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Vegetation is responding to climate change, which is especially prominent in the Arctic. Vegetation change is manifest in different ways and varies regionally, depending on the characteristics of the investigated area. Although vegetation in some Arctic areas has been thoroughly investigated, central Chukotka (NE Siberia) with its highly diverse vegetation, mountainous landscape and deciduous needle-leaf treeline remains poorly explored, despite showing strong greening in remote-sensing products. Here we quantify recent vegetation compositional changes in central Chukotka over 15 years between 2000/2001/2002 and 2016/2017. We numerically related field-derived information on foliage projective cover (percentage cover) of different plant taxa from 52 vegetation plots to remote-sensing derived (Landsat) spectral indices (Normalised Difference Vegetation Index (NDVI), Normalised Difference Water Index (NDWI) and Normalised Difference Snow Index (NDSI)) using constrained ordination. Clustering of ordination scores resulted in four land-cover classes: (1) larch closed-canopy forest, (2) forest tundra and shrub tundra, (3) graminoid tundra and (4) prostrate herb tundra and barren areas. We produced land-cover maps for early (2000, 2001 or 2002) and recent (2016 or 2017) time-slices for four focus regions along the tundra-taiga vegetation gradient. Transition from graminoid tundra to forest tundra and shrub tundra is interpreted as shrubification and amounts to 20% area increase in the tundra-taiga zone and 40% area increase in the northern taiga. Major contributors of shrubification are alder, dwarf birch and some species of the heather family. Land-cover change from the forest tundra and shrub tundra class to the larch closed-canopy forest class is interpreted as tree infilling and is notable in the northern taiga. We find almost no land-cover changes in the present treeless tundra.

International audience; The Arctic is directly impacted by climate change. The increase in air temperature drives the thawing of permafrost and an increase in coastal erosion and river discharge. This leads to a greater input of sediment and organic matter into coastal waters, which substantially impacts the ecosystems, the subsistence economy of the local population, and the climate because of the transformation of organic matter into greenhouse gases. Yet, the patterns of sediment dispersal in the nearshore zone are not well known, because ships do not often reach shallow waters and satellite remote sensing is traditionally focused on less dynamic environments. The goal of this study is to use the extensive Landsat archive to investigate sediment dispersal patterns specifically on an exemplary Arctic nearshore environment, where field measurements are often scarce. Multiple Landsat scenes were combined to calculate means of sediment dispersal and sea surface temperature under changing seasonal wind conditions in the nearshore zone of Herschel Island Qikiqtaruk in the western Canadian Arctic since 1982. We use observations in the Landsat red and thermal wavebands, as well as a recently published water turbidity algorithm to relate archive wind data to turbidity and sea surface temperature. We map the spatial patterns of turbidity and water temperature at high spatial resolution in order to resolve transport pathways of water and sediment at the water surface. Our results show that these pathways are clearly related to the prevailing wind conditions, being ESE and NW. During easterly wind conditions, both turbidity and water temperature are significantly higher in the nearshore area. The extent of the Mackenzie River plume and coastal erosion are the main explanatory variables for sediment dispersal and sea surface temperature distributions in the study area. During northwesterly wind conditions, the influence of the Mackenzie River plume is negligible. Our results highlight the potential of high spatial resolution Landsat imagery to detect small-scale hydrodynamic processes, but also show the need to specifically tune optical models for Arctic nearshore environments.

This paper describes two gas‐emission craters (GECs) in permafrost regions of the Yamal and Gydan peninsulas. We show that in three consecutive years after GEC formation (2014–2017), both morphometry and hydrochemistry of the inner crater lakes can become indistinguishable from other lakes. Craters GEC‐1 and AntGEC, with initial depths of 50–70 and 15–19 m respectively, have transformed into lakes 3–5 m deep. Crater‐like depressions were mapped in the bottom of 13 out of 22 Yamal lakes. However, we found no evidence that these depressions could have been formed as a result of gas emission. Dissolved methane (dCH4) concentration measured in the water collected from these depressions was at a background level (45 ppm on average). Yet, the concentration of dCH4 from the near‐bottom layer of lake GEC‐1 was significantly higher (824–968 ppm) during initial stages. We established that hydrochemical parameters (dissolved organic carbon, major ions, isotopes) measured in GEC lakes approached values measured in other lakes over time. Therefore, these parameters could not be used to search for Western Siberian lakes that potentially resulted from gas emission. Temperature profiles measured in GEC lakes show that the water column temperatures in GEC‐1 are lower than in Yamal lakes and in AntGEC – close to values of Gydan lakes. Given the initial GEC depth > 50 m, we suggest that at least in GEC‐1 possible re‐freezing of sediments from below might take place. However, with the present data we cannot establish the modern thickness of the closed talik under newly formed GEC lakes.

The presence of optically active water constituents is known to attenuate the light penetration in the ocean and impact the ocean heat content. Here, we investigate the influence of coloured dissolved organic matter (CDOM) and total suspended matter (TSM) on the radiative heating of the Laptev Sea shelf waters. The Laptev Sea region is heavily influenced by the Lena River, one of the largest river systems in the Arctic region. We simulate the radiative heating by using a coupled atmosphere-ocean radiative transfer model (RTM) and \textit{in situ} measurements from the TRANSDRIFT XVII expedition carried out in September 2010. The results indicate that CDOM and TSM have significant influence on the energy budget of the Laptev Sea shelf waters, absorbing most of the solar energy in the first \replaced{two meters}{2 m} of the water column. In the station with the highest CDOM absorption (a\textsubscript{CDOM}(443) = 1.77 m\textsuperscript{-1}) \replaced{$\sim$43}{42.6}\% more energy is absorbed in the surface layer compared to the station with the lowest a\textsubscript{CDOM}(443) ($\sim$0.2 m\textsuperscript{-1}), which translates to an increased \replaced{radiative}{radiant} heating rate of \replaced{$\sim$0.6}{0.57}\textdegree{}C\deleted[remark=]{/day}. The increased absorbed energy by the water constituents also implies in increased sea ice melt rate and changes in the surface heat fluxes to the atmosphere. By \replaced{using}{combining} satellite remote sensing and RTM we \replaced{quantify}{present} the spatial distribution of the radiative heating in the Laptev Sea for a typical summer day. The tools developed here \added[remark=]{(the combined use of satellite remote sensing, RT modeling and \textit{in situ} observations)} and tested in our case study can be used to improve the parameterizations of coupled atmosphere-ocean models to assess the \replaced{role}{feedback} of the ocean \added[remark=]{in the effect of} Arctic \replaced{a}{A}mplification.

