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New Challenges in Solar Radiation, Modeling and Remote Sensing (Second Edition)
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New Challenges in Solar Radiation, Modeling and Remote Sensing (Second Edition)

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: 10 December 2024 | Viewed by 9698

Special Issue Editors

Dr. Jesús Polo

E-Mail Website
Guest Editor
Photovoltaic Solar Energy Unity (Renewable Energy Division) CIEMAT, 28040 Madrid, Spain
Interests: solar radiation; atmospheric physics; solar systems modeling; radiative transfer; remote sensing; solar power plant performance
Special Issues, Collections and Topics in MDPI journals
Dr. Dmitry Efremenko

E-Mail Website
Guest Editor
Remote Sensing Technology Institute, German Aerospace Center (DLR), 82234 Oberpfaffenhofen, Germany
Interests: radiative transfer; invariant imbedding; discrete ordinate method; synthetic iterations
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Surface solar radiation is of vital importance for life on Earth, radiation–energy balance, photosynthesis and photochemical reactions, meteorological and climatic conditions, and the water cycle. Solar radiation is the most abundant renewable energy resource and, therefore, the demands for environmentally clean energy solutions and a reduction in greenhouse gas emissions have shifted global interest toward the exploitation of solar energy for sustainable development in meeting electricity demands. Solar radiation measurements are necessary in the assessment of potential solar energy resources, while their scarce spatial coverage renders solar radiation modeling and remote sensing necessary for atmospheric and energy applications. The recent applications in broadening the penetration of solar systems have given rise to new demands and challenges in modeling solar radiation and regarding the availability of new and better solar radiation products. Solar cadasters or the modeling of solar radiation with complex topology (rear surface of bifacial PV systems), for instance, are just two specific examples of numerous topics. This Special Issue aims to review recent developments in obtaining solar radiation measurements of higher quality and modeling (solar radiation networks, historical developments, technique comparisons, and standard comparisons between models) and remote sensing using satellite and advanced statistical techniques such as artificial neural networks for solar radiation and energy mapping from regional to global scales. Satellite remote sensing of solar radiation provides better spatial coverage, and various methods have been developed for this, with the main disadvantages being the increased uncertainties and requirements for validation using ground-based measurements or modeling data.

This Special Issue is the second edition of Special Issue: New Challenges in Solar Radiation, Modeling and Remote Sensing. Experts and scholars in related fields are welcome to submit their original works to this Special Issue.

Dr. Jesús Polo
Dr. Dmitry Efremenko
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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
  • models and techniques
  • solar cadasters
  • remote sensing
  • modeling solar radiation with complex topology
  • radiative forcing
  • solar dimming/brightening
  • PV systems
  • solar radiation/energy mapping

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Related Special Issue

Published Papers (5 papers)

