Mission
 |
The Atmospheric Optics Group of Valladolid University (GOA-UVa) is involved in the study of atmospheric components, mainly aerosols, with optical methods. The GOA calibration facility is devoted to radiometric calibration of optical instrumentations such as photometers, and it is part of the AERONET-Europe Central Facility, partially funded by the European Union. As a university group, our researchers carry out educational and training activity (graduate, master and PhD thesis). In this site you can find information about the work of the group, members, research lines, publications, projects, vacancies, etc. |
Latests 5 Publications
2025
1.
Sara Herrero-Anta; Roberto Román; Daniel González-Fernández; Claudia Emde; David Mateos; Celia Herrero Barrio; Ramiro González; Oleg Dubovik; Carlos Toledano; Abel Calle; Victoria E. Cachorro; Bernhard Mayer; Ángel M. de Frutos
Impact of cloud presence on sky radiances and the retrieval of aerosol properties Journal Article
In: Atmospheric Research, vol. 317, pp. 107938, 2025, ISSN: 0169-8095.
@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}
}
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.
2.
Rosa D. García; África Barreto; Celia Rey; Eugenio Fraile-Nuez; Alba González-Vega; Sergio F. León-Luis; Antonio Alcantara; A. Fernando Almansa; Carmen Guirado-Fuentes; Pablo González-Sicilia; Victoria E. Cachorro; Frederic Bouchar
Aerosol retrievals derived from a low-cost Calitoo sun-photometer taken on board a research vessel Journal Article
In: Atmospheric Environment, vol. 341, pp. 120888, 2025, ISSN: 1352-2310.
@article{García2025,
title = {Aerosol retrievals derived from a low-cost Calitoo sun-photometer taken on board a research vessel},
author = {Rosa D. García and África Barreto and Celia Rey and Eugenio Fraile-Nuez and Alba González-Vega and Sergio F. León-Luis and Antonio Alcantara and A. Fernando Almansa and Carmen Guirado-Fuentes and Pablo González-Sicilia and Victoria E. Cachorro and Frederic Bouchar},
url = {https://www.sciencedirect.com/science/article/pii/S1352231024005636},
doi = {https://doi.org/10.1016/j.atmosenv.2024.120888},
issn = {1352-2310},
year = {2025},
date = {2025-01-15},
urldate = {2025-01-15},
journal = {Atmospheric Environment},
volume = {341},
pages = {120888},
abstract = {This study presents a comprehensive 5-year period assessment of aerosol optical depth (AOD) and Å ngströn Exponent (AE) data from a hand-held Calitoo sun photometer on board the Ángeles Alvariño research vessel. Observations spanned March 2018 to September 2023, focusing on key maritime regions such as the Canary Islands, coasts of North Africa, the Mediterranean, Portugal, the Cantabrian, and the Bay of Biscay. The Calitoo device measures solar irradiance at three wavelengths (465, 540, and 619 nm). Uncertainty analysis for Calitoo AOD retrievals was performed using the Monte Carlo method, yielding an expanded uncertainty (UAOD) ranging between 0.008 and 0.050 with a mean and standard deviation of 0.032 ± 0.008 for the three wavelengths. Our results also highlight the remarkable calibration stability of the Calitoo (< 2.6%) over this 5-year period. Calitoo AOD values were assessed using reference AOD data from Santa Cruz de Tenerife (the Canary Islands), El Arenosillo (Huelva), and Palma de Mallorca (the Balearic Islands) AERONET (Aerosol Robotic Network) stations. The comparison revealed a good agreement with correlation coefficients ranging from 0.727 to 0.917 and mean bias ranging from -0.030 to -0.001. Additionally, the Calitoo AOD data were compared with MODIS (Moderate Resolution Imaging Spectroradiometer) and CAMS-ECMWF (Copernicus Atmosphere Monitoring Service-European Centre for Medium-Range Weather Forecasts) aerosol products obtaining that Calitoo AOD values were generally lower, showing negative mean bias of -0.063 and -0.024, respectively. The aerosol characterizations using AE vs. AOD plots in the three maritime study regions using 5-years of non-routine Calitoo data are similar to the corresponding aerosol characterizations performed with simultaneous AERONET-Cimel data. These findings underscore Calitoo’s reliability for aerosol studies in regions where AERONET instruments or other aerosol networks are unavailable. Likewise, given the low cost of Calitoo photometers, they could be deployed onboard a large number of merchant and passenger ships or in other remote or under-monitored areas, providing near real-time AOD/AE data to enhance our understanding of aerosols processes or for model or satellite assimilation/validation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This