Displacements of the Earth's surface can be estimated using differential interferometric synthetic aperture radar. The estimates are derived from the phase difference between two radar acquisitions. When at least three such acquisitions are available, one can compute the displacement between the first and the third acquisition and compare it with the sum of the two intermediate displacements. These two are expected to be equal for a piston-like spatially uniform deformation. However, this is not necessarily the case in measured data. Such lack of phase closure can be due to decorrelation noise alone. It has also been attributed to complex scattering processes such as soil moisture changes or multiple scattering sources. However, the nature of these nonrandom effects is only poorly understood in cold regions, as the role of snow and freeze/thaw processes has not been studied to date. To distinguish the noise-like and the systematic effects, an asymptotic Wald significance test is proposed. It detects situations when the observed closure error cannot solely be explained by noise. Such situations with $p are observed at the Ku-band during snow metamorphism and melt and following a summer precipitation event in Sodankyla, Finland. They can also be prevalent (> 25%) in the X-band observations of ice-rich permafrost regions in the Lena Delta, Russia, indicating the presence of processes that can have systematic and deleterious impacts on the estimation of surface movements. Satellite-based monitoring of these displacements is thus possibly subject to complex error sources in high-latitude regions.

The focus of this research has been on detecting changes in lake areas, vegetation, land surface temperatures, and the area covered by snow, using data from remote sensing. The study area covers the main (central) part of the Lena River catchment in the Yakutia region of Siberia (Russia), extending from east of Yakutsk to the central Siberian Plateau, and from the southern Lena River to north of the Vilyui River. Approximately 90% of the area is underlain by continuous permafrost. Remote sensing products were used to analyze changes in water bodies, land surface temperature (LST), and leaf area index (LAI), as well as the occurrence and extent of forest fires, and the area and duration of snow cover. The remote sensing analyses (for LST, snow cover, LAI, and fire) were based on MODIS-derived NASA products (250-1000 m) for 2000 to 2011. Changes in water bodies were calculated from two mosaics of (USGS) Landsat (30 m) satellite images from 2002 and 2009. Within the study area's 315,000 km2 the total area covered by lakes increased by 17.9% between 2002 and 2009, but this increase varied in different parts of the study area, ranging between 11% and 42%.The land surface temperatures showed a consistent warming trend, with an average increase of about 0.12 °C/year. The average rate of warming during the April-May transition period was 0.17 °C/year and 0.19 °C/year in the September-October period, but ranged up to 0.49 °C/year during September-October. Regional differences in the rates of land surface temperature change, and possible reasons for the temperature changes, are discussed with respect to changes in the land cover.Our analysis of a broad spectrum of variables over the study area suggests that the spring warming trend is very likely to be due to changes in the area covered by snow. The warming trend observed in fall does not, however, appear to be directly related to any changes in the area of snow cover, or to the atmospheric conditions, or to the proportion of the land surface that is covered by water (i.e., to wetting and drying).Supplementary data (original data, digitized version of the maps, metadata) are archived under PANGAEA (http://dx.doi.org/10.1594/PANGAEA.855124).

Climate change is affecting the rate of carbon cycling, particularly in the Arctic. Permafrost degradation through deeper thaw and physical disturbances results in the release of carbon dioxide and methane to the atmosphere and to an increase in lateral dissolved organic matter (DOM) fluxes. Whereas riverine DOM fluxes of the large Arctic rivers are well assessed, knowledge is limited with regard to small catchments that cover more than 40 % of the Arctic drainage basin. Here, we use absorption measurements to characterize changes in DOM quantity and quality in a low Arctic (Herschel Island, Yukon, Canada) and a high Arctic (Cape Bounty, Melville Island, Nunavut, Canada) setting with regard to geographical differences, impacts of permafrost degradation, and rainfall events. We find that DOM quantity and quality is controlled by differences in vegetation cover and soil organic carbon content (SOCC). The low Arctic site has higher SOCC and greater abundance of plant material resulting in higher chromophoric dissolved organic matter (cDOM) and dissolved organic carbon (DOC) than in the high Arctic. DOC concentration and cDOM in surface waters at both sites show strong linear relationships similar to the one for the great Arctic rivers. We used the optical characteristics of DOM such as cDOM absorption, specific ultraviolet absorbance (SUVA), ultraviolet (UV) spectral slopes (S275–295), and slope ratio (SR) for assessing quality changes downstream, at base flow and storm flow conditions, and in relation to permafrost disturbance. DOM in streams at both sites demonstrated optical signatures indicative of photodegradation downstream processes, even over short distances of 2000 m. Flow pathways and the connected hydrological residence time control DOM quality. Deeper flow pathways allow the export of permafrost-derived DOM (i.e. from deeper in the active layer), whereas shallow pathways with shorter residence times lead to the export of fresh surface- and near-surface-derived DOM. Compared to the large Arctic rivers, DOM quality exported from the small catchments studied here is much fresher and therefore prone to degradation. Assessing optical properties of DOM and linking them to catchment properties will be a useful tool for understanding changing DOM fluxes and quality at a pan-Arctic scale.

