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Remote Sensing
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Satellite Images for Assessing Solar Radiation at Surface
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Satellite Images for Assessing Solar Radiation at Surface

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

Deadline for manuscript submissions: closed (31 March 2020) | Viewed by 13230

Special Issue Editors

Prof. Philippe BLANC

E-Mail Website
Guest Editor
MINES ParisTech, PSL Research University, O.I.E. - Centre Observation, Impacts, Energy, 06904 Sophia Antipolis, France
Interests: solar energy; solar resource assessment; solar forecasting; remote sensing
Mr. Jan REMUND

E-Mail Website
Guest Editor
Meteotest AG, Fabrikstrasse 14, 3012 Bern, Switzerland
Interests: Solar energy; solar resource assessments;solar forecasting; climate change
Dr. Manajit SENGUPTA

E-Mail Website
Guest Editor
NREL
Interests: satellite remote sensing; solar resource assessment; forecasting; calibration; measurements; climate change

Special Issue Information

Dear Colleagues,

Defined as the amount of solar incident energy per unit time, per unit area detected on a horizontal surface at ground level, Surface solar irradiance (SSI) was identified as an essential climate variable by the Global Climate Observing System, meaning that it is a parameter of key importance for understanding and monitoring the global climate system. In addition to such climatology applications, SSI is of high interest in domains as varied as solar energy, health, architecture, agriculture, and forestry.

SSI estimation can be made using solar radiation measurements from the existing network of in-situ pyranometric stations. However, these are sparsely distributed worldwide, and stations measuring SSI on the long-term are very rare. Therefore, SSI estimation based on satellite image coupled or not with numerical weather models propose operational alternatives or complements to ground-based approaches, as they enable a better spatial and temporal coverage.

The present special issue will be devoted to satellite-based method of SSI retrieval which is long track record and still a very active research domain, namely identified by a devoted subtask of the task 16 “” of the International Energy Agency (IEA) program Photovoltaic Power System (PVPS ).

We invite contributions notably on the following aspects satellite-based SSI retrieval:

  • New approaches based on cloud index or cloud properties derived from satellite;
  • Improvements of existing methods (better accuracy, better solar resource characterization in the spectral and angular domains, seamless global coverage);
  • Adaptation of existing methods to new or future geostationary satellites (Himawari 8, GOES R, Meteosat Third Generation) or from other orbits (e.g. polar orbit for higher latitude);
  • Benchmarking of SSI estimations versus other approaches (e.g. reanalysis products from numerical weather models);
  • Uncertainty analysis with respect local climates and conditions;
  • Spatial resolution enhancement for high resolution solar mapping;
  • Satellite-based solar forecasting (cloud motion vectors, spatio-temporal variability assessment, etc.).

Prof. Philippe BLANC
Mr. Jan REMUND
Dr. Manajit SENGUPTA
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

  • surface solar radiation
  • satellite retrieval
  • cloud properties
  • atmosphere

Published Papers (4 papers)

