Dr. Roberto Román

@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 = {},

pubstate = {published},

tppubtype = {article}

}

@article{Barreto2026,

title = {Volcanic plume height during the 2021 Tajogaite eruption (La Palma) from two complementary monitoring methods – implications for satellite-based products},

author = {Á. Barreto and F. Quirós and O. E. García and J. Pereda-de-Pablo and D. González-Fernández and A. Bedoya-Velásquez and M. Sicard and C. Córdoba-Jabonero and M. Iarlori and V. Rizi and N. Krotkov and S. Carn and R. Roininen and A. J. Molina-Arias and A. F. Almansa and Ó. Álvarez-Losada and C. Aramo and J. J. Bustos and R. Ceolato and A. Comerón and A. Felpeto and R. D. García and P. González-Sicilia and Y. González and P. Hedelt and M. Hernández and M. -Á. López-Cayuela and D. Loyola and S. Meletlidis and C. Muñoz-Porcar and E. Pietropaolo and R. Ramos and A. Rodríguez-Gómez and R. Román and P. M. Romero-Campos and M. Stuefer and C. Toledano and E. J. Welton},

url = {https://amt.copernicus.org/articles/19/1385/2026/},

doi = {10.5194/amt-19-1385-2026},

year  = {2026},

date = {2026-02-20},

urldate = {2026-01-01},

journal = {Atmospheric Measurement Techniques},

volume = {19},

number = {4},

pages = {1385–1406},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mateos2026,

title = {Saharan and Arabian dust optical properties registered by sun photometry during A-LIFE field experiment in Cyprus},

author = {D. Mateos and C. Toledano and A. Calle and R. Román and M. Herreras-Giralda and R. González and S. Herrero-Anta and D. González-Fernández and C. Herrero-del Barrio and A. Nisantzi and R. E. Mamouri and S. Groß and V. E. Cachorro and Á. M. Frutos and B. Weinzierl},

url = {https://acp.copernicus.org/articles/26/1993/2026/},

doi = {10.5194/acp-26-1993-2026},

year  = {2026},

date = {2026-02-09},

urldate = {2026-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {26},

number = {3},

pages = {1993–2005},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Herrero-Anta2026,

title = {Exceptional high AOD over Svalbard in summer 2019: a multi-instrumental approach},

author = {S. Herrero-Anta and S. Eckhardt and N. Evangeliou and S. Gilardoni and S. Graßl and D. Heslin-Rees and S. Kazadzis and N. Kouremeti and R. Krejci and D. Mateos and M. Mazzola and C. Ritter and R. Román and K. Stebel and T. Zielinski},

url = {https://acp.copernicus.org/articles/26/1435/2026/},

doi = {10.5194/acp-26-1435-2026},

year  = {2026},

date = {2026-01-28},

urldate = {2026-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {26},

number = {2},

pages = {1435–1457},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Román2025,

title = {Star photometry with all-sky cameras to retrieve aerosol optical depth at nighttime},

author = {R. Román and D. González-Fernández and J. C. Antuña-Sánchez and C. Herrero del Barrio and S. Herrero-Anta and Á. Barreto and V. E. Cachorro and L. Doppler and R. González and C. Ritter and D. Mateos and N. Kouremeti and G. Copes and A. Calle and M. J. Granados-Muñoz and C. Toledano and Á. M. Frutos},

url = {https://amt.copernicus.org/articles/18/2847/2025/},

doi = {10.5194/amt-18-2847-2025},

year  = {2025},

date = {2025-07-04},

urldate = {2025-07-04},

journal = {Atmospheric Measurement Techniques},

volume = {18},

number = {13},

pages = {2847–2875},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{BLUM2025113476,

title = {Geometric calibration of all-sky cameras using sun and moon positions: A comprehensive analysis},

author = {Niklas Blum and Paul Matteschk and Yann Fabel and Bijan Nouri and Roberto Román and Luis F. Zarzalejo and Juan Carlos Antuña-Sánchez and Stefan Wilbert},