River water is the main source of dissolved organic carbon (DOC) in the Arctic Ocean. DOC plays an important role in the Arctic carbon cycle, and its export from land to sea is expected to increase as ongoing climate change accelerates permafrost thaw. However, transport pathways and transformation of DOC in the land-to-ocean transition are mostly unknown. We collected DOC and aCDOM(λ) samples from 11 expeditions to river, coastal and offshore waters and present a new DOC–aCDOM(λ) model for the fluvial–marine transition zone in the Laptev Sea. The aCDOM(λ) characteristics revealed that the dissolved organic matter (DOM) in samples of this dataset are primarily of terrigenous origin. Observed changes in aCDOM(443) and its spectral slopes indicate that DOM is modified by microbial and photo-degradation. Ocean colour remote sensing (OCRS) provides the absorption coefficient of coloured dissolved organic matter (aCDOM(λ)sat) at λ=440 or 443 nm, which can be used to estimate DOC concentration at high temporal and spatial resolution over large regions. We tested the statistical performance of five OCRS algorithms and evaluated the plausibility of the spatial distribution of derived aCDOM(λ)sat. The OLCI (Sentinel-3 Ocean and Land Colour Instrument) neural network swarm (ONNS) algorithm showed the best performance compared to in situ aCDOM(440) (r2=0.72). Additionally, we found ONNS-derived aCDOM(440), in contrast to other algorithms, to be partly independent of sediment concentration, making ONNS the most suitable aCDOM(λ)sat algorithm for the Laptev Sea region. The DOC–aCDOM(λ) model was applied to ONNS-derived aCDOM(440), and retrieved DOC concentration maps showed moderate agreement to in situ data (r2=0.53). The in situ and satellite-retrieved data were offset by up to several days, which may partly explain the weak correlation for this dynamic region. Satellite-derived surface water DOC concentration maps from Medium Resolution Imaging Spectrometer (MERIS) satellite data demonstrate rapid removal of DOC within short time periods in coastal waters of the Laptev Sea, which is likely caused by physical mixing and different types of degradation processes. Using samples from all occurring water types leads to a more robust DOC–aCDOM(λ) model for the retrievals of DOC in Arctic shelf and river waters.

The timing of snowmelt is an important turning point in the seasonal cycle of small Arctic catchments. The TerraSAR-X (TSX) satellite mission is a synthetic aperture radar system (SAR) with high potential to measure the high spatiotemporal variability of snow cover extent (SCE) and fractional snow cover (FSC) on the small catchment scale. We investigate the performance of multi-polarized and multi-pass TSX X-Band SAR data in monitoring SCE and FSC in small Arctic tundra catchments of Qikiqtaruk (Herschel Island) off the Yukon Coast in the Western Canadian Arctic. We applied a threshold based segmentation on ratio images between TSX images with wet snow and a dry snow reference, and tested the performance of two different thresholds. We quantitatively compared TSX- and Landsat 8-derived SCE maps using confusion matrices and analyzed the spatiotemporal dynamics of snowmelt from 2015 to 2017 using TSX, Landsat 8 and in situ time lapse data. Our data showed that the quality of SCE maps from TSX X-Band data is strongly influenced by polarization and to a lesser degree by incidence angle. VH polarized TSX data performed best in deriving SCE when compared to Landsat 8. TSX derived SCE maps from VH polarization detected late lying snow patches that were not detected by Landsat 8. Results of a local assessment of TSX FSC against the in situ data showed that TSX FSC accurately captured the temporal dynamics of different snow melt regimes that were related to topographic characteristics of the studied catchments. Both in situ and TSX FSC showed a longer snowmelt period in a catchment with higher contributions of steep valleys and a shorter snowmelt period in a catchment with higher contributions of upland terrain. Landsat 8 had fundamental data gaps during the snowmelt period in all 3 years due to cloud cover. The results also revealed that by choosing a positive threshold of 1 dB, detection of ice layers due to diurnal temperature variations resulted in a more accurate estimation of snow cover than a negative threshold that detects wet snow alone. We find that TSX X-Band data in VH polarization performs at a comparable quality to Landsat 8 in deriving SCE maps when a positive threshold is used. We conclude that TSX data polarization can be used to accurately monitor snowmelt events at high temporal and spatial resolution, overcoming limitations of Landsat 8, which due to cloud related data gaps generally only indicated the onset and end of snowmelt., Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe, 689

In permafrost areas, seasonal freeze-thaw cycles result in upward and downward movements of the ground. For some permafrost areas, long-term downward movements were reported during the last decade. We measured seasonal and multi-year ground movements in a yedoma region of the Lena River Delta, Siberia, in 2013–2017, using reference rods installed deep in the permafrost. The seasonal subsidence was 1.7 ± 1.5 cm in the cold summer of 2013 and 4.8 ± 2 cm in the warm summer of 2014. Furthermore, we measured a pronounced multi-year net subsidence of 9.3 ± 5.7 cm from spring 2013 to the end of summer 2017. Importantly, we observed a high spatial variability of subsidence of up to 6 cm across a sub-meter horizontal scale. In summer 2013, we accompanied our field measurements with Differential Synthetic Aperture Radar Interferometry (DInSAR) on repeat-pass TerraSAR-X (TSX) data from the summer of 2013 to detect summer thaw subsidence over the same study area. Interferometry was strongly affected by a fast phase coherence loss, atmospheric artifacts, and possibly the choice of reference point. A cumulative ground movement map, built from a continuous interferogram stack, did not reveal a subsidence on the upland but showed a distinct subsidence of up to 2 cm in most of the thermokarst basins. There, the spatial pattern of DInSAR-measured subsidence corresponded well with relative surface wetness identified with the near infra-red band of a high-resolution optical image. Our study suggests that (i) although X-band SAR has serious limitations for ground movement monitoring in permafrost landscapes, it can provide valuable information for specific environments like thermokarst basins, and (ii) due to the high sub-pixel spatial variability of ground movements, a validation scheme needs to be developed and implemented for future DInSAR studies in permafrost environments.

Permafrost landscapes experience different disturbances and store large amounts of organic matter, which may become a source of greenhouse gases upon permafrost degradation. We analysed the influence of terrain and geomorphic disturbances (e.g. soil creep, active-layer detachment, gullying, thaw slumping, accumulation of fluvial deposits) on soil organic carbon (SOC) and total nitrogen (TN) storage using 11 permafrost cores from Herschel Island, western Canadian Arctic. Our results indicate a strong correlation between SOC storage and the topographic wetness index. Undisturbed sites stored the majority of SOC and TN in the upper 70 cm of soil. Sites characterised by mass wasting showed significant SOC depletion and soil compaction, whereas sites characterised by the accumulation of peat and fluvial deposits store SOC and TN along the whole core. We upscaled SOC and TN to estimate total stocks using the ecological units determined from vegetation composition, slope angle and the geomorphic disturbance regime. The ecological units were delineated with a supervised classification based on RapidEye multispectral satellite imagery and slope angle. Mean SOC and TN storage for the uppermost 1 m of soil on Herschel Island are 34.8 kg C m-2 and 3.4 kg N m-2, respectively. Copyright © 2015 John Wiley & Sons, Ltd.

