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The central Arctic cryosphere is influenced by the Arctic amplification (AA) and is warming faster than the lower latitudes. AA affects the formation, loss, and transport of aerosols. Efforts to assess the underlying processes determining aerosol variability are currently limited due to the lack of ground-based and space-borne aerosol observations with high spatial coverage in this region. This study addresses the observational gap by making use of total aerosol optical depth (AOD) datasets retrieved by the AEROSNOW algorithm over the vast cryospheric region of the central Arctic during Arctic spring and summer. GEOS-Chem (GC) simulations combined with AEROSNOW-retrieved data are used to investigate the processes controlling aerosol loading and distribution at different temporal and spatial scales. For the first time, an integrated study of AOD over the Arctic cryosphere during sunlight conditions was possible with the AEROSNOW retrieval and GC simulations. The results show that the spatial patterns observed by AEROSNOW differ from those simulated by GC. During spring, which is characterized by long-range transport of anthropogenic aerosols in the Arctic, GC underestimates the AOD in the vicinity of Alaska in comparison with AEROSNOW retrieval. At the same time, it overestimates the AOD along the Bering Strait, northern Europe, and the Siberian central Arctic sea-ice regions, with differences of - 12.3 % and 21.7 %, respectively. By contrast, GC consistently underestimates AOD compared with AEROSNOW in summer, when transport from lower latitudes is insignificant and local natural processes are the dominant source of aerosol, especially north of 70° N. This underestimation is particularly pronounced over the central Arctic sea-ice region, where it is - 10.6 %. Conversely, GC tends to overestimate AOD along the Siberian and Greenland marginal sea-ice zones by 19.5 % but underestimates AOD along the Canadian Archipelago by - 9.3 %. The differences in summer AOD between AEROSNOW data products and GC-simulated AOD highlight the need to integrate improved knowledge of the summer aerosol process into existing models in order to constrain its effects on cloud condensation nuclei, on ice nucleating particles, and on the radiation budget over the central Arctic sea ice during the developing AA period. [ABSTRACT FROM AUTHOR]

The Sentinel-5 Precursor (S5P) mission was launched on October 2017 and has since provided data with high spatio-temporal resolution using its remote sensing instrument, the TROPOspheric Monitoring Instrument (TROPOMI). The latter is a nadir viewing passive grating imaging spectrometer. The mathematical inversion of the TROPOMI data yields retrievals of different trace gas and aerosol data products. The column-averaged dry-air mole fraction of methane (XCH4) is the product of interest to this study. The daily global coverage of the atmospheric methane mole fraction data enables the analysis of the methane distribution and variation on large scales and also to estimate surface emissions. The spatio-temporal high-resolution satellite data are potentially particularly valuable in remote regions, such as the Arctic, where few ground stations and in situ measurements are available. In addition to the operational Copernicus S5P total-column-averaged dry-air mole fraction methane data product developed by SRON, the scientific TROPOMI/WFMD algorithm data product v1.5 (WFMD product) was generated at the Institute of Environmental Physics at the University of Bremen. In this study we focus on the assessment of both S5P XCH4 data products over Greenland and find that spatial maps of both products show distinct features along the coastlines. Anomalies up to and exceeding 100 ppb are observed and stand out in comparison to the otherwise smooth changes in the methane distribution. These features are more pronounced for the operational product compared to the WFMD product. The spatial patterns correlate with the difference between the GMTED2010 digital elevation model (DEM) used in the retrievals and a more recent topography dataset, indicating that inaccuracies in the assumed surface elevation are the origin of the observed features. These correlations are stronger for the WFMD product. In order to evaluate the impact of the topography dataset on the retrieval we reprocess the WFMD product with updated elevation data. We find that a significant reduction of the localized features when GMTED2010 is replaced by recent topography data over Greenland based on ICESat-2 data. This study shows the importance of the chosen topography data for retrieved dry-air mole fractions. The use of a DEM that is as accurate and as up to date as possible is advised for all S5P data products as well as for future missions which rely on a DEM as input data. A modification based on this study is planned to be introduced in the next version of the WFMD data product. [ABSTRACT FROM AUTHOR]

