Abstract. Four years of continuous aerosol number size distribution measurements from the Arctic Climate Observatory in Tiksi, Russia, are analyzed. Tiksi is located in a region where in situ information on aerosol particle properties has not been previously available. Particle size distributions were measured with a differential mobility particle sizer (in the diameter range of 7–500 nm) and with an aerodynamic particle sizer (in the diameter range of 0.5–10 μm). Source region effects on particle modal features and number, and mass concentrations are presented for different seasons. The monthly median total aerosol number concentration in Tiksi ranges from 184 cm−3 in November to 724 cm−3 in July, with a local maximum in March of 481 cm−3. The total mass concentration has a distinct maximum in February–March of 1.72–2.38 μg m−3 and two minimums in June (0.42 μg m−3) and in September–October (0.36–0.57 μg m−3). These seasonal cycles in number and mass concentrations are related to isolated processes and phenomena such as Arctic haze in early spring, which increases accumulation and coarse-mode numbers, and secondary particle formation in spring and summer, which affects the nucleation and Aitken mode particle concentrations. Secondary particle formation was frequently observed in Tiksi and was shown to be slightly more common in marine, in comparison to continental, air flows. Particle formation rates were the highest in spring, while the particle growth rates peaked in summer. These results suggest two different origins for secondary particles, anthropogenic pollution being the important source in spring and biogenic emissions being significant in summer. The impact of temperature-dependent natural emissions on aerosol and cloud condensation nuclei numbers was significant: the increase in both the particle mass and the CCN (cloud condensation nuclei) number with temperature was found to be higher than in any previous study done over the boreal forest region. In addition to the precursor emissions of biogenic volatile organic compounds, the frequent Siberian forest fires, although far away, are suggested to play a role in Arctic aerosol composition during the warmest months. Five fire events were isolated based on clustering analysis, and the particle mass and cloud condensation nuclei number were shown to be somewhat affected by these events. In addition, during calm and cold months, aerosol concentrations were occasionally increased by local aerosol sources in trapping inversions. These results provide valuable information on interannual cycles and sources of Arctic aerosols.

Vegetation in the arctic tundra typically consists of a small-scale mosaic of plant communities, with species differing in growth forms, seasonality, and biogeochemical properties. Characterization of this variation is essential for understanding and modeling the functioning of the arctic tundra in global carbon cycling, as well as for evaluating the resolution requirements for remote sensing. Our objective was to quantify the seasonal development of the leaf-area index (LAI) and its variation among plant communities in the arctic tundra near Tiksi, coastal Siberia, consisting of graminoid, dwarf shrub, moss, and lichen vegetation. We measured the LAI in the field and used two very-high-spatial resolution multispectral satellite images (QuickBird and WorldView-2), acquired at different phenological stages, to predict landscape-scale patterns. We used the empirical relationships between the plant community-specific LAI and degree-day accumulation (0°C threshold) and quantified the relationship between the LAI and satellite NDVI (normalized difference vegetation index). Due to the temporal difference between the field data and satellite images, the LAI was approximated for the imagery dates, using the empirical model. LAI explained variation in the NDVI values well (R 2 adj. 0.42-0.92). Of the plant functional types, the graminoid LAI showed the largest seasonal amplitudes and was the main cause of the varying spatial patterns of the NDVI and the related LAI between the two images. Our results illustrate how the short growing season, rapid development of the LAI, yearly climatic variation, and timing of the satellite data should be accounted for in matching imagery and field verification data in the Arctic region.

Abstract. The non-uniform spatial integration, an inherent feature of the eddy covariance (EC) method, creates a challenge for flux data interpretation in a heterogeneous environment, where the contribution of different land cover types varies with flow conditions, potentially resulting in biased estimates in comparison to the areally averaged fluxes and land cover attributes. We modelled flux footprints and characterized the spatial scale of our EC measurements in Tiksi, a tundra site in northern Siberia. We used leaf area index (LAI) and land cover class (LCC) data, derived from very-high-spatial-resolution satellite imagery and field surveys, and quantified the sensor location bias. We found that methane (CH4) fluxes varied strongly with wind direction (−0.09 to 0.59 µgCH4m-2s-1 on average) during summer 2014, reflecting the distribution of different LCCs. Other environmental factors had only a minor effect on short-term flux variations but influenced the seasonal trend. Using footprint weights of grouped LCCs as explanatory variables for the measured CH4 flux, we developed a multiple regression model to estimate LCC group-specific fluxes. This model showed that wet fen and graminoid tundra patches in locations with topography-enhanced wetness acted as strong sources (1.0 µgCH4m-2s-1 during the peak emission period), while mineral soils were significant sinks (−0.13 µgCH4m-2s-1). To assess the representativeness of measurements, we upscaled the LCC group-specific fluxes to different spatial scales. Despite the landscape heterogeneity and rather poor representativeness of EC data with respect to the areally averaged LAI and coverage of some LCCs, the mean flux was close to the CH4 balance upscaled to an area of 6.3 km2, with a location bias of 14 %. We recommend that EC site descriptions in a heterogeneous environment should be complemented with footprint-weighted high-resolution data on vegetation and other site characteristics.

Abstract. Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm−3 in bare soil and lichen tundra and 89 g dm−3 in other LCTs. Total moss biomass varied from 0 to 820 g m−2, total vascular shoot mass from 7 to 112 g m−2 and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 ∘C in bare soil and lichen tundra, and varied from 5 to 9 ∘C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14–34 % of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6–15 % of variation. NDVI captured variation in vascular LAI better than in moss biomass, but while this difference was significant with late season NDVI, it was minimal with early season NDVI. For this reason, soil attributes associated with moss mass were better captured by early season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. The LCT map we produced had low to moderate uncertainty in predictions for plant and soil properties except for moss biomass and bare soil and lichen tundra LCTs. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM % and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance, topography or a LCT map. Despite the general accuracy of landscape level predictions in our LCT approach, this indicates challenges in the spatial extrapolation of some of those vegetation and soil attributes that are relevant for the regional ecosystem and global climate models.

Abstract. Four years of continuous aerosol number size distribution measurements from an Arctic Climate Observatory in Tiksi Russia are analyzed. Source region effects on particle modal features, and number and mass concentrations are presented for different seasons. The monthly median total aerosol number concentration in Tiksi ranges from 184 cm-3 in November to 724 cm-3 in July with a local maximum in March of 481 cm-3. The total mass concentration has a distinct maximum in February–March of 1.72–2.38 μg m-3 and two minimums in June of 0.42 μg m-3 and in September–October of 0.36–0.57 μg m-3. These seasonal cycles in number and mass concentrations are related to isolated aerosol sources such as Arctic haze in early spring which increases accumulation and coarse mode numbers, and biogenic emissions in summer which affects the smaller, nucleation and Aitken mode particles. The impact of temperature dependent natural emissions on aerosol and cloud condensation nuclei numbers was significant. Therefore, in addition to the precursor emissions of biogenic volatile organic compounds, the frequent Siberian forest fires, although far are suggested to play a role in Arctic aerosol composition during the warmest months. During calm and cold months aerosol concentrations were occasionally increased by nearby aerosol sources in trapping inversions. These results provide valuable information on inter-annual cycles and sources of Arctic aerosols.