Aims: An Arctic Vegetation Classification (AVC) is needed to address issues related to rapid Arctic-wide changes to climate, land-use, and biodiversity. Location: The 7.1 million km2 Arctic tundra biome. Approach and conclusions: The purpose, scope and conceptual framework for an Arctic Vegetation Archive (AVA) and Classification (AVC) were developed during numerous workshops starting in 1992. The AVA and AVC are modeled after the European vegetation archive (EVA) and classification (EVC). The AVA will use Turboveg for data management. The AVC will use a Braun-Blanquet (Br.-Bl.) classification approach. There are approximately 31,000 Arctic plots that could be included in the AVA. An Alaska AVA (AVA-AK, 24 datasets, 3026 plots) is a prototype for archives in other parts of the Arctic. The plan is to eventually merge data from other regions of the Arctic into a single Turboveg v3 database. We present the pros and cons of using the Br.-Bl. classification approach compared to the EcoVeg (US) and Biogeoclimatic Ecological Classification (Canada) approaches. The main advantages are that the Br.-Bl. approach already has been widely used in all regions of the Arctic, and many described, well-accepted vegetation classes have a pan-Arctic distribution. A crosswalk comparison of Dryas octopetala communities described according to the EcoVeg and the Braun-Blanquet approaches indicates that the non-parallel hierarchies of the two approaches make crosswalks difficult above the plantcommunity level. A preliminary Arctic prodromus contains a list of typical Arctic habitat types with associated described syntaxa from Europe, Greenland, western North America, and Alaska. Numerical clustering methods are used to provide an overview of the variability of habitat types across the range of datasets and to determine their relationship to previously described Braun-Blanquet syntaxa. We emphasize the need for continued maintenance of the Pan-Arctic Species List, and additional plot data to fully sample the variability across bioclimatic subzones, phytogeographic regions, and habitats in the Arctic. This will require standardized methods of plot-data collection, inclusion of physiogonomic information in the numeric analysis approaches to create formal definitions for vegetation units, and new methods of data sharing between the AVA and national vegetation- plot databases.

Arctic vegetation phenology is a sensitive indicator of a changing climate and rapid assessment of vegetation status is necessary to more comprehensively understand the impacts on foliar condition and photosynthetic activity. Airborne and space-borne optical remote sensing have been successfully used to monitor vegetation phenology in Arctic ecosystems by exploiting the biophysical and biochemical changes associated with vegetation growth and senescence. However, persistent cloud cover and low sun angles in the region make the acquisition of high quality temporal optical data within one growing season challenging. In the following study, we examine the capability of “near-field” remote sensing technologies, in this case digital, true colour, cameras to produce surrogate in-situ spectral data to characterize changes in vegetation driven by seasonal pigment dynamics. Simple linear regression was used to investigate relationships between common pigment-driven spectral indices calculated from field-based spectrometry and red, green, and blue (RGB) indices from corresponding digital photographs in three dominant vegetation communities across three major seasons at Toolik Lake, North Slope, Alaska. We chose the strongest and most consistent RGB index across all communities to represent each spectral index. Next, linear regressions were used to relate RGB indices and extracted leaf-level pigment content with a simple additive error propagation of the root mean square error (RMSE). Results indicate that the green-based RGB indices had the strongest relationship with chlorophyll a and total chlorophyll, while a red-based RGB index showed moderate relationships with the chlorophyll to carotenoid ratio. The results suggest that vegetation colour contributes strongly to the response of pigment-driven spectral indices and RGB data can act as a surrogate to track seasonal vegetation change associated with pigment development and degradation. Overall, we find that low-cost, easy-to-use digital cameras can monitor vegetation status and changes related to seasonal foliar condition and photosynthetic activity in three dominant, low-Arctic vegetation communities.

Satellite‐derived surface soil moisture data are available for the Arctic, but detailed validation is still lacking. Previous studies have shown low correlations between in situ and modeled data. It is hypothesized that soil temperature variations after soil thaw impact MetOp ASCAT satellite‐derived surface soil moisture (SSM) measurements in wet tundra environments, as C band backscatter is sensitive to changes in dielectric properties. We compare in situ measurements of water content within the active layer at four sites across the Arctic in Alaska (Barrow, Sagwon, Toolik) and Siberia (Tiksi), taken in the spring after thawing and in autumn prior to freezing. In addition to the long‐term measurement fields, where sensors are installed deeper in the ground, we designed a monitoring setup for measuring moisture very close to the surface in the Lena River Delta, Siberia. The volumetric water content (VWC) and soil temperature sensors were placed in the moss organic layer in order to account for the limited penetration depth of the radar signal. ASCAT SSM variations are generally very small, in line with the low variability of in situ VWC. Short‐term changes after complete thawing of the upper organic layer, however, seem to be mostly influenced by soil temperature. Correlations between SSM and in situ VWC are generally very low, or even negative. Mean standard deviation matching results in a comparably high root‐mean‐square error (on average 11%) for predictions of VWC. Further investigations and measurement networks are needed to clarify factors causing temporal variation of C band backscatter in tundra regions., Key Points Organic layer temperature variations explain temporal behavior of soil moisture derived from C band radar in unfrozen wet tundraTemporal variability of volumetric water content from in situ point measurements is representative over distances of several kilometers in tundraNear‐surface volumetric water content predicted from matched ASCAT data has an average RMSE of 11% across five sites in Alaska and Siberia

