This paper is an overview of the progress in sky radiometer technology and the development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from sky radiometer observations of aerosol, cloud, water vapor, and ozone. A formula was proposed for estimating the accuracy of the sky radiometer calibration constant F₀ using the improved Langley (IL) method, which was found to be a good approximation to observed monthly mean uncertainty in F₀, around 0.5 % to 2.4 % at the Tokyo and Rome sites and smaller values of around 0.3 % to 0.5 % at the mountain sites at Mt. Saraswati and Davos. A new cross IL (XIL) method was also developed to correct an underestimation by the IL method in cases with large aerosol retrieval errors. The root-mean-square difference (RMSD) in aerosol optical thickness (AOT) comparisons with other networks took values of less than 0.02 for λ≥500 nm and a larger value of about 0.03 for shorter wavelengths in city areas and smaller values of less than 0.01 in mountain comparisons. Accuracies of single-scattering albedo (SSA) and size distribution retrievals are affected by the propagation of errors in measurement, calibrations for direct solar and diffuse sky radiation, ground albedo, cloud screening, and the version of the analysis software called the Skyrad pack. SSA values from SKYNET were up to 0.07 larger than those from AERONET, and the major error sources were identified as an underestimation of solid viewing angle (SVA) and cloud contamination. Correction of these known error factors reduced the SSA difference to less than 0.03. Retrievals of other atmospheric constituents by the sky radiometer were also reviewed. Retrieval accuracies were found to be about 0.2 cm for precipitable water vapor amount and 13 DU (Dobson Unit) for column ozone amount. Retrieved cloud optical properties still showed large deviations from validation data, suggesting a need to study the causes of the differences. It is important that these recent studies on improvements presented in the present paper are introduced into the existing operational systems and future systems of the International SKYNET Data Center.

In order to reduce uncertainty in the estimation of Direct Aerosol Radiative Forcing (DARF), it is important to improve the estimation of the single scattering albedo (SSA). In this study, we propose a new data processing method to improve SSA retrievals for the SKYNET sky radiometer network, which is one of the growing number of networks of sun-sky photometers, such as NASA AERONET and others. There are several reports that SSA values from SKYNET have a bias compared to those from AERONET, which is regarded to be the most accurate due to its rigorous calibration routines and data quality and cloud screening algorithms. We investigated possible causes of errors in SSA that might explain the known biases through sensitivity experiments using a numerical model, and also using real data at the SKYNET sites at Pune (18.616° N/73.800° E) in India and Beijing (39.586° N/116.229° E) in China. Sensitivity experiments showed that an uncertainty of the order of ±0.03 in the SSA value can be caused by a possible error in the ground surface albedo or solid view angle assumed for each observation site. Another candidate for possible error in the SSA was found in cirrus contamination generated by imperfect cloud screening in the SKYNET data processing. Therefore, we developed a new data quality control method to get rid of low quality or cloud contamination data, and we applied this method to the real observation data at the Pune site in SKYNET. After applying this method to the observation data, we were able to screen out a large amount of cirrus-contaminated data and to reduce the deviation in the SSA value from that of AERONET. We then estimated DARF using data screened by our new method. The result showed that the method significantly reduced the difference of 5 W m⁻² that existed between the SKYNET and AERONET values of DARF before screening. The present study also suggests the necessity of preparing suitable a priori information on the distribution of coarse particles ranging in radius between 10 μm and 30 μm for the analysis of heavily dust-laden atmospheric cases.

