Sara Herrero-Anta

This study presents a refined, automated in near-real time methodology to obtain cloud height maps using a network of 20 all-sky cameras. This low-cost and easily manipulated instruments are distributed in the city of Valladolid, Spain, trying to cover uniformly an estimated area up to 200 km ² , with the actual spatial coverage depending on cloud height. Camera distances vary from more than 50 km to less than 200 m, in order to have different viewing angles of the clouds above them. All these cameras are geometrically calibrated and maintained within GOA-SCAN (Group of Atmospheric Optics all-Sky CAmeras Network). The methodology utilizes a stereoscopic approach, pairing simultaneous images from all the cameras. Correlation between the image pixels is computed in order to find the same sky point in both images. Then knowing the baseline distance and the orientation of the cameras, the height of every pixel identified as cloudy is computed. This is repeated for all the camera pairs that have a significant overlapping field of view. Filtering criteria are applied to retain only the significant values. With this methodology, cloud base and top heights (CBH and CTH) maps with a 50 m spatial resolution are obtained every five minutes during daytime and every two minutes for nighttime. These maps are compared with the scene classification product from Sentinel-2 satellite images, finding significant agreement. Some discrepancies were found for high transparent clouds and cloud edges. In addition, all CBH and CTH data available during two and a half years are compared against the independent values measured by a ceilometer collocated with one of the cameras. The determination coefficient for the median CBH values within a circular 150 m distance is 0.93. The obtained CTH values tend to overestimate the ceilometer ones and have wider dispersion, with lower determination coefficient of 0.72. Illuminating conditions are crucial for the correct segmentation of cloudy pixels, limiting the performance of the algorithm at nighttime. Overall, the proposed methodology is promising for obtaining cloud spatial masks and cloud height maps, over different cloud types, layering and conditions.

Atmospheric aerosols are among the key factors affecting the Earth's radiation budget, playing a fundamental role in understanding climate forcing, feedback mechanisms, and their impact on future climate projections and on solar energy systems. More specifically, dust aerosol particles, which are characterized by high complexity of their optical and microphysical properties, remain one of the most uncertain components. In this study, we focus on four severe dust events across multiple sites in the broader Mediterranean Basin between 2021 and 2022. We employ a combination of ground-based remote sensing observations along with Radiative Transfer (RT) modelling, with the libRadtran package and METAL-WRF scheme, as well as photovoltaic (PV) power generation simulations using the Global Solar Energy Estimator (GSEE) to investigate the impact of the different optical and geometrical aspects of these events on solar radiation and solar energy. The results revealed that the strongest dust-induced attenuation under clear-sky conditions was systematically observed in the direct component of solar radiation (DNI), with maximum losses frequently exceeding 60 %–80 %, while Global Horizontal Irradiance (GHI) typically ranged between 5 % and 25 %. These findings were reflected directly into substantial PV power output losses, for both fixed-tilt and two-axis tracking systems, reaching ∼ 45 % and 80 %, respectively, with the impact on the latter being significantly higher due to their strong dependence on DNI. A sensitivity analysis based on how aerosol optical properties and solar geometry jointly influence PV energy production revealed that Solar Zenith Angle (SZA) plays the most dominant role, followed by Aerosol Optical Depth (AOD), which leads to strong attenuation independently of SZA under altered aerosol load conditions. Finally, the comparison of the modelled PV output estimated from the modelled irradiances based on the two different RT models with the PV output considering ground-based GHI measurements revealed a similar agreement under clear sky conditions, while under cloudy conditions, the analysis revealed the critical role of the diffuse horizontal irradiance (DHI) component in the simulations.

Dust events frequently affect the Mediterranean Basin, however, the evolution of their optical and microphysical properties during transport remains poorly characterized. This study examines four major dust outbreaks in 2021–2022 affecting the Mediterranean, originating from the Eastern, Western, and Central Sahara and the Middle East. Combining ground-based AERONET sun photometers (24 stations), satellite (IASI, MODIS MIDAS) dust optical depth (DOD) data, and HYSPLIT back-trajectories, we track these events across Mediterranean sites. Results reveal regional differences in dust optical properties, including aerosol optical depth, single scattering albedo, and asymmetry factor, arising from source regions and transport processes. The Saharan events examined were dominated by coarse, scattering mineral dust, while the event originating from the Middle East featured finer, more absorbing particles, likely influenced by anthropogenic sources. MIDAS DOD-to-AOD ratios indicate that only one East-Central Saharan event maintained high dust fractions (DOD-to-AOD >0.8), suggesting relatively pure dust, while other events exhibited stronger spatial variability, with the Middle East event showing the lowest ratios, reflecting enhanced mixing with anthropogenic or marine aerosols. A regional case study in Cyprus using in situ elemental and absorption measurements shows that Middle Eastern dust event, despite lower mass concentrations, exhibited stronger absorption than the Saharan dust events observed in Cyprus. METAL-WRF mineralogical simulations indicate broadly similar mineral fractions across events, which alone could not explain the optical variability that observed across events. UAV-based composition data provide a first case-specific evaluation of modeled variability, although discrepancies in aluminum and magnesium highlight limitations in current dust representations.

