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@article{Gatón2026,

title = {Multi-frame cloud prediction in all-sky images from RGB images and segmented masks},

author = {Javier Gatón and Roberto Román and Cesar Guzman and Daniel González-Fernández and Bruno Longarela and Carlos Toledano and Ramiro González},

url = {https://www.sciencedirect.com/science/article/pii/S0038092X26002033},

doi = {https://doi.org/10.1016/j.solener.2026.114515},

issn = {0038-092X},

year  = {2026},

date = {2026-03-18},

urldate = {2026-01-01},

journal = {Solar Energy},

volume = {311},

pages = {114515},

abstract = {This paper presents a comparative study on the impact of input representation on deterministic artificial intelligence models for short-term multi-frame prediction in all-sky images. This work compares a model operating on 8-bit RGB all-sky images with a model that shares the same backbone, but operates directly on semantically segmented masks that encode cloud-related classes. Using an available sky segmentation model, predictions are evaluated in the segmentation label space using segmenter-derived masks as a proxy reference. Within this evaluation framework, the use of semantic masks as input for short-term prediction leads to improved temporal stability and higher agreement across standard segmentation metrics such as intersection over union, Dice coefficient, and categorical cross-entropy. While these results suggest potential relevance for weather and solar energy nowcasting applications, further validation against physical irradiance measurements is required.},

keywords = {All-sky images, Artificial intelligence, Cloud motion prediction, clouds, Next-frame prediction, Semantic segmentation},

pubstate = {published},

tppubtype = {article}

}

@article{Herrero-Anta2025,

title = {Impact of cloud presence on sky radiances and the retrieval of aerosol properties},

author = {Sara Herrero-Anta and Roberto Román and Daniel González-Fernández and Claudia Emde and David Mateos and Celia Herrero Barrio and Ramiro González and Oleg Dubovik and Carlos Toledano and Abel Calle and Victoria E. Cachorro and Bernhard Mayer and Ángel M. de Frutos},

url = {https://www.sciencedirect.com/science/article/pii/S0169809525000304},

doi = {https://doi.org/10.1016/j.atmosres.2025.107938},

issn = {0169-8095},

year  = {2025},

date = {2025-01-18},

urldate = {2025-01-01},

journal = {Atmospheric Research},

volume = {317},

pages = {107938},

abstract = {This paper explores the influence of the presence of clouds on sky radiances. It also analyses their impact on the retrieval of aerosol properties when using an inversion algorithm whose radiative transfer model (RTM) is designed for cloud-free atmospheres. For that, synthetic observations are simulated for 9 partially cloudy skies and for their equivalent cloud-free skies, considering 16 different aerosol scenarios. A parameter named cloud enhancement factor (CEF) has been used to determine the modifications induced in the sky radiances by each partially cloudy scenario with respect to the cloud-free sky. This parameter indicates that the sky radiances remaining after applying a cloud-screening are affected by the presence of clouds. In general, they show enhancements between 0 and 20 % with respect to the cloud-free radiances, depending on the cloudy conditions and the scattering angle. The synthetic observations used as input for the retrieval of aerosol properties are the ones required by the inversion strategy used, GRASPpac: the aerosol optical depth (AOD) and sky radiances at 4 different wavelengths together with the ceilometer range corrected signal (RCS). In partially cloudy scenarios with low CEFs, the aerosol properties do not present significant changes with respect to the cloud-free conditions. However, for partially cloudy scenarios with higher CEFs, a clear differentiation between the aerosol optical properties retrieved with and without clouds is observed. In these scenarios, the precision of the retrieval is similar for both conditions, but the accuracy is lower for the cloudy conditions. In particular, under partially cloudy conditions, it is observed an overestimation of the real refractive index (RRI) and the single scattering albedo (SSA) between 0.05 and 0.06 and between 0.03 and 0.06 respectively, and an underestimation of the asymmetry factor (g) and the imaginary refractive index (IRI) of about ?0.02 and ? 0.005, respectively. These values slightly vary with the aerosol load and wavelength for the RRI and SSA. The effects on the size distribution parameters are very small, concluding that the impact of clouds is noticeable in the optical properties but not so much in the microphysical part.},

keywords = {Aerosols, clouds, Enhancement effect, GRASP, sky radiance},

pubstate = {published},

tppubtype = {article}

}

@article{Antuña-Sánchez2022,

title = {ORION software tool for the geometrical calibration of all-sky cameras},

author = {J.C. Antuña-Sánchez and R. Román and J.L. Bosch and C. Toledano and D. Mateos and R. González and V.E. Cachorro and Ángel de Frutos},

doi = {10.1371/journal.pone.0265959},

year  = {2022},

date = {2022-03-31},

urldate = {2022-03-31},

journal = {PLoS ONE 17(3)},

abstract = {This paper presents the software application ORION (All-sky camera geOmetry calibRation from star positIONs). This software has been developed with the aim of providing geometrical calibration to all-sky cameras, i.e. assess which sky coordinates (zenith and azimuth angles) correspond to each camera pixel. It is useful to locate bodies over the celestial vault, like stars and planets, in the camera images. The user needs to feed ORION with a set of cloud-free sky images captured at night-time for obtaining the calibration matrices. ORION searches the position of various stars in the sky images. This search can be automatic or manual. The sky coordinates of the stars and the corresponding pixel positions in the camera images are used together to determine the calibration matrices. The calibration is based on three parameters: the pixel position of the sky zenith in the image; the shift angle of the azimuth viewed by the camera with respect to the real North; and the relationship between the sky zenith angle and the pixel radial distance regards to the sky zenith in the image. In addition, ORION includes other features to facilitate its use, such as the check of the accuracy of the calibration. An example of ORION application is shown, obtaining the calibration matrices for a set of images and studying the accuracy of the calibration to predict a star position. Accuracy is about 9.0 arcmin for the analyzed example using a camera with average resolution of 5.4 arcmin/pixel (about 1.7 pixels).},

keywords = {all-sky camera, clouds, image analylis, polynomials, stars},

pubstate = {published},

tppubtype = {article}

}

@article{ROMAN2017224,

title = {Cloud cover detection combining high dynamic range sky images and ceilometer measurements},

author = {R. Román and A. Cazorla and C. Toledano and F.J. Olmo and V.E. Cachorro and A. de Frutos and L. Alados-Arboledas},

url = {http://www.sciencedirect.com/science/article/pii/S0169809516307475},

doi = {10.1016/j.atmosres.2017.06.006},

issn = {0169-8095},

year  = {2017},

date = {2017-01-01},

journal = {Atmospheric Research},

volume = {196},

pages = {224 - 236},

keywords = {Aerosols, clouds, High dynamic range, sky camera},

pubstate = {published},

tppubtype = {article}

}