Ioannis-Panagiotis Raptis

The third campaign for the calibration and intercomparison of solar UV radiometers (UVC III) took place at Davos, Switzerland in June–August 2022. More than 70 radiometers participated in the campaign and measured side-by-side with the portable reference spectroradiometer QASUME. The UVIOS2 system is a flexible UVI modelling tool that can be exploited for different applications depending on the inputs. Thus, different combinations of satellite, reanalysis, and/or ground-based inputs were used to test the UVIOS2 performance when it is used as a tool for UVI nowcasting or for climatological studies. While UVIOS2 provided quite accurate estimates of the average (for the period of the campaign) UVI levels, larger deviations were found for individual estimates. The average agreement between the UVI from the UVIOS2 and QASUME was better than 1 % for all the different sets of inputs that were used for the study. The range of the variability was of the order of 40 % for instantaneous measurements (15 min), mainly due to the model's inability to capture the instantaneous effects of cloudiness, especially under broken cloud conditions. Under clear-sky conditions the model was found to perform much better, with the differences between the model estimates and the QASUME measurements being smaller than 12 % for 95 % of the studied cases. Even at the pristine environment of Davos, single scattering albedo (SSA) was found to contribute significantly to the modelling uncertainties under cloudless conditions. For Aerosol Optical Depth (AOD) of the order of 0.2–0.4 at 550 nm, the role of the SSA was found to be comparable to the role of AOD in the modelling of the UVI.

Aerosols significantly attenuate solar radiation and influence atmospheric thermodynamic stability, particularly over regions like the Atlantic, impacting Earth's energy budget and climate through radiative heating or cooling. Quantifying these effects is challenging due to aerosol diversity and complexity. For desert dust particles, the difficulty lies in defying their optical properties and accurately monitoring their extensive distribution.This study aims to assess the radiative effects of dust aerosols and water vapor (WV), and their impact on atmospheric heating rates, by adopting non-spherical particle shapes and their intrinsic microphysical and optical properties during severe dust events. To achieve this, ground-based, airborne, and satellite observations are employed along with Radiative Transfer (RT) modeling, and more precisely the libRadtran RT package (Mayer and Kylling, 2005; Emde et al., 2016). The study utilizes data from two experimental campaigns – ASKOS and ORCESTRA/PERCUSION – both conducted in the Atlantic region during peak trans-Atlantic dust transport periods, in summers of 2022 and 2024.In the frame of the ASKOS ESA Joint Aeolus Tropical Atlantic Campaign (JATAC), we utilized ground-based remote sensing and airborne in-situ observations, including solar radiation and airborne meteorological profiles. Microphysical properties from UAVs, MOPSMAP (Gasteiger and Wiegner, 2018) and TAMUdust2020 (Saito et al., 2021) scattering databases were used to derive dust optical properties considering a mixture of spheroidal and irregular-hexahedra shapes. Multi-wavelength lidar measurements contributed to the validation of the optical properties and dust vertical distribution. RT simulations incorporated WV concentration, to investigate dust-WV-solar radiation interactions under clear sky conditions. The simulated broadband shortwave radiation was, finally, compared with the ground-based solar radiation measurements.A second case study was performed, leveraging ORCESTRA/PERCUSION campaign (https://orcestra-campaign.org/percusion.html) synergistic airborne measurements. This campaign incorporated a comprehensive suite of airborne instruments, providing, amongst others, radiation measurements, meteorological profiles, and extensive lidar measurements. Radiation at the top of the atmosphere (TOA) from the EarthCARE ESA mission supported comprehensive closure studies at TOA and at aircraft level.Acknowledgements This research was financially supported by the PANGEA4CalVal project (Grant Agreement 101079201) funded by the European Union, the CERTAINTY project (Grant Agreement 101137680) funded by Horizon Europe program and the AIRSENSE project which is part of Atmosphere Science Cluster of ESA’s EO Science for Society programme. DK, ΑΤ, ΚP, PR and SK would like to acknowledge COST Action HARMONIA (International network for harmonization of atmospheric aerosol retrievals from ground-based photometers), CA21119, supported by COST (European Cooperation in Science and Technology).References Mayer, B., Kylling, A.: Technical note: The libRadtran software package for radiative transfer calculations - description and examples of use. Atmos. Chem. Phys., 5(7), 1855–1877, 2005.Emde, C., et al.: The libRadtran software package for radiative transfer calculations (version 2.0.1), Geoscientific Model Development, 9(5), 1647–1672, 2016.Gasteiger, J. and Wiegner, M.: MOPSMAP v1.0: a versatile tool for the modeling of aerosol optical properties, Geosci. Model Dev., 11, 2739–2762, https://doi.org/10.5194/gmd-11-2739-2018, 2018.Saito, M., et al.: A comprehensive database of the optical properties of irregular aerosol particles for radiative transfer simulations, J. Atmos. Sci., in press, https://doi.org/10.1175/JAS-D-20-0338.1, 2021.