study presents a comprehensive 5-year period assessment of aerosol optical depth (AOD) and Å ngströn Exponent (AE) data from a hand-held Calitoo sun photometer on board the Ángeles Alvariño research vessel. Observations spanned March 2018 to September 2023, focusing on key maritime regions such as the Canary Islands, coasts of North Africa, the Mediterranean, Portugal, the Cantabrian, and the Bay of Biscay. The Calitoo device measures solar irradiance at three wavelengths (465, 540, and 619 nm). Uncertainty analysis for Calitoo AOD retrievals was performed using the Monte Carlo method, yielding an expanded uncertainty (UAOD) ranging between 0.008 and 0.050 with a mean and standard deviation of 0.032 ± 0.008 for the three wavelengths. Our results also highlight the remarkable calibration stability of the Calitoo (< 2.6%) over this 5-year period. Calitoo AOD values were assessed using reference AOD data from Santa Cruz de Tenerife (the Canary Islands), El Arenosillo (Huelva), and Palma de Mallorca (the Balearic Islands) AERONET (Aerosol Robotic Network) stations. The comparison revealed a good agreement with correlation coefficients ranging from 0.727 to 0.917 and mean bias ranging from -0.030 to -0.001. Additionally, the Calitoo AOD data were compared with MODIS (Moderate Resolution Imaging Spectroradiometer) and CAMS-ECMWF (Copernicus Atmosphere Monitoring Service-European Centre for Medium-Range Weather Forecasts) aerosol products obtaining that Calitoo AOD values were generally lower, showing negative mean bias of -0.063 and -0.024, respectively. The aerosol characterizations using AE vs. AOD plots in the three maritime study regions using 5-years of non-routine Calitoo data are similar to the corresponding aerosol characterizations performed with simultaneous AERONET-Cimel data. These findings underscore Calitoo’s reliability for aerosol studies in regions where AERONET instruments or other aerosol networks are unavailable. Likewise, given the low cost of Calitoo photometers, they could be deployed onboard a large number of merchant and passenger ships or in other remote or under-monitored areas, providing near real-time AOD/AE data to enhance our understanding of aerosols processes or for model or satellite assimilation/validation.
2024
3.
Celia Herrero del Barrio; Roberto Román; Ramiro González; Alberto Cazorla; Marcos Herreras-Giralda; Juan Carlos Antuña-Sánchez; Francisco Molero; Francisco Navas-Guzmán; Antonio Serrano; María Ángeles Obregón; Yolanda Sola; Marco Pandolfi; Sara Herrero-Anta; Daniel González-Fernández; Jorge Muñiz-Rosado; David Mateos; Abel Calle; Carlos Toledano; Victoria E. Cachorro; Ángel M. de Frutos
In: PloS one, vol. 19, no. 12, pp. e0311990, 2024.
@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}
}
4.
Daniel González-Fernández; Roberto Román; David Mateos; Celia Herrero del Barrio; Victoria E. Cachorro; Gustavo Copes; Ricardo Sánchez; Rosa Delia García; Lionel Doppler; Sara Herrero-Anta; Juan Carlos Antuña-Sánchez; África Barreto; Ramiro González; Javier Gatón; Abel Calle; Carlos Toledano; Ángel Frutos
Retrieval of Solar Shortwave Irradiance from All-Sky Camera Images Journal Article
In: Remote Sensing, vol. 16, no. 20, 2024, ISSN: 2072-4292.
@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}
}
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.
5.
Xindan Zhang; Lei Li; Huizheng Che; Oleg Dubovik; Yevgeny Derimian; Brent Holben; Pawan Gupta; Thomas F. Eck; Elena S. Lind; Carlos Toledano; Xiangao Xia; Yu Zheng; Ke Gui; Xiaoye Zhang
Aerosol Components Derived from Global AERONET Measurements by GRASP: A New Value-Added Aerosol Component Global Dataset and Its Application Journal Article
In: Bulletin of the American Meteorological Society, vol. 105, no. 10, pp. E1822 - E1848, 2024.
@article{Zhang2024Aerosol,
title = {Aerosol Components Derived from Global AERONET Measurements by GRASP: A New Value-Added Aerosol Component Global Dataset and Its Application},
author = {Xindan Zhang and Lei Li and Huizheng Che and Oleg Dubovik and Yevgeny Derimian and Brent Holben and Pawan Gupta and Thomas F. Eck and Elena S. Lind and Carlos Toledano and Xiangao Xia and Yu Zheng and Ke Gui and Xiaoye Zhang},
url = {https://journals.ametsoc.org/view/journals/bams/105/10/BAMS-D-23-0260.1.xml},
doi = {10.1175/BAMS-D-23-0260.1},
year = {2024},
date = {2024-10-14},
urldate = {2024-01-01},
journal = {Bulletin of the American Meteorological Society},
volume = {105},
number = {10},
pages = {E1822 - E1848},
publisher = {American Meteorological Society},
address = {Boston MA, USA},
keywords = {},
pubstate = {published},
tppubtype = {article}
}