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Research

17 pages, 26224 KiB  
Article
Parametric Analytical Modulation Transfer Function Model in Turbid Atmosphere with Application to Image Restoration
by Mengxing Guo, Pengfei Wu, Zizhao Fan, Hao Lu and Ruizhong Rao
Remote Sens. 2024, 16(21), 3998; https://doi.org/10.3390/rs16213998 - 28 Oct 2024
Viewed by 480
Abstract
To address the issues of image blurring and color distortion in hazy conditions, an image restoration method based on a parametric analytical modulation transfer function model is proposed under turbid atmospheric conditions. A source database is established using a numerical radiative transfer method [...] Read more.
To address the issues of image blurring and color distortion in hazy conditions, an image restoration method based on a parametric analytical modulation transfer function model is proposed under turbid atmospheric conditions. A source database is established using a numerical radiative transfer method based on discrete ordinate. Through multivariate nonlinear fitting and linear interpolation, the quantitative relationships among critical spatial frequency, turbid atmospheric MTF, and key atmospheric optical parameters—such as optical thickness, single scattering albedo, and asymmetry factor—are examined. A fast and efficient parametric analytical MTF model for turbid atmospheres is developed and applied to restore images affected by fog. The results demonstrate that, within the applicable range of the model, the model’s maximum mean relative error and the root mean square error are 7.16% and 0.0454, respectively. The computational speed is nearly a thousand times faster than that of the numerical radiative transfer method, achieving high accuracy and ease of application. Images restored using this model exhibit enhanced clarity and quality, effectively compensating for the degradation in image quality caused by turbid atmospheres. This approach represents a novel solution to the challenges of image processing in complex atmospheric environments. Full article
(This article belongs to the Special Issue New Challenges in Solar Radiation, Modeling and Remote Sensing (Second Edition))
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22 pages, 3924 KiB  
Article
Diurnal Variation in Surface Incident Solar Radiation Retrieved by CERES and Himawari-8
by Lu Lu, Ying Li, Lingjun Liang and Qian Ma
Remote Sens. 2024, 16(14), 2670; https://doi.org/10.3390/rs16142670 - 22 Jul 2024
Viewed by 633
Abstract
The diurnal variation of surface incident solar radiation (Rs) has a significant impact on the Earth’s climate. Satellite-retrieved Rs datasets display good spatial and temporal continuity compared with ground-based observations and, more importantly, have higher accuracy than reanalysis datasets. Facilitated by these advantages, [...] Read more.
The diurnal variation of surface incident solar radiation (Rs) has a significant impact on the Earth’s climate. Satellite-retrieved Rs datasets display good spatial and temporal continuity compared with ground-based observations and, more importantly, have higher accuracy than reanalysis datasets. Facilitated by these advantages, many scholars have evaluated satellite-retrieved Rs, especially based on monthly and annual data. However, there is a lack of evaluation on an hourly scale, which has a profound impact on sea–air interactions, climate change, agriculture, and prognostic models. This study evaluates Himawari-8 and Clouds and the Earth’s Radiant Energy System Synoptic (CERES)-retrieved hourly Rs data covering 60°S–60°N and 80°E–160°W based on ground-based observations from the Baseline Surface Radiation Network (BSRN). Hourly Rs were first standardized to remove the diurnal and seasonal cycles. Furthermore, the sensitivities of satellite-retrieved Rs products to clouds, aerosols, and land cover types were explored. It was found that Himawari-8-retrieved Rs was better than CERES-retrieved Rs at 8:00–16:00 and worse at 7:00 and 17:00. Both satellites performed better at continental sites than at island/coastal sites. The diurnal variations of statistical parameters of Himawari-8 satellite-retrieved Rs were stronger than those of CERES. Relatively larger MABs in the case of stratus and stratocumulus were exhibited for both hourly products. Smaller MAB values were found for CERES covered by deep convection and cumulus clouds and for Himawari-8 covered by deep convection and nimbostratus clouds. Larger MAB values at evergreen broadleaf forest sites and smaller MAB values at open shrubland sites were found for both products. In addition, Rs retrieved by Himawari-8 was more sensitive to AOD at 10:00–16:00, while that retrieved by CERES was more sensitive to COD at 9:00–15:00. The CERES product showed larger sensitivity to COD (at 9:00–15:00) and AOD (at 7:00–10:00) than Himawari-8. This work helps data producers know how to improve their future products and helps data users be aware of the uncertainties that exist in hourly satellite-retrieved Rs data. Full article
(This article belongs to the Special Issue New Challenges in Solar Radiation, Modeling and Remote Sensing (Second Edition))
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18 pages, 9179 KiB  
Article
Real-Time Terrain Correction of Satellite Imagery-Based Solar Irradiance Maps Using Precomputed Data and Memory Optimization
by Myeongchan Oh, Chang Ki Kim, Boyoung Kim, Yongheack Kang and Hyun-Goo Kim
Remote Sens. 2023, 15(16), 3965; https://doi.org/10.3390/rs15163965 - 10 Aug 2023
Cited by 2 | Viewed by 1846
Abstract
Satellite imagery-based solar irradiance mapping studies are essential for large-scale solar energy assessments but are limited in spatial resolution and accuracy. Despite efforts to increase map resolution by correcting inaccuracies caused by shadows on the terrain, the computational time of these models and [...] Read more.