The third campaign for the calibration and intercomparison of solar UV radiometers (UVC III) took place at Davos, Switzerland in June–August 2022. More than 70 radiometers participated in the campaign and measured side-by-side with the portable reference spectroradiometer QASUME. By using inputs from various sources, the UVIOS2 system was used to estimate the UV index (UVI) for the site of the campaign. The UVIOS2 system is a flexible UVI modelling tool that can be exploited for different applications depending on the inputs. Thus, different combinations of satellite, reanalysis, and/or ground-based inputs were used to test the UVIOS2 performance when it is used as a tool for UVI nowcasting or for climatological studies. While UVIOS2 provided quite accurate estimates of the average (for the period of the campaign) UVI levels, larger deviations were found for individual estimates. The average agreement between the UVI from the UVIOS2 and QASUME was better than 1 % for all the different sets of inputs that were used for the study. The range of the variability was of the order of 40 % for instantaneous measurements (15 min), mainly due to the model’s inability to capture the instantaneous effects of cloudiness, especially under broken cloud conditions. Under clear-sky conditions the model was found to perform much better, with the differences between the model estimates and the QASUME measurements being smaller than 12 % for 95 % of the studied cases. Even at the pristine environment of Davos, single scattering albedo (SSA) was found to contribute significantly to the modelling uncertainties under cloudless conditions. For relatively small Aerosol Optical Depth (AOD), of the order of 0.2 – 0.4, the role of the SSA was found to be comparable to the role of AOD in the modelling of the UVI. Radiometers that were not properly maintained and/or calibrated were found to provide UVI measurements with uncertainty that was comparable to the uncertainty of the UVIOS2 estimates, which highlights the significance of systematic maintenance and calibration of the UV radiometers.

The third campaign for the calibration and intercomparison of solar UV radiometers (UVC III) took place at Davos, Switzerland in June–August 2022. More than 70 radiometers participated in the campaign and measured side-by-side with the portable reference spectroradiometer QASUME. By using inputs from various sources, the UVIOS2 system was used to estimate the UV index (UVI) for the site of the campaign. The UVIOS2 system is a flexible UVI modelling tool that can be exploited for different applications depending on the inputs. Thus, different combinations of satellite, reanalysis, and/or ground-based inputs were used to test the UVIOS2 performance when it is used as a tool for UVI nowcasting or for climatological studies. While UVIOS2 provided quite accurate estimates of the average (for the period of the campaign) UVI levels, larger deviations were found for individual estimates. The average agreement between the UVI from the UVIOS2 and QASUME was better than 1 % for all the different sets of inputs that were used for the study. The range of the variability was of the order of 40 % for instantaneous measurements (15 min), mainly due to the model’s inability to capture the instantaneous effects of cloudiness, especially under broken cloud conditions. Under clear-sky conditions the model was found to perform much better, with the differences between the model estimates and the QASUME measurements being smaller than 12 % for 95 % of the studied cases. Even at the pristine environment of Davos, single scattering albedo (SSA) was found to contribute significantly to the modelling uncertainties under cloudless conditions. For relatively small Aerosol Optical Depth (AOD), of the order of 0.2 – 0.4, the role of the SSA was found to be comparable to the role of AOD in the modelling of the UVI. Radiometers that were not properly maintained and/or calibrated were found to provide UVI measurements with uncertainty that was comparable to the uncertainty of the UVIOS2 estimates, which highlights the significance of systematic maintenance and calibration of the UV radiometers.