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Research

20 pages, 4408 KiB  
Article
Evaluation of Global Solar Irradiance Estimates from GL1.2 Satellite-Based Model over Brazil Using an Extended Radiometric Network
by Anthony C. S. Porfirio, Juan C. Ceballos, José M. S. Britto and Simone M. S. Costa
Remote Sens. 2020, 12(8), 1331; https://doi.org/10.3390/rs12081331 - 23 Apr 2020
Cited by 7 | Viewed by 3129
Abstract
The GL (GLobal radiation) physical model was developed to compute global solar irradiance at ground level from (VIS) visible channel imagery of geostationary satellites. Currently, its version 1.2 (GL1.2) runs at Brazilian Center for Weather Forecast and Climate Studies/National Institute for Space Research [...] Read more.
The GL (GLobal radiation) physical model was developed to compute global solar irradiance at ground level from (VIS) visible channel imagery of geostationary satellites. Currently, its version 1.2 (GL1.2) runs at Brazilian Center for Weather Forecast and Climate Studies/National Institute for Space Research (CPTEC/INPE) based on GOES-East VIS imagery. This study presents an extensive validation of GL1.2 global solar irradiance estimates using ground-based measurements from 409 stations belonging to the Brazilian National Institute of Meteorology (INMET) over Brazil for the year 2016. The INMET reasonably dense network allows characterizing the spatial distribution of GL1.2 data uncertainties. It is found that the GL1.2 estimates have a tendency to overestimate the ground data, but the magnitude varies according to region. On a daily basis, the best performances are observed for the Northeast, Southeast, and South regions, with a mean bias error (MBE) between 2.5 and 4.9 W m−2 (1.2% and 2.1%) and a root mean square error (RMSE) between 21.1 and 26.7 W m−2 (10.8% and 11.8%). However, larger differences occur in the North and Midwest regions, with MBE between 12.7 and 23.5 W m−2 (5.9% and 11.7%) and RMSE between 27 and 33.4 W m−2 (12.7% and 16.7%). These errors are most likely due to the simplified assumptions adopted by the GL1.2 algorithm for clear sky reflectance (Rmin) and aerosols as well as the uncertainty of the water vapor data. Further improvements in determining these parameters are needed. Additionally, the results also indicate that the GL1.2 operational product can help to improve the quality control of radiometric data from a large network, such as INMET's. Overall, the GL1.2 data are suitable for use in various regional applications. Full article
(This article belongs to the Special Issue Satellite Images for Assessing Solar Radiation at Surface)
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22 pages, 11607 KiB  
Article
Analysis of Spatial and Temporal Variability of the PAR/GHI Ratio and PAR Modeling Based on Two Satellite Estimates
by Francisco Ferrera-Cobos, Jose M. Vindel, Rita X. Valenzuela and José A. González
Remote Sens. 2020, 12(8), 1262; https://doi.org/10.3390/rs12081262 - 16 Apr 2020
Cited by 11 | Viewed by 2886
Abstract
The main objectives of this work are to address the analysis of the spatial and temporal variability of the ratio between photosynthetically active radiation (PAR) and global horizontal irradiance (GHI), as well as to develop PAR models. The analysis [...] Read more.
The main objectives of this work are to address the analysis of the spatial and temporal variability of the ratio between photosynthetically active radiation (PAR) and global horizontal irradiance (GHI), as well as to develop PAR models. The analysis was carried out using data from three stations located in mainland Spain covering three climates: oceanic, standard Mediterranean, and continental Mediterranean. The results of this analysis showed a clear dependence between the PAR/GHI ratio and the location; the oceanic climate showed higher values of PAR/GHI compared with Mediterranean climates. Further, the temporal variability of PAR/GHI was conditioned by the variability of clearness index, so it was also higher in oceanic than in Mediterranean climates. On the other hand, Climate Monitoring Satellite Facility (CM-SAF) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data were used to estimate PAR as a function of GHI over the whole territory. The validation with ground measurements showed better performance of the MODIS-estimates-derived model for the oceanic climate (root-mean-square error (RMSE) around 5%), while the model obtained from CM-SAF fitted better for Mediterranean climates (RMSEs around 2%). Full article
(This article belongs to the Special Issue Satellite Images for Assessing Solar Radiation at Surface)
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28 pages, 9982 KiB  
Article
Satellite Retrieval of Downwelling Shortwave Surface Flux and Diffuse Fraction under All Sky Conditions in the Framework of the LSA SAF Program (Part 2: Evaluation)
by Dominique Carrer, Suman Moparthy, Chloé Vincent, Xavier Ceamanos, Sandra C. Freitas and Isabel F. Trigo
Remote Sens. 2019, 11(22), 2630; https://doi.org/10.3390/rs11222630 - 11 Nov 2019
Cited by 11 | Viewed by 2972
Abstract