Mountainous regions are often considered pristine environments; however they can be affected by pollutants emitted in more populated and industrialised areas, transported by regional winds. Based on experimental evidence, further supported by modelling tools, here we demonstrate and quantify the impact of air masses transported from the Po Valley, a European atmospheric pollution hotspot, to the northwestern Alps. This is achieved through a detailed investigation of the phenomenology of near-range (a few hundred kilometres), trans-regional transport, exploiting synergies of multi-sensor observations mainly focussed on particulate matter. The explored dataset includes vertically resolved data from atmospheric profiling techniques (automated lidar ceilometers, ALCs), vertically integrated aerosol properties from ground (sun photometer) and space, and in situ measurements (PM₁₀ and PM_2.5, relevant chemical analyses, and aerosol size distribution). During the frequent advection episodes from the Po basin, all the physical quantities observed by the instrumental setup are found to significantly increase: the scattering ratio from ALC reaches values >30, aerosol optical depth (AOD) triples, surface PM₁₀ reaches concentrations >100 µg m⁻³ even in rural areas, and contributions to PM₁₀ by secondary inorganic compounds such as nitrate, ammonium, and sulfate increase up to 28 %, 8 %, and 17 %, respectively. Results also indicate that the aerosol advected from the Po Valley is hygroscopic, smaller in size, and less light-absorbing compared to the aerosol type locally emitted in the northwestern Italian Alps. In this work, the phenomenon is exemplified through detailed analysis and discussion of three case studies, selected for their clarity and relevance within the wider dataset, the latter being fully exploited in a companion paper quantifying the impact of this phenomenology over the long-term (Diémoz et al., 2019). For the three case studies investigated, a high-resolution numerical weather prediction model (COSMO) and a Lagrangian tool (LAGRANTO) are employed to understand the meteorological mechanisms favouring transport and to demonstrate the Po Valley origin of the air masses. In addition, a chemical transport model (FARM) is used to further support the observations and to partition the contributions of local and non-local sources. Results show that the simulations are important to the understanding of the phenomenon under investigation. However, in quantitative terms, modelled PM₁₀ concentrations are 4–5 times lower than the ones retrieved from the ALC and maxima are anticipated in time by 6–7 h. Underestimated concentrations are likely mainly due to deficiencies in the emission inventory and to water uptake of the advected particles not fully reproduced by FARM, while timing mismatches are likely an effect of suboptimal simulation of up-valley and down-valley winds by COSMO. The advected aerosol is shown to remarkably degrade the air quality of the Alpine region, with potential negative effects on human health, climate, and ecosystems, as well as on the touristic development of the investigated area. The findings of the present study could also help design mitigation strategies at the trans-regional scale in the Po basin and suggest an observation-based approach to evaluate the outcome of their implementation.

A new procedure is presented for determining in situ the solar calibration constant, i.e., the Sun-sky radiometer counts for a direct normal solar flux extrapolated to the top of the atmosphere. The method makes use of a modified version of the Langley plot based on the use of an inversion code of column-integrated aerosol size distribution, and it is ordinarily applied to calibrate Prede Sun-sky radiometers. To analyze how such an in situ method can work accurately, the technique has been applied to a five-month dataset obtained from measurements taken in Rome, Italy, by a Prede Sun-sky radiometer from 22 April to 5 November 2001. The precision of the in situ method has been estimated to within 1–2.5%, depending on the wavelength.

The in situ procedure for determining the solar calibration constants, originally developed for the PREDE Sun–sky radiometers and based on a modified version of the Langley plot, was applied to a CIMEL instrument located in Valencia, Spain, not integrated into AERONET. Taking into account the different mechanical and electronic characteristics of the two radiometers, the method was adapted to the characteristics of the CIMEL instrument. The iterative procedure for the determination of the solar calibration constants was applied to a 3-year data set. The results were compared with the two sets of experimental calibration constants determined during this period using the standard Langley plot method. The agreement was found to be consistent with the experimental errors, and the method can definitely also be used to determine the solar calibration constant for the CIMEL instrument, improving its calibration. The method can be used provided the radiometer is previously calibrated for diffuse radiance using a standard lamp.

This study presents the results of the Fourth Filter Radiometer Comparison that was held in Davos, Switzerland, between 28 September and 16 October 2015. Thirty filter radiometers and spectroradiometers from 12 countries participated including reference instruments from global aerosol networks. The absolute differences of all instruments compared to the reference have been based on the World Meteorological Organization (WMO) criterion defined as follows: 95% of the measured data has to be within 0.005 ± 0.001∕m (where m is the air mass). At least 24 out of 29 instruments achieved this goal at both 500 and 865 nm, while 12 out of 17 and 13 out of 21 achieved this at 368 and 412 nm, respectively. While searching for sources of differences among different instruments, it was found that all individual differences linked to Rayleigh, NO₂, ozone, water vapor calculations and related optical depths and air mass calculations were smaller than 0.01 in aerosol optical depth (AOD) at 500 and 865 nm. Different cloud-detecting algorithms used have been compared. Ångström exponent calculations showed relatively large differences among different instruments, partly because of the high calculation uncertainty of this parameter in low AOD conditions. The overall low deviations of these AOD results and the high accuracy of reference aerosol network instruments demonstrated a promising framework to achieve homogeneity, compatibility and harmonization among the different spectral AOD networks in the near future.