The third campaign for the calibration and intercomparison of solar UV radiometers (UVC III) took place at Davos, Switzerland in June–August 2022. More than 70 radiometers participated in the campaign and measured side-by-side with the portable reference spectroradiometer QASUME. By using inputs from various sources, the UVIOS2 system was used to estimate the UV index (UVI) for the site of the campaign. The UVIOS2 system is a flexible UVI modelling tool that can be exploited for different applications depending on the inputs. Thus, different combinations of satellite, reanalysis, and/or ground-based inputs were used to test the UVIOS2 performance when it is used as a tool for UVI nowcasting or for climatological studies. While UVIOS2 provided quite accurate estimates of the average (for the period of the campaign) UVI levels, larger deviations were found for individual estimates. The average agreement between the UVI from the UVIOS2 and QASUME was better than 1 % for all the different sets of inputs that were used for the study. The range of the variability was of the order of 40 % for instantaneous measurements (15 min), mainly due to the model’s inability to capture the instantaneous effects of cloudiness, especially under broken cloud conditions. Under clear-sky conditions the model was found to perform much better, with the differences between the model estimates and the QASUME measurements being smaller than 12 % for 95 % of the studied cases. Even at the pristine environment of Davos, single scattering albedo (SSA) was found to contribute significantly to the modelling uncertainties under cloudless conditions. For relatively small Aerosol Optical Depth (AOD), of the order of 0.2 – 0.4, the role of the SSA was found to be comparable to the role of AOD in the modelling of the UVI. Radiometers that were not properly maintained and/or calibrated were found to provide UVI measurements with uncertainty that was comparable to the uncertainty of the UVIOS2 estimates, which highlights the significance of systematic maintenance and calibration of the UV radiometers.

The third campaign for the calibration and intercomparison of solar UV radiometers (UVC III) took place at Davos, Switzerland in June–August 2022. More than 70 radiometers participated in the campaign and measured side-by-side with the portable reference spectroradiometer QASUME. By using inputs from various sources, the UVIOS2 system was used to estimate the UV index (UVI) for the site of the campaign. The UVIOS2 system is a flexible UVI modelling tool that can be exploited for different applications depending on the inputs. Thus, different combinations of satellite, reanalysis, and/or ground-based inputs were used to test the UVIOS2 performance when it is used as a tool for UVI nowcasting or for climatological studies. While UVIOS2 provided quite accurate estimates of the average (for the period of the campaign) UVI levels, larger deviations were found for individual estimates. The average agreement between the UVI from the UVIOS2 and QASUME was better than 1 % for all the different sets of inputs that were used for the study. The range of the variability was of the order of 40 % for instantaneous measurements (15 min), mainly due to the model’s inability to capture the instantaneous effects of cloudiness, especially under broken cloud conditions. Under clear-sky conditions the model was found to perform much better, with the differences between the model estimates and the QASUME measurements being smaller than 12 % for 95 % of the studied cases. Even at the pristine environment of Davos, single scattering albedo (SSA) was found to contribute significantly to the modelling uncertainties under cloudless conditions. For relatively small Aerosol Optical Depth (AOD), of the order of 0.2 – 0.4, the role of the SSA was found to be comparable to the role of AOD in the modelling of the UVI. Radiometers that were not properly maintained and/or calibrated were found to provide UVI measurements with uncertainty that was comparable to the uncertainty of the UVIOS2 estimates, which highlights the significance of systematic maintenance and calibration of the UV radiometers.

The third campaign for the calibration and intercomparison of solar UV radiometers (UVC III) took place at Davos, Switzerland in June–August 2022. More than 70 radiometers participated in the campaign and measured side-by-side with the portable reference spectroradiometer QASUME. By using inputs from various sources, the UVIOS2 system was used to estimate the UV index (UVI) for the site of the campaign. The UVIOS2 system is a flexible UVI modelling tool that can be exploited for different applications depending on the inputs. Thus, different combinations of satellite, reanalysis, and/or ground-based inputs were used to test the UVIOS2 performance when it is used as a tool for UVI nowcasting or for climatological studies. While UVIOS2 provided quite accurate estimates of the average (for the period of the campaign) UVI levels, larger deviations were found for individual estimates. The average agreement between the UVI from the UVIOS2 and QASUME was better than 1 % for all the different sets of inputs that were used for the study. The range of the variability was of the order of 40 % for instantaneous measurements (15 min), mainly due to the model’s inability to capture the instantaneous effects of cloudiness, especially under broken cloud conditions. Under clear-sky conditions the model was found to perform much better, with the differences between the model estimates and the QASUME measurements being smaller than 12 % for 95 % of the studied cases. Even at the pristine environment of Davos, single scattering albedo (SSA) was found to contribute significantly to the modelling uncertainties under cloudless conditions. For relatively small Aerosol Optical Depth (AOD), of the order of 0.2 – 0.4, the role of the SSA was found to be comparable to the role of AOD in the modelling of the UVI. Radiometers that were not properly maintained and/or calibrated were found to provide UVI measurements with uncertainty that was comparable to the uncertainty of the UVIOS2 estimates, which highlights the significance of systematic maintenance and calibration of the UV radiometers.