Arctic warming is leading to substantial changes to permafrost including rapid Degradation of ice and ice-rich coasts and riverbanks. In this study, we present and evaluate a high spatiotemporal resolution three-year time series of X-Band microwave satellite data from the TerraSAR-X (TSX) satellite to quantify cliff-top erosion (CTE) of an ice-rich permafrost riverbank in the central Lena Delta. We apply a threshold on TSX backscatter images and automatically extract cliff-top lines to derive intra- and inter-annual CTE. In order to examine the drivers of erosion we statistically compare CTE with climatic baseline data using linear mixed models and analysis of variance (ANOVA). Our evaluation of TSX-derived CTE against annual optical-derived CTE and seasonal in situ measurements showed good agreement between all three datasets. We observed continuous erosion from June to September in 2014 and 2015 with no significant seasonality across the thawing season. We found the highest net annual cliff-top erosion of 6.9 m in 2014, in accordance with above-average mean temperatures and thawing degree days as well as low precipitation. We found high net annual erosion and erosion variability in 2015 associated with moderate mean temperatures but above average precipitation. According to linear mixed models, climate parameters alone could not explain intra-seasonal erosional patterns and additional factors such as ground ice content likely drive the observed erosion. Finally, mean backscatter intensity on the cliff surface decreased from -5.29 to -6.69 dB from 2013 to 2015, respectively, likely resulting from changes in surface geometry and properties that could be connected to partial slope stabilization. Overall, we conclude that X-Band backscatter time series can successfully be used to complement optical remote sensing and in situ monitoring of rapid tundra permafrost erosion at riverbanks and coasts by reliably providing information about intra-seasonal dynamics.

Arctic tundra ecosystems exhibit small-scale variations in species composition, micro-topography as well as significant spatial and temporal variations in moisture. These attributes result in similar spectral characteristics between distinct vegetation communities. In this study we examine spectral variability at three phenological phases of leaf-out, maximum canopy, and senescence of ground-based spectroscopy, as well as a simulated Environmental Mapping and Analysis Program (EnMAP) and simulated Sentinel-2 reflectance spectra, from five dominant low-Arctic tundra vegetation communities in the Toolik Lake Research Area, Alaska, in order to inform spectral differentiation and subsequent vegetation classification at both the ground and satellite scale. We used the InStability Index (ISI), a ratio of between endmember and within endmember variability, to determine the most discriminative phenophase and wavelength regions for identification of each vegetation community. Our results show that the senescent phase was the most discriminative phenophase for the identification of the majority of communities when using both ground-based and simulated EnMAP reflectance spectra. Maximum canopy was the most discriminative phenophase for the majority of simulated Sentinel-2 reflectance data. As with previous ground-based spectral characterization of Alaskan low-Arctic tundra, the blue, red, and red-edge parts of the spectrum were most discriminative for all three reflectance datasets. Differences in vegetation colour driven by pigment dynamics appear to be the optimal areas of the spectrum for differentiation using high spectral resolution field spectroscopy and simulated hyperspectral EnMAP and multispectral Sentinel-2 reflectance spectra. The phenological aspect of this study highlights the potential exploitation of more extreme colour differences in vegetation observed during senescence when hyperspectral data is available. The results provide insight into both the community and seasonal dynamics of spectral variability to better understand and interpret currently used broadband vegetation indices and also for improved spectral unmixing of hyperspectral aerial and satellite data which is useful for a wide range of applications from fine-scale monitoring of shifting vegetation composition to the identification of vegetation vigor.

International audience; The MEthane Remote sensing Lidar missioN (MERLIN) aims at demonstrating the spaceborne active measurement of atmospheric methane, a potent greenhouse gas, based on an Integrated Path Differential Absorption (IPDA) nadir-viewing LIght Detecting and Ranging (Lidar) instrument. MERLIN is a joint French and German space mission, with a launch currently scheduled for the timeframe 2021/22. The German Space Agency (DLR) is responsible for the payload, while the platform (MYRIADE Evolutions product line) is developed by the French Space Agency (CNES). The main scientific objective of MERLIN is the delivery of weighted atmospheric columns of methane dry-air mole fractions for all latitudes throughout the year with systematic errors small enough (

The Lena Delta in Northern Siberia is one of the largest river deltas in the world. During peak discharge, after the ice melt in spring, it delivers between 60–8000 m3s−1 of water and sediment into the Arctic Ocean. The Lena Delta and the Laptev Sea coast also constitute a~continuous permafrost region. Ongoing climate change, which is particularly pronounced in the Arctic, is leading to increased rates of permafrost thaw. This is likely to profoundly change the discharge rates of the Lena River and the chemistry of the river waters which are discharged into the coastal Laptev Sea, e.g. by increasing concentrations of inorganic nutrients, DOC and importantly methane. These physical and chemical changes will also affect the composition of and interactions between phytoplankton and zooplankton communities, forming the basis of the food web. However, before potential consequences of climate change for coastal arctic plankton communities can be judged, the inherent status of the diversity and linked foodweb interactions within the delta need to be established. As part of the AWI Lena Delta Programme in 2010 the phyto- and microzooplankton community in three river channels as well as four coastal transects were investigated to capture the typical river phytoplankton communities and the transitional zone of brackish/marine conditions. Most CTD profiles from 23 coastal stations showed very strong stratification. The only exception to this was a small a shallow and mixed area running from the outflow of Bykovskaya channel in a northerly direction parallel to the shore (transect 3). Of the five stations in this area three had a salinity of close to zero. Two further stations had salinities of around 2 and 5 throughout the water column. In the remaining transects on the other hand salinities varied between 5–30 with depth. Phytoplankton counts from the outflow from the Lena were dominated by diatoms (Aulacoseira species) cyanobacteria (Aphanizomenon, Pseudanabaena) and chlorophytes, in those stations characterized by river outflow (stations in the Lena itself and in coastal transect 3). In contrast in the stratified stations the plankton was mostly dominated by dinoflagellates, ciliates and nanoflagellates, with only an insignificant diatom component from the genera Chaetoceros and Thalassiosira (brackish as opposed to freshwater species). Ciliate abundance was significantly coupled with the abundance of total flagellates. A pronounced partitioning in the phytoplankton community was also discernible with depth, with a different community composition and abundance above and below the thermocline in the stratified sites. This work represents the first attempt at analyzing the phytoplankton structure of the region of freshwater influence at confluence Lena–Laptev sea.