High frequency knowledge of the spatio-temporal distribution of the downwelling surface shortwave flux (DSSF) and its diffuse fraction (fd) at the surface is nowadays essential for understanding climate processes at the surface–atmosphere interface, plant photosynthesis and carbon cycle, and for the solar energy [...] Read more.
High frequency knowledge of the spatio-temporal distribution of the downwelling surface shortwave flux (DSSF) and its diffuse fraction (fd) at the surface is nowadays essential for understanding climate processes at the surface–atmosphere interface, plant photosynthesis and carbon cycle, and for the solar energy sector. The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility for Land Surface Analysis operationally delivers estimation of the MDSSFTD (MSG Downwelling Surface Short-wave radiation Fluxes—Total and Diffuse fraction) product with an operational status since the year 2019. The method for retrieval was presented in a companion paper. Part 2 now focuses on the evaluation of the MDSSFTD algorithm and presents a comparison of the corresponding outputs, i.e., total DSSF and diffuse fraction (fd) components, against in situ measurements acquired at four Baseline Surface Radiation Network (BSRN) stations over a seven-month period. The validation is performed on an instantaneous basis. We show that the satellite estimates of DSSF and fd meet the target requirements defined by the user community for all-sky (clear and cloudy) conditions. For DSSF, the requirements are 20 Wm−2 for DSSF < 200 Wm−2, and 10% for DSSF ≥ 200 Wm−2. The mean bias error (MBE) and relative mean bias error (rMBE) compared to the ground measurements are 3.618 Wm−2 and 0.252%, respectively. For fd, the requirements are 0.1 for fd < 0.5, and 20% for fd ≥ 0.5. The MBE and rMBE compared to the ground measurements are −0.044% and −17.699%, respectively. The study also provides a separate analysis of the product performances for clear sky and cloudy sky conditions. The importance of representing the cloud–aerosol radiative coupling in the MDSSFTD method is discussed. Finally, it is concluded that the quality of the aerosol optical depth (AOD) forecasts currently available is accurate enough to obtain reliable diffuse solar flux estimates. This quality of AOD forecasts was still a limitation a few years ago. Full article
(This article belongs to the Special Issue Satellite Images for Assessing Solar Radiation at Surface)
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25 pages, 4033 KiB  
Article
Satellite Retrieval of Downwelling Shortwave Surface Flux and Diffuse Fraction under All Sky Conditions in the Framework of the LSA SAF Program (Part 1: Methodology)
by Dominique Carrer, Xavier Ceamanos, Suman Moparthy, Chloé Vincent, Sandra C. Freitas and Isabel F. Trigo
Remote Sens. 2019, 11(21), 2532; https://doi.org/10.3390/rs11212532 - 29 Oct 2019
Cited by 12 | Viewed by 3667
Abstract
Several studies have shown that changes in incoming solar radiation and variations of the diffuse fraction can significantly modify the vegetation carbon uptake. Hence, monitoring the incoming solar radiation at large scale and with high temporal frequency is crucial for this reason along [...] Read more.
Several studies have shown that changes in incoming solar radiation and variations of the diffuse fraction can significantly modify the vegetation carbon uptake. Hence, monitoring the incoming solar radiation at large scale and with high temporal frequency is crucial for this reason along with many others. The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility for Land Surface Analysis (LSA SAF) has operationally disseminated in near real time estimates of the downwelling shortwave radiation at the surface since 2005. This product is derived from observations provided by the SEVIRI instrument onboard the Meteosat Second Generation series of geostationary satellites, which covers Europe, Africa, the Middle East, and part of South America. However, near real time generation of the diffuse fraction at the surface level has only recently been initiated. The main difficulty towards achieving this goal was the general lack of accurate information on the aerosol particles in the atmosphere. This limitation is less important nowadays thanks to the improvements in atmospheric numerical models. This study presents an upgrade of the LSA SAF operational retrieval method, which provides the simultaneous estimation of the incoming solar radiation and its diffuse fraction from the satellite every 15 min. The upgrade includes a comprehensive representation of the influence of aerosols based on physical approximations of the radiative transfer within an atmosphere-surface associated medium. This article explains the retrieval method, discusses its limitations and differences with the previous method, and details the characteristics of the output products. A companion article will focus on the evaluation of the products against independent measurements of solar radiation. Finally, the access to the source code is provided through an open access platform in order to share the expertise on the satellite retrieval of this variable with the community. Full article
(This article belongs to the Special Issue Satellite Images for Assessing Solar Radiation at Surface)
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