This work aims at investigating the effect of NO₂ absorption on aerosol-optical-depth (AOD) measurements and Ångström exponent (AE) retrievals of sun photometers by the synergistic use of accurate NO₂ characterization for optical-depth estimation from co-located ground-based measurements. The analysis was performed for ∼ 7 years (2017–2023) at several sites worldwide for the AOD measurements and AE retrievals by Aerosol Robotic Network (AERONET) sun photometers which use OMI (Ozone Monitoring Instrument) climatology for NO₂ representation. The differences in AOD and AE retrievals by NO₂ absorption are accounted for using high-frequency columnar NO₂ measurements by a co-located Pandora spectroradiometer belonging to the Pandonia Global Network (PGN). NO₂ absorption affects the AOD measurements in UV-Vis (visible) range, and we found that the AOD bias is the most affected at 380 nm by NO₂ differences, followed by 440, 340, and 500 nm, respectively. AERONET AOD was found to be overestimated in half of the cases, while also underestimated in other cases as an impact of the NO₂ difference from “real” (PGN NO₂) values. Overestimations or underestimations are relatively low. About one-third of these stations showed a mean difference in NO₂ and AOD (at 380 and 440 nm) above 0.5 × 10⁻⁴ mol m⁻² and 0.002, respectively, which can be considered a systematic contribution to the uncertainties in the AOD measurements that are reported to be of the order of 0.01. However, under extreme NO₂ loading scenarios (i.e. 10 % highest differences) at highly urbanized/industrialized locations, even higher AOD differences were observed that were at the limit of or higher than the reported 0.01 uncertainty in the AOD measurement. PGN NO₂-based sensitivity analysis of AOD difference suggested that for PGN NO₂ varying between 2 × 10⁻⁴ and 8 × 10⁻⁴ mol m⁻², the median AOD differences were found to rise above 0.01 (even above 0.02) with the increase in NO₂ threshold (i.e. the lower limit from 2 × 10⁻⁴ to 8 × 10⁻⁴ mol m⁻²). The AOD-derivative product, AE, was also affected by the NO₂ correction (discrepancies between the AERONET OMI climatological representation of NO₂ values and the real PGN NO₂ measurements) on the spectral AOD. Normalized frequency distribution of AE (at 440–870 and 340–440 nm wavelength pair) was found to be narrower for a broader AOD distribution for some stations, and vice versa for other stations, and a higher relative error at the shorter wavelength (among the wavelength pairs used for AE estimation) led to a shift in the peak of the AE difference distribution towards a higher positive value, while a higher relative error at a lower wavelength shifted the AE difference distribution to a negative value for the AOD overestimation case, and vice versa for the AOD underestimation case. For rural locations, the mean NO₂ differences were found to be mostly below 0.50 × 10⁻⁴ mol m⁻², with the corresponding AOD differences being below 0.002, and in extreme NO₂ loading scenarios, it went above this value and reached above 1.00 × 10⁻⁴ mol m⁻² for some stations, leading to higher AOD differences but below 0.005. Finally, AOD and AE trends were calculated based on the original AERONET AOD (based on AERONET OMI climatological NO₂), and its comparison with the mean differences in the AERONET and PGN NO₂-corrected AOD was indicative of how NO₂ correction could potentially affect realistic AOD trends.