Water bodies are ubiquitous features in Arctic wetlands. Ponds, i.e., waters with a surface area smaller than 104 m2, have been recognized as hotspots of biological activity and greenhouse gas emissions but are not well inventoried. This study aimed to identify common characteristics of three Arctic wetlands including water body size and abundance for different spatial resolutions, and the potential of Landsat-5 TM satellite data to show the subpixel fraction of water cover (SWC) via the surface albedo. Water bodies were mapped using optical and radar satellite data with resolutions of 4mor better, Landsat-5 TM at 30mand the MODIS water mask (MOD44W) at 250m resolution. Study sites showed similar properties regarding water body distributions and scaling issues. Abundance-size distributions showed a curved pattern on a log-log scale with a flattened lower tail and an upper tail that appeared Paretian. Ponds represented 95% of the total water body number. Total number of water bodies decreased with coarser spatial resolutions. However, clusters of small water bodies were merged into single larger water bodies leading to local overestimation of water surface area. To assess the uncertainty of coarse-scale products, both surface water fraction and the water body size distribution should therefore be considered. Using Landsat surface albedo to estimate SWC across different terrain types including polygonal terrain and drained thermokarst basins proved to be a robust approach. However, the albedo–SWC relationship is site specific and needs to be tested in other Arctic regions. These findings present a baseline to better represent small water bodies of Arctic wet tundra environments in regional as well as global ecosystem and climate models.

To project the future development of the soil organic carbon (SOC) storage in permafrost environments, the spatial and vertical distribution of key soil properties and their landscape controls needs to be understood. This article reports findings from the Arctic Lena River Delta where we sampled 50 soil pedons. These were classified according to the U.S.D.A. Soil Taxonomy and fall mostly into the Gelisol soil order used for permafrost-affected soils. Soil profiles have been sampled for the active layer (mean depth 58 ± 10 cm) and the upper permafrost to one meter depth. We analyze SOC stocks and key soil properties, i.e. C%, N%, C/N, bulk density, visible ice and water content. These are compared for different landscape groupings of pedons according to geomorphology, soil and land cover and for different vertical depth increments. High vertical resolution plots are used to understand soil development. These show that SOC storage can be highly variable with depth. We recommend the treatment of permafrost-affected soils according to subdivisions into: the surface organic layer, mineral subsoil in the active layer, organic enriched cryoturbated or buried horizons and the mineral subsoil in the permafrost. The major geomorphological units of a subregion of the Lena River Delta were mapped with a land form classification using a data-fusion approach of optical satellite imagery and digital elevation data to upscale SOC storage. Landscape mean SOC storage is estimated to 19.2 ± 2.0 kg C m− 2. Our results show that the geomorphological setting explains more soil variability than soil taxonomy classes or vegetation cover. The soils from the oldest, Pleistocene aged, unit of the delta store the highest amount of SOC per m2 followed by the Holocene river terrace. The Pleistocene terrace affected by thermal-degradation, the recent floodplain and bare alluvial sediments store considerably less SOC in descending order.

Permafrost soils have been shown to respond rapidly to warming temperatures. When ice-rich permafrost soils thaw, the melting ground ice reduces the volume and stability of the soils, inducing changes in the topography. We monitor surface elevation changes in three test sites in Northern Eurasia using single-pass TanDEM-X Science Phase data with submetre vertical precision. The results indicate the suitability of single-pass InSAR data for monitoring thaw-induced topographic changes (e.g. coastal erosion) but they also reveal the spurious impact of late-lying snow packs and water bodies, both of which are common in lowland permafrost areas. Furthermore, the coherence and hence the precision with which elevation changes can be estimated is found to be limited by the noise level in certain cases. As some of these influences could be mitigated using appropriate mission and acquisition designs, we conclude that single-pass interferometry has considerable potential for monitoring thaw-induced surface elevation changes in permafrost areas, which in turn could contribute to assessing their vulnerability, fate, and climate system feedback in a warming climate.

Thermokarst lakes and ponds are major elements of permafrost landscapes, occupying up to 40% of the land area in some Arctic regions. Shallow lakes freeze to the bed, thus preventing permafrost thaw underneath them and limiting the length of the period with greenhouse gas production in the unfrozen lake sediments. Radar remote sensing permits to distinguish lakes with bedfast ice due to the difference in backscatter intensities from bedfast and floating ice. This study investigates the potential of a unique time series of three-year repeat-pass TerraSAR-X (TSX) imagery with high temporal (11 days) and spatial (10 m) resolution for monitoring bedfast ice as well as ice phenology of lakes in the zone of continuous permafrost in the Lena River Delta, Siberia. TSX backscatter intensity is shown to be an excellent tool for monitoring floating versus bedfast lake ice as well as ice phenology. TSX-derived timing of ice grounding and the ice growth model CLIMo are used to retrieve the ice thicknesses of the bedfast ice at points where in situ ice thickness measurements were available. Comparison shows good agreement in the year of field measurements. Additionally, for the first time, an 11-day sequential interferometric coherence time series is analyzed as a supplementary approach for the bedfast ice monitoring. The coherence time series detects most of the ice grounding as well as spring snow/ice melt onset. Overall, the results show the great value of TSX time series for monitoring Arctic lake ice and provide a basis for various applications: for instance, derivation of shallow lakes bathymetry, evaluation of winter water resources and locating fish winter habitat as well as estimation of taliks extent in permafrost.