url = {https://www.sciencedirect.com/science/article/pii/S0038092X25002397},

doi = {https://doi.org/10.1016/j.solener.2025.113476},

issn = {0038-092X},

year  = {2025},

date = {2025-03-24},

urldate = {2025-01-01},

journal = {Solar Energy},

volume = {295},

pages = {113476},

abstract = {All-sky imagers (ASIs) have been applied to enable accurate very-short-term forecasts of the production of solar power plants and to derive measurements which facilitate the efficient and reliable operation of such plants. Overall, ASIs can support the grid integration and efficient operation of solar power plants. These tasks often require to reconstruct ‘world coordinates’ of observed scene points from their position in the ASI images. This requires a practically feasible geometric calibration of each ASI regarding camera-intrinsic lens distortion parameters and the ASI’s external orientation. We present ‘SuMo’ an open-source Python tool which determines all relevant parameters only using regular ASI images of Sun and Moon. The method avoids a manual interference on-site, can be applied retrospectively and can also be used to continuously monitor an ASI’s geometric calibration. We validate the calibration method on five cameras at three sites and over various datasets representing different seasons, atmospheric conditions, exposure times and sun/ moon elevation and azimuth angles. Already a single month of images from either summer or winter yields an accurate calibration (RMSE ?0.14?). A comparable calibration accuracy (RMSE 0.14 – 0.38?) could be achieved for all tested ASIs without modifying any of the method’s parameters. Image quality moderately influenced the calibration accuracy. An additional cross-validation with the star-based ORION calibration method further confirms the high accuracy of our method over the entire sky dome (MAE 0.14?). We provide a Python package and >2 years of ASI images and irradiance measurements with the publication.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Antuña-Marrero2025b,

title = {Comparing Integrated Water Vapor Sun Photometer Observations Over the Arctic With ERA5 and MERRA-2 Reanalyses},

author = {J. C. Antuña-Marrero and R. Román and V. E. Cachorro and D. Mateos and C. Toledano and A. Calle and J. C. Antuña-Sánchez and R. Gonzalez and M. Antón and J. Vaquero-Martínez and Á.  M. Frutos Baraja},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2024JD041120},

doi = {https://doi.org/10.1029/2024JD041120},

year  = {2025},

date = {2025-03-17},

urldate = {2025-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {130},

number = {6},

pages = {e2024JD041120},

abstract = {Abstract Atmospheric water vapor, a greenhouse gas, is increasing in the Arctic. It is a scientific challenge to understand the causes for this increase and determine adaptation and mitigation actions to confront its climatic effects. During the last decades, spatial and temporal coverage of water vapor satellite observations increased notably, and reanalysis water vapor estimates have steadily improved. However, the scarce spatial and temporal coverage in the Arctic of integrated water vapor (IWV) surface-based observations limits the representativeness of satellite observations and reanalysis estimate validations. Recently, we validated sun photometer IWV (IWVsp) observations with IWV from radiosondes in the Arctic. Here, we compare the hourly means of IWVsp from 13 Arctic AERONET stations and the IWV from ERA-5 and MERRA-2 reanalyses. The comparison is conducted at hourly timescale for individual stations for two Arctic regions and for the whole Arctic. The comparison showed a moist bias of IWV from reanalyses with respect to IWVsp. The individual station wise pattern shows slightly better accuracy and precision for ERA5 than for MERRA-2 also evident at the selected subregional scale. The differences of IWV from ERA5 and MERRA-2 and IWVsp show no dependence on IWVsp nor the solar zenith angle. This study corroborates that IWVsp may be used for validations of satellite IWV observations and IWV reanalyses products.},

note = {e2024JD041120 2024JD041120},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Antuña-Marrero2025,

title = {A Long and Fruitful Cooperation in Atmospheric Aerosol Research between Cuba and Spain},

author = {Juan Carlos Antuña-Marrero and Ángel Frutos and Rene Estevan and Victoria Cachorro and Boris Barja and Sandra Mogo and Albeht Rodríguez-Vega and Carlos Toledano and Frank García and David Mateos and Juan Carlos Antuña-Sánchez and Ramiro González and Jorge Rosas and Roberto Román and Luis Enrique Ramos-Guadalupe and Abel Calle and Iralmy Y. Platero and Carlos Hernández and Nelson Díaz and Joel Díaz},

url = {https://journals.ametsoc.org/view/journals/bams/106/2/BAMS-D-23-0138.1.xml},