Sun photometers retrieve Aerosol Optical Depth (AOD) from direct solar irradiance observations when sun disk is not obscured by clouds. Therefore, identifying cloud-contaminated measurements is crucial for achieving high-quality AOD retrieval. Cloud flagging algorithms are instrumental in this process, as failure to accurately flag clouds can have significant impact on AOD retrieval and related applications e.g., air quality monitoring, numerical weather prediction, atmospheric transport models and data synergism.This work aims at synergistically leverage ground-based instruments to analyze the performance of existing stand-alone algorithms in different scenarios, including periods of high-variability due to clouds, and extreme weather events like wildfires, dust storms, etc. To this direction, we used co-located Pandonia Global Network Pandora spectroradiometer and Global Atmosphere Watch Precision filter radiometer (PFR) network instrument and analyzed the performance of existing algorithms over the course of 2023 at Izana station.PFR and Pandora measurements were synchronized with a time window of 1 min. For this analysis, PFR flags comprise two scenarios for clear-sun and flagged data, while Pandora has nine double-digit quality flags (QF) representing a combination of uncertainty (high: 0, medium: 1, low: 2) and data quality assurance (assured: 0, not assured:1, unusable data: 2). The analysis revealed good agreement between Pandora QF10 and PFR clear-sun flag (96.45%) followed by QF11 and QF12 (2.29% and 1.26%, respectively). Conversely, for PFR flagged data, corresponding percentages for Pandora QF10, QF11 and QF12 were 57.83%, 12.58% and 29.6%, respectively. Daily variation of Pandora QFs for 1-year indicated 34 days with Saharan dust episodes (concluded from HYSPLIT 24-h backward trajectories at levels from 500 to 6000 m above ground level originating from the Saharan region) on which for PFR clear sun flag, QF10 flag was more than 90% of daily number of comparison points indicating that dust events did not deteriorate much the flagging agreement between the two instruments. On the contrary, there were 20 dust free days with QF10 below 90% (most days had number of daily comparison points below 40, indicating high variability due to clouds). PFR clear-sun flag based and Pandora QF10 based AOD distribution showed respective geometric mean ranging from 0.02 to 0.04 and respective standard deviation ranging from 3.24 to 2.35 at 862 nm to 367 nm, respectively. This attempt of synergistic use of different measuring instruments can be useful for enhancing cloud flagging algorithms, thereby contributing to higher quality retrieval product. AcknowledgementThis research has been supported by European Space Agency (ESA) in the frame of Instrument Data quality Evaluation and Assessment Service – Quality Assurance for Earth Observation (IDEAS-QA4EO) project, ACTRIS Switzerland project funded by Swiss State Secretariat for Education Research and Innovation and COST Action HARMONIA CA21119, supported by COST (European Cooperation in Science and Technology).

Aerosols play a dominant role in the solar radiation field and Earth's energy budget, inducing considerable climatic forcing (IPCC, 2022). Dust particles and water vapor (WV) can change the atmospheric thermodynamic stability through radiative heating and/or cooling (Gutleben et al, 2019). Although the quantification of these aspects is crucial, the difficulty in defining the aerosols microphysical and optical properties along with their high spatial and temporal variability makes this quantification challenging. Despite the considerable progress in recent years regarding this topic, sophisticated atmospheric field experiments that provide highly accurate information are essential, not only to enrich knowledge, but for the validation and the improvement of ongoing and future satellite-based products.The current study provides valuable information on dust and WV radiative effects through a unique dataset of synergistic high-quality measurements during the ASKOS ESA campaign in Cabo Verde. Specifically, the study utilizes sophisticated ground-based remote sensing, airborne (UAV) in-situ measurements, along with surface solar irradiance measurements and airborne (UAV and radiosonde) profiling of temperature and WV. The under-study period (summer of 2022) coincides with the annual peak of dust transport in the Atlantic.To derive realistic optical properties of the dust particles along with their vertical distribution in the atmosphere, we use the airborne in-situ observations of particle microphysical properties (size, shape and mineralogical composition). The calculated optical properties are evaluated using multi-wavelength ground-based lidar measurements. Then, radiative transfer (RT) simulations are performed under clear and cloudy sky conditions employing the libRadtran RT package (Mayer & Kylling, 2005; Emde et al., 2016). The RT simulations of shortwave radiation at the bottom of the atmosphere are compared with surface broadband radiation measurements. Finally, the heating rate (HR) calculations are evaluated against changes in the temperature profile of the atmosphere. Acknowledgements: This research was financially supported by the PANGEA4CalVal project (Grant Agreement 101079201) funded by the European Union . DK, ΑΤ, ΚP, PR and SK would like to acknowledge COST Action HARMONIA (International network for harmonization of atmospheric aerosol retrievals from ground-based photometers), CA2119, supported by COST (European Cooperation in Science and Technology).References Emde, C., Buras-Schnell, R., Kylling, A., Mayer, B., Gasteiger, J., Hamann, U., Kylling, J., Richter, B., Pause, C., Dowling, T., Bugliaro. L. (2016). The libRadtran software package for radiative transfer calculations (version 2.0.1), Geoscientific Model Development, 9(5), 1647–1672, https://doi.org/10.5194/gmd-9-1647-2016.Gutleben, M., Groß, S., Wirth, M., Emde, C., and Mayer, B. (2019). Impacts of Water Vapor on Saharan Air Layer Radiative Heating. Geophysical Research Letters. 46, https://doi.org/10.1029/2019GL085344.Intergovernmental Panel on Climate Change (IPCC) (2022), Land–climate interactions. In: Climate Change and Land: IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems. Cambridge University Press,131-248.Mayer, B., Kylling, A. (2005), Technical note: The libRadtran software package for radiative transfer calculations - description and examples of use. Atmos. Chem. Phys., 5(7), 1855–1877, https://doi.org/10.5194/acp-5-1855-2005.