In this study, we analyze interactions in lake and lake catchment systems of a continuous permafrost area. We assessed colored dissolved organic matter (CDOM) absorption at 440 nm (a(440)(CDOM)) and absorption slope (S300-500) in lakes using field sampling and optical remote sensing data for an area of 350 km(2) in Central Yamal, Siberia. Applying a CDOM algorithm (ratio of green and red band reflectance) for two high spatial resolution multispectral GeoEye-1 and Worldview-2 satellite images, we were able to extrapolate the a()(CDOM) data from 18 lakes sampled in the field to 356 lakes in the study area (model R-2 = 0.79). Values of a(440)(CDOM) in 356 lakes varied from 0.48 to 8.35 m(-1) with a median of 1.43 m(-1). This a()(CDOM) dataset was used to relate lake CDOM to 17 lake and lake catchment parameters derived from optical and radar remote sensing data and from digital elevation model analysis in order to establish the parameters controlling CDOM in lakes on the Yamal Peninsula. Regression tree model and boosted regression tree analysis showed that the activity of cryogenic processes (thermocirques) in the lake shores and lake water level were the two most important controls, explaining 48.4% and 28.4% of lake CDOM, respectively (R-2 = 0.61). Activation of thermocirques led to a large input of terrestrial organic matter and sediments from catchments and thawed permafrost to lakes (n = 15, mean a(440)(CDOM) = 5.3 m(-1)). Large lakes on the floodplain with a connection to Mordy-Yakha River received more CDOM (n = 7, mean a(440)(CDOM) = 3.8 m(-1)) compared to lakes located on higher terraces., Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe; 1333

The Lena River forms one of the largest deltas in the Arctic. We compare two sets of data to reveal new insights into the hydrological, hydrochemical, and geochemical processes within the delta: (i) long-term hydrometric observations at the Khabarova station at the head of the delta from 1951 to 2005; (ii) field hydrological and geochemical observations carried out within the delta since 2002. Periods with differing relative discharge and intensity of fluvial processes were identified from the long-term record of water and sediment discharge. Ice events during spring melt (high water) reconfigured branch channels and probably influenced sediment transport within the delta. Based on summer field measurements during 2005–2012 of discharge and sediment fluxes along main delta channels, both are increased between the apex and the front of the delta. This increase is to a great extent connected with an additional influx of water from tributaries, as well as an increase of suspended and dissolved material released from the ice complex. Summer concentrations of major ion and biogenic substances along the delta branches are partly explained by water sources within the delta, such as thawing ice complex waters, small Lena River branches and estuarine areas.

The rapidly changing East Siberian Arctic Shelf (ESAS) receives large amounts of terrestrial organic carbon (OC) from coastal erosion and Russian-Arctic rivers. Climate warming increases thawing of coastal Ice Complex Deposits (ICD) and can change both the amount of released OC, as well as its propensity to be converted to greenhouse gases (fueling further global warming) or to be buried in coastal sediments. This study aimed to unravel the susceptibility to degradation, and transport and dispersal patterns of OC delivered to the ESAS. Bulk and molecular radiocarbon analyses on surface particulate matter (PM), sinking PM and underlying surface sediments illustrate the active release of old OC from coastal permafrost. Molecular tracers for recalcitrant soil OC showed ages of 3.4-13 14C-ky in surface PM and 5.5-18 14C-ky in surface sediments. The age difference of these markers between surface PM and surface sediments is larger (i) in regions with low OC accumulation rates, suggesting a weaker exchange between water column and sediments, and (ii) with increasing distance from the Lena River, suggesting preferential settling of fluvially derived old OC nearshore. A dual-carbon end-member mixing model showed that (i) contemporary terrestrial OC is dispersed mainly by horizontal transport while being subject to active degradation, (ii) marine OC is most affected by vertical transport and also actively degraded in the water column, and (iii) OC from ICD settles rapidly and dominates surface sediments. Preferential burial of ICD-OC released into ESAS coastal waters might therefore lower the suggested carbon cycle climate feedback from thawing ICD permafrost.

Enhanced permafrost warming and increased Arctic river discharges have heightened concern about the input of terrigenous matter into Arctic coastal waters. We used optical operational satellite data from the ocean colour sensor MERIS (Medium-Resolution Imaging Spectrometer) aboard the ENVISAT satellite mission for synoptic monitoring of the pathways of terrigenous matter on the shallow Laptev Sea shelf. Despite the high cloud coverage in summer that is inherent to this Arctic region, time series from MERIS satellite data from 2006 on to 2011 could be acquired and were processed using the Case-2 Regional Processor (C2R) for optically complex surface waters installed in the open-source software ESA BEAM-VISAT. Since optical remote sensing using ocean colour satellite data has seen little application in Siberian Arctic coastal and shelf waters, we assess the applicability of the calculated MERIS C2R parameters with surface water sampling data from the Russian–German ship expeditions LENA2008, LENA2010 and TRANSDRIFT-XVII taking place in August 2008 and August and September 2010 in the southern Laptev Sea. The shallow Siberian shelf waters are optically not comparable to the deeper, more transparent waters of the Arctic Ocean. The inner-shelf waters are characterized by low transparencies, due to turbid river water input, terrestrial input by coastal erosion, resuspension events and, therefore, high background concentrations of suspended particulate matter and coloured dissolved organic matter. We compared the field-based measurements with the satellite data that are closest in time. The match-up analyses related to LENA2008 and LENA2010 expedition data show the technical limits of matching in optically highly heterogeneous and dynamic shallow inner-shelf waters. The match-up analyses using the data from the marine TRANSDRIFT expedition were constrained by several days' difference between a match-up pair of satellite-derived and in situ parameters but are also based on the more stable hydrodynamic conditions of the deeper inner- and the outer-shelf waters. The relationship of satellite-derived turbidity-related parameters versus in situ suspended matter from TRANSDRIFT data shows that the backscattering coefficient C2R_bb_spm can be used to derive a Laptev-Sea-adapted SPM algorithm. Satellite-derived Chl a estimates are highly overestimated by a minimum factor of 10 if applied to the inner-shelf region due to elevated concentrations of terrestrial organic matter. To evaluate the applicability of ocean colour remote sensing, we include the visual analysis of lateral hydrographical features. The mapped turbidity-related MERIS C2R parameters show that the Laptev Sea is dominated by resuspension above submarine shallow banks and by frontal instabilities such as frontal meanders with amplitudes up to 30 km and eddies and filaments with horizontal scales up to 100 km that prevail throughout the sea-ice-free season. The widespread turbidity above submarine shallow banks indicates inner-shelf vertical mixing that seems frequently to reach down to submarine depths of a minimum of 10 m. The resuspension events and the frontal meanders, filaments and eddies indicate enhanced vertical mixing being widespread on the inner shelf. It is a new finding for the Laptev Sea that numerous frontal instabilities are made visible, and how highly time-dependent and turbulent the Laptev Sea shelf is. The meanders, filaments and eddies revealed by the ocean colour parameters indicate the lateral transportation pathways of terrestrial and living biological material in surface waters.