The Sentinel-5 Precursor (S5P) mission was launched on October 2017 and has since provided data with high spatiotemporal resolution using its remote sensing instrument, the TROPOspheric Monitoring Instrument (TROPOMI). The latter is a nadir viewing passive grating imaging spectrometer. The mathematical inversion of the TROPOMI data yields retrievals of different trace gas and aerosol data products. The column-averaged dry air mole fraction of methane (XCH4) is the product of interest to this 5 study. The daily global coverage of the atmospheric methane mole fraction data enables the analysis of the methane distribution and variation on large scales and also to estimate surface emissions. The spatio-temporal high-resolution satellite data are potentially particularly valuable in remote regions, such as the Arctic, where few ground stations and insitu measurements are available. In addition to the operational Copernicus S5P total-column averaged dry air mole fraction methane data product developed by SRON, the scientific TROPOMI/WFMD algorithm data product v1.5 (WFMD product) was generated at the Institute of Environmental Physics at the University of Bremen. In this study we focus on the assessment of both S5P XCH4 data products over Greenland and find that spatial maps of both products show distinct features along the coast lines. Anomalies up to and exceeding 100 ppb are observed and stand out in comparison to the otherwise smooth changes in the methane distribution. These features are more pronounced for the operational product compared to the WFMD product. The spatial patterns correlate with the difference of the GMTED2010 digital elevation model (DEM) used in the retrievals to a more recent topography data set indicating that inaccuracies in the assumed surface elevation are the origin of the observed features. These correlations are stronger for the WFMD product. In order to evaluate the impact of the topography dataset on the retrieval we reprocess the WFMD product with updated elevation data. We find a significant reduction of the localized features when GMTED2010 is replaced by recent topography data over Greenland based on ICESat-2 data. This study shows the importance of the chosen topography data on retrieved dry air mole fractions. Use of a precise and up-to-date as possible DEMis advised for all S5P data products as well as for future missions which rely on DEMas input data. A modification based on this study is planned to be introduced to the next version of the WFMD data product. [ABSTRACT FROM AUTHOR]

To evaluate the performance of the eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm, presented in the Part 1 companion paper to this paper, we apply the XBAER algorithm to the Sea and Land Surface Temperature Radiometer (SLSTR) instrument on board Sentinel-3. Snow properties – snow grain size (SGS), snow particle shape (SPS) and specific surface area (SSA) – are derived under cloud-free conditions. XBAER-derived snow properties are compared to other existing satellite products and validated by ground-based and aircraft measurements. The atmospheric correction is performed on SLSTR for cloud-free scenarios using Modern-Era Retrospective Analysis for Research and Applications (MERRA) aerosol optical thickness (AOT) and the aerosol typing strategy according to the standard XBAER algorithm. The optimal SGS and SPS are estimated iteratively utilizing a look-up-table (LUT) approach, minimizing the difference between SLSTR-observed and SCIATRAN-simulated surface directional reflectances at 0.55 and 1.6 µm. The SSA is derived for a retrieved SGS and SPS pair. XBAER-derived SGS, SPS and SSA have been validated using in situ measurements from the recent campaign SnowEx17 during February 2017. The comparison shows a relative difference between the XBAER-derived SGS and SnowEx17-measured SGS of less than 4 %. The difference between the XBAER-derived SSA and SnowEx17-measured SSA is 2.7 m 2 /kg. XBAER-derived SPS can be reasonably explained by the SnowEx17-observed snow particle shapes. Intensive validation shows that (1) for SGS and SSA, XBAER-derived results show high correlation with field-based measurements, with correlation coefficients higher than 0.85. The root mean square errors (RMSEs) of SGS and SSA are around 12 µm