This study presents a refined, automated in near-real time methodology to obtain cloud height maps using a network of 20 all-sky cameras. This low cost and easily manipulated instruments are distributed in the city of Valladolid, Spain, trying to cover uniformly an estimated area up to 200 km², with the actual spatial coverage depending on cloud height. Camera distances vary from 16 km to less than 1 km, in order to have different viewing angles of the clouds above them. All this cameras are geometrically calibrated and maintained within GOA-SCAN (Group of Atmospheric Optics all-Sky CAmeras Network). The methodology utilizes a stereoscopic approach, pairing simultaneous images from all the cameras. Correlation between the image pixels is computed in order to find the same sky point in both images. Then knowing the baseline distance and the orientation of the cameras, the height of every pixel identified as cloudy is computed. This is repeated for all the camera pairs that have a significant overlapping field of view. Filtering criteria are applied to retain only the significant values. With this methodology, cloud base and top heights (CBH and CTH) maps with a 50 m spatial resolution are obtained every five minutes during daytime and every two minutes for nighttime. These maps are compared with the scene classification product from Sentinel-2 satellite images, finding significant agreement. Some discrepancies were found for high transparent clouds and cloud edges. In addition, all CBH and CTH data available during two and a half years are compared against the independent values measured by a ceilometer collocated with one of the cameras. The determination coefficient for the median CBH values within a circular 150 m distance is 0.93. The obtained CTH values tend to overestimate the ceilometer ones and have wider dispersion, with lower determination coefficient of 0.72. Illuminating conditions are crucial for the correct segmentation of cloudy pixels, limiting the performance of the algorithm at nighttime. Overall, the proposed methodology is promising for obtaining cloud spatial masks and cloud height maps, over different cloud types, layering and conditions.

This study presents a refined, automated in near-real time methodology to obtain cloud height maps using a network of 20 all-sky cameras. This low cost and easily manipulated instruments are distributed in the city of Valladolid, Spain, trying to cover uniformly an estimated area up to 200 km², with the actual spatial coverage depending on cloud height. Camera distances vary from 16 km to less than 1 km, in order to have different viewing angles of the clouds above them. All this cameras are geometrically calibrated and maintained within GOA-SCAN (Group of Atmospheric Optics all-Sky CAmeras Network). The methodology utilizes a stereoscopic approach, pairing simultaneous images from all the cameras. Correlation between the image pixels is computed in order to find the same sky point in both images. Then knowing the baseline distance and the orientation of the cameras, the height of every pixel identified as cloudy is computed. This is repeated for all the camera pairs that have a significant overlapping field of view. Filtering criteria are applied to retain only the significant values. With this methodology, cloud base and top heights (CBH and CTH) maps with a 50 m spatial resolution are obtained every five minutes during daytime and every two minutes for nighttime. These maps are compared with the scene classification product from Sentinel-2 satellite images, finding significant agreement. Some discrepancies were found for high transparent clouds and cloud edges. In addition, all CBH and CTH data available during two and a half years are compared against the independent values measured by a ceilometer collocated with one of the cameras. The determination coefficient for the median CBH values within a circular 150 m distance is 0.93. The obtained CTH values tend to overestimate the ceilometer ones and have wider dispersion, with lower determination coefficient of 0.72. Illuminating conditions are crucial for the correct segmentation of cloudy pixels, limiting the performance of the algorithm at nighttime. Overall, the proposed methodology is promising for obtaining cloud spatial masks and cloud height maps, over different cloud types, layering and conditions.

Dust events frequently affect the Mediterranean Basin, however, the evolution of their optical and microphysical properties during transport remains poorly characterized. This study examines four major dust outbreaks in 2021–2022 affecting the Mediterranean, originating from the Eastern, Western, and Central Sahara and the Middle East. Combining ground-based AERONET sun photometers (24 stations), satellite (IASI, MODIS MIDAS) dust optical depth (DOD) data, and HYSPLIT back-trajectories, we track these events across multiple Mediterranean sites. Results reveal clear regional differences in dust optical properties, such as aerosol optical depth, single scattering albedo, and asymmetry factor, arising from source regions and transport processes. Saharan events are dominated by coarse, scattering mineral dust, while the Middle East event featured finer, more absorbing particles, likely influenced by anthropogenic sources. MIDAS DOD-to-AOD ratios indicate that only one East-Central Saharan event maintained high dust fractions (DOD-to-AOD > 0.8), suggesting relatively pure dust, while other events exhibited stronger spatial variability, with the Middle East event showing the lowest ratios, reflecting enhanced mixing with anthropogenic or marine aerosols. A regional case study in Cyprus using in situ elemental and absorption measurements shows that Middle East dust, despite lower mass concentrations, exhibits stronger absorption than Saharan dust. METAL-WRF mineralogical simulations indicate broadly similar dominant mineral fractions (silicates and calcium-rich minerals) across events, suggesting that optical variability was mainly driven by dust-to-total aerosol ratio and mixing state rather than mineralogy. UAV-based composition data further validate modeled variability, although discrepancies in aluminum and magnesium highlight limitations in current dust representations.