Satellite imagery-based solar irradiance mapping studies are essential for large-scale solar energy assessments but are limited in spatial resolution and accuracy. Despite efforts to increase map resolution by correcting inaccuracies caused by shadows on the terrain, the computational time of these models and the massive volume of generated data still pose challenges. Particularly, forecasting generates large amounts of time series data, and the data production rate is faster than the computational speed of traditional terrain correction. Moreover, while previous research has been conducted to expedite computations, a novel and innovative technology in terrain correction is still required. Therefore, we propose a new correction method that can bypass complex calculations and process enormous data within seconds. This model extends the lookup table concept, optimizes the results of many shadow operations, and stores them in memory for use. The model enabled 90 m scale computations across Korea within seconds on a local desktop computer. Optimization was performed based on domain knowledge to reduce the required memory to a realistic level. A quantitative analysis of computation time was also conducted, revealing a previously overlooked computational bottleneck. In conclusion, the developed model enables real-time terrain correction and subsequent processing of massive amounts of data. Full article
(This article belongs to the Special Issue New Challenges in Solar Radiation, Modeling and Remote Sensing (Second Edition))
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20 pages, 3124 KiB  
Article
The SOLAR-HRS New High-Resolution Solar Spectra for Disk-Integrated, Disk-Center, and Intermediate Cases
by Mustapha Meftah, Alain Sarkissian, Philippe Keckhut and Alain Hauchecorne
Remote Sens. 2023, 15(14), 3560; https://doi.org/10.3390/rs15143560 - 15 Jul 2023
Cited by 4 | Viewed by 4248
Abstract
The solar spectrum at the top of the atmosphere contains crucial data for solar physics, astronomy, and geophysics. Accurately determining high-resolution solar reference spectra, whether they are disk-integrated, disk-center, or intermediate cases, represents a new challenge and is of primary importance for all [...] Read more.
The solar spectrum at the top of the atmosphere contains crucial data for solar physics, astronomy, and geophysics. Accurately determining high-resolution solar reference spectra, whether they are disk-integrated, disk-center, or intermediate cases, represents a new challenge and is of primary importance for all applications where spectral solar radiation needs to be evaluated. These spectra are also essential for interpreting remote sensing measurements that rely on sunlight, such as those obtained by Earth observation satellites or spacecraft exploring other planets. This paper lays a foundation for the implementation of multiple new solar irradiance reference spectra that have high resolution and are representative of solar minimum conditions. We developed the SOLAR high-resolution extraterrestrial reference spectra (SOLAR-HRS disk-integrated spectra) by normalizing high-spectral-resolution solar line data to the absolute irradiance scale of the SOLAR-ISS reference spectrum. The resulting one-of-a-kind SOLAR-HRS disk-integrated spectrum has a spectral resolution varying between 0.001 and 1 nm in the 0.5–4400 nm wavelength range. We also implemented a new high-resolution solar spectrum at the disk-center, covering a range of 650–4400 nm with a spectral resolution of 0.001 to 0.02 nm. We further expanded our analysis by producing several solar spectra for ten different solar view angles ranging from μ = 0.9 to μ = 0.05 (SOLAR-HRS intermediate cases). Finally, we developed new Merged Parallelised Simplified ATLAS spectra (MPS-ATLAS) based on solar modeling with Kurucz and Vald3 solar linelists for both the disk-integrated and disk-center spectra. One of the objectives of implementing all these new solar spectra is to fulfill the requirements of the MicroCarb space mission, which focuses on measuring greenhouse gas emissions. The solar data of this study are openly available. Full article
(This article belongs to the Special Issue New Challenges in Solar Radiation, Modeling and Remote Sensing (Second Edition))
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25 pages, 9624 KiB  
Article
Diurnal Cycle in Surface Incident Solar Radiation Characterized by CERES Satellite Retrieval
by Lu Lu and Qian Ma
Remote Sens. 2023, 15(13), 3217; https://doi.org/10.3390/rs15133217 - 21 Jun 2023
Cited by 2 | Viewed by 1761
Abstract
Surface incident solar radiation (Rs) plays an important role in climate change on Earth. Recently, the use of satellite-retrieved datasets to obtain global-scale Rs with high spatial and temporal resolutions has become an indispensable tool for research in related [...] Read more.
Surface incident solar radiation (Rs) plays an important role in climate change on Earth. Recently, the use of satellite-retrieved datasets to obtain global-scale Rs with high spatial and temporal resolutions has become an indispensable tool for research in related fields. Many studies were carried out for Rs evaluation based on the monthly satellite retrievals; however, few evaluations have been performed on their diurnal variation in Rs. This study used independently widely distributed ground-based data from the Baseline Surface Radiation Network (BSRN) to evaluate hourly Rs from the Clouds and the Earth’s Radiant Energy System Synoptic (CERES) SYN1deg–1Hour product through a detrended standardization process. Furthermore, we explored the influence of cloud cover and aerosols on the diurnal variation in Rs. We found that CERES-retrieved Rs performs better at midday than at 7:00–9:00 and 15:00–17:00. For spatial distribution, CERES-retrieved Rs performs better over the continent than over the island/coast and polar regions. The Bias, MAB and RMSE in CERES-retrieved Rs under clear-sky conditions are rather small, although the correlation coefficients are slightly lower than those under overcast-sky conditions from 9:00 to 15:00. In addition, the range in Rs bias caused by cloud cover is 1.97–5.38%, which is significantly larger than 0.31–2.52% by AOD. Full article
(This article belongs to the Special Issue New Challenges in Solar Radiation, Modeling and Remote Sensing (Second Edition))
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