Satellite data are increasingly used to provide observation-based estimates of the effects of aerosols on climate. The Aerosol-cci project, part of the European Space Agency's Climate Change Initiative (CCI), was designed to provide essential climate variables for aerosols from satellite data. Eight algorithms, developed for the retrieval of aerosol properties using data from AATSR (4), MERIS (3) and POLDER, were evaluated to determine their suitability for climate studies. The primary result from each of these algorithms is the aerosol optical depth (AOD) at several wavelengths, together with the Ångström exponent (AE) which describes the spectral variation of the AOD for a given wavelength pair. Other aerosol parameters which are possibly retrieved from satellite observations are not considered in this paper. The AOD and AE (AE only for Level 2) were evaluated against independent collocated observations from the ground-based AERONET sun photometer network and against "reference" satellite data provided by MODIS and MISR. Tools used for the evaluation were developed for daily products as produced by the retrieval with a spatial resolution of 10×10km2 (Level 2) and daily or monthly aggregates (Level 3). These tools include statistics for L2 and L3 products compared with AERONET, as well as scoring based on spatial and temporal correlations. In this paper we describe their use in a round robin (RR) evaluation of four months of data, one month for each season in 2008. The amount of data was restricted to only four months because of the large effort made to improve the algorithms, and to evaluate the improvement and current status, before larger data sets will be processed. Evaluation criteria are discussed. Results presented show the current status of the European aerosol algorithms in comparison to both AERONET and MODIS and MISR data. The comparison leads to a preliminary conclusion that the scores are similar, including those for the references, but the coverage of AATSR needs to be enhanced and further improvements are possible for most algorithms. None of the algorithms, including the references, outperforms all others everywhere. AATSR data can be used for the retrieval of AOD and AE over land and ocean. PARASOL and one of the MERIS algorithms have been evaluated over ocean only and both algorithms provide good results. © 2013 Elsevier Inc

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Abstract. Understanding long-term variations in aerosol loading is essential for evaluating the health and climate effects of airborne particulates as well as the effectiveness of pollution control policies. The expected satellite lifetime is about 10 to 15 years. Therefore, to study the variations of atmospheric constituents over longer periods information from different satellites must be utilized. Here we introduce a method to construct a combined annual and seasonal long time series of AOD at 550 nm using the Along-Track Scanning Radiometers (ATSR: ATSR-2 and AATSR combined) and the MODerate resolution Imaging Spectroradiometer on Terra (MODIS/Terra), which together cover the 1995–2017 period. The long-term (1995–2017) combined AOD time series are presented for all of mainland China, for southeastern (SE) China and for 10 selected regions in China. Linear regression was applied to the combined AOD time series constructed for individual L3 (1∘ × 1∘) pixels to estimate the AOD tendencies for two periods: 1995–2006 (P1) and 2011–2017 (P2), with respect to the changes in the emission reduction policies in China. During P1, the annually averaged AOD increased by 0.006 (or 2 % of the AOD averaged over the corresponding period) per year across all of mainland China, reflecting increasing emissions due to rapid economic development. In SE China, the annual AOD positive tendency in 1995–2006 was 0.014 (3 %) per year, reaching maxima (0.020, or 4 %, per year) in Shanghai and the Pearl River Delta regions. After 2011, during P2, AOD tendencies reversed across most of China with the annually averaged AOD decreasing by −0.015 (−6 %) per year in response to the effective reduction of the anthropogenic emissions of primary aerosols, SO2 and NOx. The strongest AOD decreases were observed in the Chengdu (−0.045, or −8 %, per year) and Zhengzhou (−0.046, or −9 %, per year) areas, while over the North China Plain and coastal areas the AOD decrease was lower than −0.03 (approximately −6 %) per year. In the less populated areas the AOD decrease was small. The AOD tendency varied by both season and region. The increase in the annually averaged AOD during P1 was mainly due to an increase in summer and autumn in SE China (0.020, or 4 %, and 0.016, or 4 %, per year, respectively), while during winter and spring the AOD actually decreased over most of China. The AOD negative tendencies during the 2011–2017 period were larger in summer than in other seasons over the whole of China (ca. −0.021, or −7 %, per year) and over SE China (ca. −0.048, or −9 %, per year). The long-term AOD variations presented here show a gradual decrease in the AOD after 2011 with an average reduction of 30 %–50 % between 2011 and 2017. The effect is more visible in the highly populated and industrialized regions in SE China, as expected.