Remote sensing has become a valuable tool in monitoring arctic environments. The aim of this paper is ground-based hyperspectral characterization of Low Arctic Alaskan tundra communities along four environmental gradients (regional climate, soil pH, toposequence, and soil moisture) that all vary in ground cover, biomass, and dominating plant communities. Field spectroscopy in connection with vegetation analysis was carried out in summer 2012, along the North American Arctic Transect (NAAT). Spectral metrics were extracted, including the averaged reflectance and absorption-related metrics such as absorption depths and area of continuum removal. The spectral metrics were investigated with respect to “greenness”, biomass, vegetation height, and soil moisture regimes. The results show that the surface reflectances of all sites are similar in shape with a reduced near-infrared (NIR) reflectance that is specific for low-growing biomes. The main spectro-radiometric findings are: (i) Southern sites along the climate gradient have taller shrubs and greater overall vegetation biomass, which leads to higher reflectance in the NIR. (ii) Vegetation height and surface wetness are two antagonists that balance each other out with respect to the NIR reflectance along the toposequence and soil moisture gradients. (iii) Moist acidic tundra (MAT) sites have “greener” species, more leaf biomass, and green-colored moss species that lead to higher pigment absorption compared to moist non-acidic tundra (MNT) sites. (iv) MAT and MNT plant community separation via narrowband Normalized Difference Vegetation Index (NDVI) shows the potential of hyperspectral remote sensing applications in the tundra.

This study aims to establish, evaluate, and apply a modern pollen-climate transfer function from the transition zone between arctic tundra and light-needled taiga in Arctic Siberia. Lacustrine samples (n = 96) from the northern Siberian lowlands of Yakutia were collected along four north-to-south transects crossing the arctic forest line. Samples span a broad temperature and precipitation gradient (mean July temperature, T-July: 7.5-18.7 degrees C; mean annual precipitation, P-ann: 114-315 mm/yr). Redundancy analyses are used to examine the relationship between the modern pollen signal and corresponding vegetation types and climate. Performance of transfer functions for T-July and P-ann were cross-validated and tested for spatial autocorrelation effects. The root mean square errors of prediction are 1.67 degrees C for T-July and 40 mm/yr for P-ann. A climate reconstruction based on fossil pollen spectra from a Siberian Arctic lake sediment core spanning the Holocene yielded cold conditions for the Late Glacial (1-2 degrees C below present T-July). Warm and moist conditions were reconstructed for the early to mid Holocene (2 degrees C higher T-July than present), and climate conditions similar to modern ones were reconstructed for the last 4000 years. In conclusion, our modern pollen data set fills the gap of existing regional calibration sets with regard to the underrepresented Siberian tundra-taiga transition zone. The Holocene climate reconstruction indicates that the temperature deviation from modern values was only moderate despite the assumed Arctic sensitivity to present climate change.

In this investigation we focused on the development of a new water detection algorithm based on VIS-NIR imaging spectroscopy data. By analyzing different images containing inland and ocean water types we found the slopes of the reflectance spectrum of water at specific spectral wavelengths within the VIS-NIR spectral region to be diagnostic features for surface water identification. However, the presence of these features depends on the spectral superimposition of water constituents and bottom coverage. This aspect has been considered in the development of a knowledge-based classifier. The results (probability of detection generally lies above 90%) indicate the great potential of the developed algorithm for surface water body detection and delineation within urban, rural and coastal scenes.

Ignoring small-scale heterogeneities in Arctic land cover may bias estimates of water, heat and carbon fluxes in large-scale climate and ecosystem models. We investigated subpixel-scale heterogeneity in CHRIS/PROBA and Landsat-7 ETM+ satellite imagery over ice-wedge polygonal tundra in the Lena Delta of Siberia, and the associated implications for evapotranspiration (ET) estimation. Field measurements were combined with aerial and satellite data to link fine-scale (0.3m resolution) with coarse-scale (upto 30m resolution) land cover data. A large portion of the total wet tundra (80%) and water body area (30%) appeared in the form of patches less than 0.1 ha in size, which could not be resolved with satellite data. Wet tundra and small water bodies represented about half of the total ET in summer. Their contribution was reduced to 20% in fall, during which ET rates from dry tundra were highest instead. Inclusion of subpixel-scale water bodies increased the total water surface area of the Lena Delta from 13% to 20%. The actual land/water proportions within each composite satellite pixel was best captured with Landsat data using a statistical downscaling approach, which is recommended for reliable large-scale modelling of water, heat and carbon exchange from permafrost landscapes. Keywords: permafrost; remote sensing; Arctic; wetlands; patterned ground; latent heat fluxes (Published: 9 March 2012) Citation: Tellus B 2012, 64, 17301, DOI: 10.3402/tellusb.v64i0.17301

This article presents and technically describes a new field spectro-goniometer system for the ground-based characterization of the surface reflectance anisotropy under natural illumination conditions developed at the Alfred Wegener Institute (AWI). The spectro-goniometer consists of a Manual Transportable Instrument platform for ground-based Spectro-directional observations (ManTIS), and a hyperspectral sensor system. The presented measurement strategy shows that the AWI ManTIS field spectro-goniometer can deliver high quality hemispherical conical reflectance factor (HCRF) measurements with a pointing accuracy of ±6 cm within the constant observation center. The sampling of a ManTIS hemisphere (up to 30° viewing zenith, 360° viewing azimuth) needs approx. 18 min. The developed data processing chain in combination with the software used for the semi-automatic control provides a reliable method to reduce temporal effects during the measurements. The presented visualization and analysis approaches of the HCRF data of an Arctic low growing vegetation showcase prove the high quality of spectro-goniometer measurements. The patented low-cost and lightweight ManTIS instrument platform can be customized for various research needs and is available for purchase.