doi = {10.1175/BAMS-D-23-0138.1},

year  = {2025},

date = {2025-02-21},

urldate = {2025-01-01},

journal = {Bulletin of the American Meteorological Society},

volume = {106},

number = {2},

pages = {E364 - E377},

publisher = {American Meteorological Society},

address = {Boston MA, USA},

abstract = {Cuban and Spanish scientists have been studying the properties of atmospheric aerosols in Camagüey, Cuba, for more than 15?years, achieving notable scientific results at the local, regional, and global levels. Using instruments and expertise supplied by Spain, Cuban scientists have characterized local aerosol optical and microphysical properties and their chemical composition and optical absorbing properties. Aerosol optical depth (AOD) and Ångström exponent observations were used to validate MODIS satellite observations and broadband AOD from local pyrheliometers. Sun photometer cloud optical depth allowed us to characterize local cloudiness and its radiative forcing. Scientific work included climatologies of the solar radiation for the last four decades at Camagüey and of aerosols in the Caribbean basin in the last two decades. Another result was designing, building, and processing of a low-cost all-sky camera. Besides scientific results, the cooperation allowed the Cuban sun photometer observations to contribute to the Red Ibérica de Medida Fotométrica de Aerosoles and AERONET. A workshop celebrating 10?years of cooperation was held at Camagüey in 2016. The workshop participants evaluated the progress, difficulties, and challenges and inaugurated a Spanish angular calibration bench for solar radiation sensors at Camagüey. The workshop also included the first visit of a NASA scientist to Cuba, the only one visit. Cuban scientists became members of the International Science Team of the NASA Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite mission, just launched, participating in its prelaunch activities. Considering the joint capabilities we developed, Cuban–Spanish contribution is expected for the TEMPO postlaunch validation campaign.},

keywords = {},

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 = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2024JD041120,

title = {Comparing Integrated Water Vapor Sun Photometer Observations Over the Arctic With ERA5 and MERRA-2 Reanalyses},

author = {J. C. Antuña-Marrero and R. Román and V. E. Cachorro and D. Mateos and C. Toledano and A. Calle and J. C. Antuña-Sánchez and R. Gonzalez and M. Antón and J. Vaquero-Martínez and Á.  M. Frutos Baraja},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2024JD041120},

doi = {https://doi.org/10.1029/2024JD041120},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {130},

number = {6},

pages = {e2024JD041120},

abstract = {Abstract Atmospheric water vapor, a greenhouse gas, is increasing in the Arctic. It is a scientific challenge to understand the causes for this increase and determine adaptation and mitigation actions to confront its climatic effects. During the last decades, spatial and temporal coverage of water vapor satellite observations increased notably, and reanalysis water vapor estimates have steadily improved. However, the scarce spatial and temporal coverage in the Arctic of integrated water vapor (IWV) surface-based observations limits the representativeness of satellite observations and reanalysis estimate validations. Recently, we validated sun photometer IWV (IWVsp) observations with IWV from radiosondes in the Arctic. Here, we compare the hourly means of IWVsp from 13 Arctic AERONET stations and the IWV from ERA-5 and MERRA-2 reanalyses. The comparison is conducted at hourly timescale for individual stations for two Arctic regions and for the whole Arctic. The comparison showed a moist bias of IWV from reanalyses with respect to IWVsp. The individual station wise pattern shows slightly better accuracy and precision for ERA5 than for MERRA-2 also evident at the selected subregional scale. The differences of IWV from ERA5 and MERRA-2 and IWVsp show no dependence on IWVsp nor the solar zenith angle. This study corroborates that IWVsp may be used for validations of satellite IWV observations and IWV reanalyses products.},

note = {e2024JD041120 2024JD041120},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{delBarrio2024h,

title = {CAECENET: An automatic system processing photometer and ceilometer data from different networks to provide columnar and vertically-resolved aerosol properties},

author = {Celia Herrero del Barrio and Roberto Román and Ramiro González and Alberto Cazorla and Marcos Herreras-Giralda and Juan Carlos Antuña-Sánchez and Francisco Molero and Francisco Navas-Guzmán and Antonio Serrano and María Ángeles Obregón and Yolanda Sola and Marco Pandolfi and Sara Herrero-Anta and Daniel González-Fernández and Jorge Muñiz-Rosado and David Mateos and Abel Calle and Carlos Toledano and Victoria E. Cachorro and Ángel M. de Frutos},

doi = {10.1371/journal.pone.0311990},

year  = {2024},

date = {2024-12-27},

urldate = {2024-12-27},

journal = {PloS one},

volume = {19},

number = {12},

pages = {e0311990},

publisher = {Public Library of Science San Francisco, CA USA},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{rs16203821,

title = {Retrieval of Solar Shortwave Irradiance from All-Sky Camera Images},

author = {Daniel González-Fernández and Roberto Román and David Mateos and Celia Herrero del Barrio and Victoria E. Cachorro and Gustavo Copes and Ricardo Sánchez and Rosa Delia García and Lionel Doppler and Sara Herrero-Anta and Juan Carlos Antuña-Sánchez and África Barreto and Ramiro González and Javier Gatón and Abel Calle and Carlos Toledano and Ángel Frutos},