and 6 m 2 /kg. (2) For SPS, aggregate SPS retrieved by XBAER algorithm is likely to be matched with rounded grains while single SPS in XBAER is possibly linked to faceted crystals. The comparison with aircraft measurements, during the Polar Airborne Measurements and Arctic Regional Climate Model Simulation Project (PAMARCMiP) campaign held in March 2018, also shows good agreement (with R=0.82 and R=0.81 for SGS and SSA, respectively). XBAER-derived SGS and SSA reveal the variability in the aircraft track of the PAMARCMiP campaign. The comparison between XBAER-derived SGS results and the Moderate Resolution Imaging Spectroradiometer (MODIS) Snow-Covered Area and Grain size (MODSCAG) product over Greenland shows similar spatial distributions. The geographic distribution of XBAER-derived SPS over Greenland and the whole Arctic can be reasonably explained by campaign-based and laboratory investigations, indicating a reasonable retrieval accuracy of the retrieved SPS. The geographic variabilities in XBAER-derived SGS and SSA both over Greenland and Arctic-wide agree with the snow metamorphism process. [ABSTRACT FROM AUTHOR]

The lack of aerosol information over the cryosphere introduces large uncertainties to our understanding of phenomenon, known as the Arctic Amplification (AA) and its feedback mechanisms. The aerosol optical depth (AOD) describes the optical characteristics of aerosol loading. This paper describes a novel algorithm, which retrieves AOD above snow-covered regions from the measurements of the up-welling radiation at the top of atmosphere, observed by the Advanced Along-Track Scanning Radiometer (AATSR) and the Sea and Land Surface Temperature Radiometer (SLSTR) instruments. The algorithm optimizes the generic eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) approach for longer wavelengths over the cryosphere. The algorithm utilizes the characteristics of solar bidirectional distribution properties of snow and aerosol at wavelength 3.7 μm to derive above-snow-AOD. Since the impact of fine-mode aerosol on 3.7 μm is ignorable, the retrieved AOD in this manuscript represents mainly coarse-mode dominated part. A novel method to extract the solar reflection part at 3.7 μm is presented and used in the surface parameterization. Two aerosol types (sea salt-dominated and dust-dominated) are used and the best-fit type is derived by an iterative procedure, using a Look-Up-Table (LUT) approach. Sensitivity studies of the impact on the retrieved AOD using XBAER algorithm, which investigate the impacts of aerosol type, snow surface emissivity and potential cloud contamination under typical AATSR observation conditions, are presented. The sensitivity studies show that the surface parametrization and aerosol typing are suitable for the retrieval of above-snow-AOD over the Arctic snow-covered region. AOD observations retrieved in this study from AATSR (2002–2012) observation collocated with those from the Aerosol Robotic Network (AERONET) sites over Greenland show good agreement. 72.1% of the match-ups fall into the expected error envelope of (±0.15AOD ± 0.025). The AATSR derived above-snow-AOD at 0.55 μm research product has also been compared with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) aerosol product, the Mineral Aerosols Profiling from Infrared Radiances (MAPIR) derived Infrared Atmospheric Sounding Interferometer (IASI) AOD research product, and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) AOD simulations over Greenland on April 2011. The comparison reveals that all datasets show similar patterns for the AOD above Greenland. The AOD is smaller in central Greenland and larger over the coastline regions. The XBAER derived above-snow-AOD has improved coverage, as compared to that of the existing AATSR aerosol product. The transition between above-snow-AOD and AOD derived over surrounding ocean surfaces does not indicate any systematic errors. Two aerosol transport events have been well-captured by the XBAER derived above-snow-AOD research product. The new algorithm is also applied to the SLSTR onboard Sentinel-3 demonstrating new SLSTR above-snow-AOD data products, and its value for research in the changing AOD during the period of Arctic Amplification. • A new aerosol retrieval algorithm to derive AOD over cryosphere was developed. • Large AOD coverage extension over cryosphere has been achieved. • Validation by AERONET shows 72.1% retrievals fall into (±0.15AOD ± 0.025). • The comparison with MERRA, CALIOP and IASI products shows promising agreement. • Aerosol transport events have been well-captured by the new algorithm. [ABSTRACT FROM AUTHOR]