Abstract. In order to assess the evolution of aerosol parameters affecting climate change, a long-term trend analysis of aerosol optical properties was performed on time series from 52 stations situated across five continents. The time series of measured scattering, backscattering and absorption coefficients as well as the derived single scattering albedo, backscattering fraction, scattering and absorption Ångström exponents covered at least 10 years and up to 40 years for some stations. The non-parametric seasonal Mann–Kendall (MK) statistical test associated with several pre-whitening methods and with Sen's slope was used as the main trend analysis method. Comparisons with general least mean square associated with autoregressive bootstrap (GLS/ARB) and with standard least mean square analysis (LMS) enabled confirmation of the detected MK statistically significant trends and the assessment of advantages and limitations of each method. Currently, scattering and backscattering coefficient trends are mostly decreasing in Europe and North America and are not statistically significant in Asia, while polar stations exhibit a mix of increasing and decreasing trends. A few increasing trends are also found at some stations in North America and Australia. Absorption coefficient time series also exhibit primarily decreasing trends. For single scattering albedo, 52 % of the sites exhibit statistically significant positive trends, mostly in Asia, eastern/northern Europe and the Arctic, 22 % of sites exhibit statistically significant negative trends, mostly in central Europe and central North America, while the remaining 26 % of sites have trends which are not statistically significant. In addition to evaluating trends for the overall time series, the evolution of the trends in sequential 10-year segments was also analyzed. For scattering and backscattering, statistically significant increasing 10-year trends are primarily found for earlier periods (10-year trends ending in 2010–2015) for polar stations and Mauna Loa. For most of the stations, the present-day statistically significant decreasing 10-year trends of the single scattering albedo were preceded by not statistically significant and statistically significant increasing 10-year trends. The effect of air pollution abatement policies in continental North America is very obvious in the 10-year trends of the scattering coefficient – there is a shift to statistically significant negative trends in 2009–2012 for all stations in the eastern and central USA. This long-term trend analysis of aerosol radiative properties with a broad spatial coverage provides insight into potential aerosol effects on climate changes.

Abstract. A continuous, 36-year measurement composite of atmospheric carbon dioxide (CO2) at three measurement locations on Mount Zugspitze, Germany, was studied. For a comprehensive site characterization of Mount Zugspitze, analyses of CO2 weekly periodicity and diurnal cycle were performed to provide evidence for local sources and sinks, showing clear weekday to weekend differences, with dominantly higher CO2 levels during the daytime on weekdays. A case study of atmospheric trace gases (CO and NO) and the passenger numbers to the summit indicate that CO2 sources close by did not result from tourist activities but instead obviously from anthropogenic pollution in the near vicinity. Such analysis of local effects is an indispensable requirement for selecting representative data at orographic complex measurement sites. The CO2 trend and seasonality were then analyzed by background data selection and decomposition of the long-term time series into trend and seasonal components. The mean CO2 annual growth rate over the 36-year period at Zugspitze is 1.8±0.4 ppm yr−1, which is in good agreement with Mauna Loa station and global means. The peak-to-trough amplitude of the mean CO2 seasonal cycle is 12.4±0.6 ppm at Mount Zugspitze (after data selection: 10.5±0.5 ppm), which is much lower than at nearby measurement sites at Mount Wank (15.9±1.5 ppm) and Schauinsland (15.9±1.0 ppm), but following a similar seasonal pattern.

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Abstract. Critical data selection is essential for determining representative baseline levels of atmospheric trace gases even at remote measurement sites. Different data selection techniques have been used around the world, which could potentially lead to reduced compatibility when comparing data from different stations. This paper presents a novel statistical data selection method named adaptive diurnal minimum variation selection (ADVS) based on CO2 diurnal patterns typically occurring at elevated mountain stations. Its capability and applicability were studied on records of atmospheric CO2 observations at six Global Atmosphere Watch stations in Europe, namely, Zugspitze-Schneefernerhaus (Germany), Sonnblick (Austria), Jungfraujoch (Switzerland), Izaña (Spain), Schauinsland (Germany), and Hohenpeissenberg (Germany). Three other frequently applied statistical data selection methods were included for comparison. Among the studied methods, our ADVS method resulted in a lower fraction of data selected as a baseline with lower maxima during winter and higher minima during summer in the selected data. The measured time series were analyzed for long-term trends and seasonality by a seasonal-trend decomposition technique. In contrast to unselected data, mean annual growth rates of all selected datasets were not significantly different among the sites, except for the data recorded at Schauinsland. However, clear differences were found in the annual amplitudes as well as the seasonal time structure. Based on a pairwise analysis of correlations between stations on the seasonal-trend decomposed components by statistical data selection, we conclude that the baseline identified by the ADVS method is a better representation of lower free tropospheric (LFT) conditions than baselines identified by the other methods.

Abstract. Aerosol particles are essential constituents of the Earth's atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence times, resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in situ near-surface segment of the atmospheric observation system. This paper will provide the widest effort so far to document variability of climate-relevant in situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High-quality data from almost 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single-scattering albedo, and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information, including data provision procedures, quality control and analysis, data policy, and usage of the ground-based aerosol measurement network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.