Atmospheric aerosols are among the key factors affecting the Earth’s radiation budget, playing a fundamental role in understanding climate forcing, feedback mechanisms, and their impact on future climate projections and on solar energy systems. More specifically, dust aerosol particles, which are characterized by high complexity of their optical and microphysical properties, remain one of the most uncertain components. In this study, we focus on four severe dust events across multiple sites in the broader Mediterranean Basin between 2021 and 2022. We employ a combination of ground-based remote sensing observations along with Radiative Transfer (RT) modelling, with the libRadtran package and METAL-WRF scheme, as well as photovoltaic (PV) power generation simulations using the Global Solar Energy Estimator (GSEE) to investigate the impact of the different optical and geometrical aspects of these events on solar radiation and solar energy. The results revealed that the strongest dust-induced attenuation was systematically observed in the direct component of solar radiation (DNI), with maximum losses frequently exceeding 60–80%, while Global Horizontal Irradiance (GHI) typically ranged between 5% and 25%. These findings were reflected directly into substantial PV power output losses, for both fixed tilt and two-axis tracking systems, reaching ~45% and 80%, respectively, with the impact on the latter being significantly higher due to their strong dependence on DNI. A sensitivity analysis based on how aerosol optical properties and solar geometry jointly influence PV energy production revealed that Solar Zenith Angle (SZA) plays the most dominant role, followed by Aerosol Optical Depth (AOD), which leads to strong attenuation independently of SZA under altered aerosol load conditions. Finally, the comparison of the modelled PV output estimated from the modelled irradiances based on the two different RT models with the PV output considering ground-based GHI measurements revealed a similar agreement under clear sky conditions, while under cloudy conditions, the analysis revealed the critical role of the diffuse horizontal irradiance (DHI) component in the simulations.

Dust events frequently affect the Mediterranean Basin, however, the evolution of their optical and microphysical properties during transport remains poorly characterized. This study examines four major dust outbreaks in 2021–2022 affecting the Mediterranean, originating from the Eastern, Western, and Central Sahara and the Middle East. Combining ground-based AERONET sun photometers (24 stations), satellite (IASI, MODIS MIDAS) dust optical depth (DOD) data, and HYSPLIT back-trajectories, we track these events across multiple Mediterranean sites. Results reveal clear regional differences in dust optical properties, such as aerosol optical depth, single scattering albedo, and asymmetry factor, arising from source regions and transport processes. Saharan events are dominated by coarse, scattering mineral dust, while the Middle East event featured finer, more absorbing particles, likely influenced by anthropogenic sources. MIDAS DOD-to-AOD ratios indicate that only one East-Central Saharan event maintained high dust fractions (DOD-to-AOD > 0.8), suggesting relatively pure dust, while other events exhibited stronger spatial variability, with the Middle East event showing the lowest ratios, reflecting enhanced mixing with anthropogenic or marine aerosols. A regional case study in Cyprus using in situ elemental and absorption measurements shows that Middle East dust, despite lower mass concentrations, exhibits stronger absorption than Saharan dust. METAL-WRF mineralogical simulations indicate broadly similar dominant mineral fractions (silicates and calcium-rich minerals) across events, suggesting that optical variability was mainly driven by dust-to-total aerosol ratio and mixing state rather than mineralogy. UAV-based composition data further validate modeled variability, although discrepancies in aluminum and magnesium highlight limitations in current dust representations.

Dust events frequently affect the Mediterranean Basin, however, the evolution of their optical and microphysical properties during transport remains poorly characterized. This study examines four major dust outbreaks in 2021–2022 affecting the Mediterranean, originating from the Eastern, Western, and Central Sahara and the Middle East. Combining ground-based AERONET sun photometers (24 stations), satellite (IASI, MODIS MIDAS) dust optical depth (DOD) data, and HYSPLIT back-trajectories, we track these events across multiple Mediterranean sites. Results reveal clear regional differences in dust optical properties, such as aerosol optical depth, single scattering albedo, and asymmetry factor, arising from source regions and transport processes. Saharan events are dominated by coarse, scattering mineral dust, while the Middle East event featured finer, more absorbing particles, likely influenced by anthropogenic sources. MIDAS DOD-to-AOD ratios indicate that only one East-Central Saharan event maintained high dust fractions (DOD-to-AOD > 0.8), suggesting relatively pure dust, while other events exhibited stronger spatial variability, with the Middle East event showing the lowest ratios, reflecting enhanced mixing with anthropogenic or marine aerosols. A regional case study in Cyprus using in situ elemental and absorptionmeasurements shows that Middle East dust, despite lower mass concentrations, exhibits stronger absorption than Saharan dust.METAL-WRF mineralogical simulations indicate broadly similar dominant mineral fractions (silicates and calcium-rich minerals) across events, suggesting that optical variability was mainly driven by dust-to-total aerosol ratio and mixing state rather than mineralogy. UAV-based composition data further validate modeled variability, although discrepancies in aluminum and magnesium highlight limitations in current dust representations.