud influence, with the two fields having similar spatial patterns of opposite signs. The variation in solar irradiance can be attributed mainly to the influence of clouds. Empirical Orthogonal Function (EOF) analysis indicates that the variation in the first mode of irradiance is consistent in most parts of China, and its time coefficient is selected for monthly forecasting. Both the traditional multiple linear regression method and the Long Short-Term Memory (LSTM) network are used to construct monthly forecast models, with the preceding time coefficient of the first EOF mode and different climate indices as input. Compared with the multiple linear regression method, LSTM has a better forecasting skill. When the input length increases, the forecasting skill decreases. The inclusion of climate indices, such as the Indian Ocean Basin (IOB), El Nino–Southern Oscillation (ENSO), and Indian Ocean Dipole (IOD), can enhance the forecasting skill. Among these three indices, IOB has the most significant improvement effect. The research provides a basis for accurate forecasting of solar irradiance over China on monthly time scale. Full article
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31 pages, 2029 KiB  
Article
A Comparison of Different Solar Radiation Models in the Iberian Peninsula
by Catalina Roca-Fernández, Xavier Pons and Miquel Ninyerola
Atmosphere 2025, 16(5), 590; https://doi.org/10.3390/atmos16050590 - 14 May 2025
Viewed by 449
Abstract
Solar radiation is a first-order essential climate variable like temperature and precipitation. Its significant spatiotemporal variability, mainly due to atmospheric conditions, makes modelling particularly challenging, especially in regions with complex atmospheric dynamics and sparse meteorological stations. This study evaluates 6 solar radiation models [...] Read more.
Solar radiation is a first-order essential climate variable like temperature and precipitation. Its significant spatiotemporal variability, mainly due to atmospheric conditions, makes modelling particularly challenging, especially in regions with complex atmospheric dynamics and sparse meteorological stations. This study evaluates 6 solar radiation models (SARAH, PVGIS, Constant Atmospheric Conditions, Physical Solar Model, CAMS Worldwide, and InsolMets) using monthly measurements from 141 ground-based stations across the Iberian Peninsula from 2004–2020. Although all models consistently captured intra-annual variability, discrepancies in absolute values arise due to factors such as the differences in their functional designs and input parameters. InsolMets, which integrates cloud optical thickness, cloud fractional cover, the diffuse radiation component, and enhanced solar illumination geometry, was the most robust model, showing relevant improvements (61.5% in January, 59.7% in November, and 52.0% in December) compared to the worst-performing model (constant atmospheric conditions). Using as a threshold three times the root-mean-square error (RMSE) proposed by the Global Climate Observing System, InsolMets achieved the highest number of months (10) under this limit, also achieving the best overall result, with only 1 month showing non-significant correlations over the same time span. Nevertheless, SARAH and PVGIS matched InsolMets’ performance during March, November, and December. The results provide insights for selecting and improving solar radiation estimations, highlighting the need to incorporate remote sensing atmospheric data to minimize uncertainties. While all models that account for atmospheric effects enhance accuracy, InsolMets stands out as the most accurate model for estimating solar radiation across the Iberian Peninsula throughout the year, achieving the lowest RMSE and normalized RMSE values. Full article
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