url = {https://www.mdpi.com/2072-4292/16/20/3821},

doi = {10.3390/rs16203821},

issn = {2072-4292},

year  = {2024},

date = {2024-10-14},

urldate = {2024-01-01},

journal = {Remote Sensing},

volume = {16},

number = {20},

abstract = {The present work proposes a new model based on a convolutional neural network (CNN) to retrieve solar shortwave (SW) irradiance via the estimation of the cloud modification factor (CMF) from daytime sky images captured by all-sky cameras; this model is named CNN-CMF. To this end, a total of 237,669 sky images paired with SW irradiance measurements obtained by using pyranometers were selected at the following three sites: Valladolid and Izaña, Spain, and Lindenberg, Germany. This dataset was randomly split into training and testing sets, with the latter excluded from the training model in order to validate it using the same locations. Subsequently, the test dataset was compared with the corresponding SW irradiance measurements obtained by the pyranometers in scatter density plots. The linear fit shows a high determination coefficient (R2) of 0.99. Statistical analyses based on the mean bias error (MBE) values and the standard deviation (SD) of the SW irradiance differences yield results close to ?2% and 9%, respectively. The MBE indicates a slight underestimation of the CNN-CMF model compared to the measurement values. After its validation, model performance was evaluated at the Antarctic station of Marambio (Argentina), a location not used in the training process. A similar comparison between the model-predicted SW irradiance and pyranometer measurements yielded R2=0.95, with an MBE of around 2% and an SD of approximately 26%. Although the precision provided by the SD at the Marambio station is lower, the MBE shows that the model’s accuracy is similar to previous results but with a slight overestimation of the SW irradiance. Finally, the determination coefficient improved to 0.99, and the MBE and SD are about 3% and 11%, respectively, when the CNN-CMF model is used to estimate daily SW irradiation values.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gonzalez2024CCNeural,

title = {A neural network to retrieve cloud cover from all-sky cameras: A case of study over Antarctica},

author = {Daniel González-Fernández and Roberto Román and Juan Carlos Antuña-Sánchez and Victoria E. Cachorro and Gustavo Copes and Sara Herrero-Anta and Celia Herrero del Barrio and África Barreto and Ramiro González and Ramón Ramos and Patricia Martín and David Mateos and Carlos Toledano and Abel Calle and Ángel Frutos},

url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.4834},

doi = {https://doi.org/10.1002/qj.4834},

year  = {2024},

date = {2024-08-28},

journal = {Quarterly Journal of the Royal Meteorological Society},

volume = {n/a},

number = {n/a},

abstract = {Abstract We present a new model based on a convolutional neural network (CNN) to predict daytime cloud cover (CC) from sky images captured by all-sky cameras, which is called CNN-CC. A total of 49,016 daytime sky images, recorded at different Spanish locations (Valladolid, La Palma, and Izaña) from two different all-sky camera types, are manually classified into different CC (oktas) values by trained researchers. Subsequently, the images are randomly split into a training set and a test set to validate the model. The CC values predicted by the CNN-CC model are compared with the observations made by trained people on the test set, which serve as reference. The predicted CC values closely match the reference values within ±$$ ± $$1?oktas in 99% of the cloud-free and overcast cases. Moreover, this percentage is above 93% for the rest of partially cloudy cases. The mean bias error (MBE) and standard deviation (SD) of the differences between the predicted and reference CC values are calculated, resulting in MBE=0.007$$ mathrmMBE=0.007 $$?oktas and SD=0.674$$ mathrmSD=0.674 $$?oktas. The MBE and SD are also represented for different intervals of measured aerosol optical depth and Ångström exponent values, revealing that the performance of the CNN-CC model does not depend on aerosol load or size. Once the model is validated, the CC obtained from a set of images captured every 5?min, from January 2018 to March 2022, at the Antarctic station of Marambio (Argentina) is compared against direct field observations of CC (not from images) taken at this location, which is not used in the training process. As a result, the model slightly underestimates the observations with an MBE of ?$$ - $$0.3?oktas. The retrieved data are analyzed in detail. The monthly and annual CC values are calculated. Overcast conditions are the most frequent, accounting for 46.5% of all observations throughout the year, rising to 64.5% in January. The annual mean CC value at this location is 5.5?oktas, with a standard deviation of approximately 3.1?oktas. A similar analysis is conducted, separating data by hours, but no significant diurnal cycles are observed except for some isolated months.},

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tppubtype = {article}

}