Abstract. Cloud misclassification is a serious problem in the retrieval of aerosol optical depth (AOD), which might considerably bias the AOD results. On the one hand, residual cloud contamination leads to AOD overestimation, whereas the removal of high-AOD pixels (due to their misclassification as clouds) leads to underestimation. To remove cloudcontaminated areas in AOD retrieved from reflectances measured with the (Advanced) Along Track Scanning Radiometers (ATSR-2 and AATSR), using the ATSR dual-view algorithm (ADV) over land or the ATSR single-view algorithm (ASV) over ocean, a cloud post-processing (CPP) scheme has been developed at the Finnish Meteorological Institute (FMI) as described in Kolmonen et al. (2016). The application of this scheme results in the removal of cloudcontaminated areas, providing spatially smoother AOD maps and favourable comparison with AOD obtained from the ground-based reference measurements from the AERONET sun photometer network. However, closer inspection shows that the CPP also removes areas with elevated AOD not due to cloud contamination, as shown in this paper. We present an improved CPP scheme which better discriminates between cloud-free and cloud-contaminated areas. The CPP thresholds have been further evaluated and adjusted according to the findings. The thresholds for the detection of high-AOD regions (> 60 % of the retrieved pixels should be high-AOD (> 0.6) pixels), and cloud contamination criteria for low-AOD regions have been accepted as the default for AOD global post-processing in the improved CPP. Retaining elevated AOD while effectively removing cloud-contaminated pixels affects the resulting global and regional mean AOD values as well as coverage. Effects of the CPP scheme on The aggregated AOD over ocean and globally (land and ocean together) is 0.164 with the improved CPP scheme (compared to 0.152 and 0.150 with the existing scheme, for ocean and globally respectively). Effects of the improved CPP scheme on the 10-year time series are illustrated and seasonal and temporal changes are discussed. The improved CPP method introduced here is applicable to other aerosol retrieval algorithms. However, the thresholds for detecting the high-AOD regions, which were developed for AATSR, might have to be adjusted to the actual features of the instruments.

Abstract. Retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the Aqua satellite, 12 years (2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014) of aerosol and cloud properties were used to statistically quantify aerosol-cloud interaction (ACI) over the Baltic Sea region, including the relatively clean Fennoscandia and the more polluted central-eastern Europe. These areas allowed us to study the effects of different aerosol types and concentrations on macro-and microphysical properties of clouds: cloud effective radius (CER), cloud fraction (CF), cloud optical thickness (COT), cloud liquid water path (LWP) and cloud-top height (CTH). Aerosol properties used are aerosol optical depth (AOD), Ångström exponent (AE) and aerosol index (AI). The study was limited to low-level water clouds in the summer.The vertical distributions of the relationships between cloud properties and aerosols show an effect of aerosols on low-level water clouds. CF, COT, LWP and CTH tend to increase with aerosol loading, indicating changes in the cloud structure, while the effective radius of cloud droplets decreases. The ACI is larger at relatively low cloud-top levels, between 900 and 700 hPa. Most of the studied cloud variables were unaffected by the lower-tropospheric stability (LTS), except for the cloud fraction.The spatial distribution of aerosol and cloud parameters and ACI, here defined as the change in CER as a function of aerosol concentration for a fixed LWP, shows positive and statistically significant ACI over the Baltic Sea and Fennoscandia, with the former having the largest values. Small negative ACI values are observed in central-eastern Europe, suggesting that large aerosol concentrations saturate the ACI.