ALBERT

Description: Remote sensing has been a tool of choice for decades for studying periglacial landscape dynamics and for scaling-up field data. Remoteness, geographic extent, and harsh climates of study areas as well as logistical challenges in visiting them make aerial or satellite imagery key components of studies focusing on mapping of landforms, vegetation and hydrologic features, or simply planning field research. For some regions, the historical aerial image record now extends back 〉80 years, allowing tremendous insights into scales and rates of land surface processes such as thermokarst lake dynamics, coastal erosion, peat plateau collapse, thaw slump development, or rock glacier movement. Such long temporal archives increasingly allow correlation of observed changes with climatic or anthropogenic disturbances. Classical remote sensing tools include panchromatic and color-infrared aerial imagery, widely available across the Arctic since the 1950s and 1970s, respectively. Stereo-photogrammetric analyses provided critical three-dimensional insights for many studies. The advent of earth surface-observing satellite sensors in the 1970s brought multi-spectral Landsat and other imagery to researchers. In the 1990s, satellite synthetic aperture radar (SAR) data became widely available. Another enormous boost in usage of remote sensing data was achieved by rendering data archives public and freely available in the 2000s, namely the full Landsat and MODIS archives. In addition, commercial, very high-resolution platforms have provided sufficient spatial resolution for detecting periglacial landscape dynamics during the last decade. The 4th International Polar Year 2007/08 also helped directing remote sensing efforts to permafrost regions, followed by international activities such as the ESA Data User Element Permafrost project, an upcoming large NASA field campaign termed the Arctic Boreal Vulnerability Experiment (ABoVE), and a recent US National Academy of Sciences workshop report on Remote Sensing of Permafrost guided by numerous international experts. New sensors, processing techniques, and analysis methods available today provide promising avenues to monitor periglacial landscapes and even permafrost directly, to support and scale field research, and to parameterize and validate modeling. Here we show some of the developments in technology and applications for periglacial environments and for observing characteristics of permafrost, including multi-temporal high-resolution imagery in the visible to infrared range for change detection studies, hemispherical-scale remote sensing datasets of the physical state of the earth surface such as freeze-thaw state, interferometric SAR for detection of seasonal or long-term surface deformation in periglacial regions, airborne geophysical sensors used to map permafrost extent and talik distribution, and high-resolution elevation data from airborne interferometric SAR, LIDAR, or stereo-optical sensors to characterize periglacial features and their deformation over time.

Description: Arctic permafrost coasts are eroding at rates similar or greater than temperate coasts and release large quantities of organic carbon and nitrogen previously stored in permafrost. Estimates of organic carbon fluxes from ice-rich permafrost coasts of the Laptev Sea, where data is scarce, differ widely with estimates varying by two orders or magnitude. Here, we used high resolution datasets on coastal erosion, cryostratigraphy, organic carbon and geomorphology from the Bykovsky Peninsula, in the southern Laptev Sea, to compute below ground organic carbon and nitrogen pools and fluxes of organic carbon from the coast for the current period and the next hundred years. Frozen deposits of the peninsula contain 141.6 Tg of organic carbon, a number 27% lower than what it would contain if the surface had not been affected by permafrost thaw in the past. An additional 44.0 Tg of organic carbon is contained under the peninsula below current sea level. The current fluxes of organic carbon from the peninsula are estimated at 0.058 Tg C a-1 and future fluxes at 0.067 Tg C a-1, or even at 0.085 Tg C a-1 if below sea level organic carbon stocks are included in the calculation. Extrapolation of these measurements to the entire Yedoma coast of the Laptev Sea gives an maximum annual flux of organic carbon from coastal erosion of 6.95 Tg C a-1, which ranges between the previously published minimum and maximum estimations for the same area.s

Description: Arctic permafrost coasts make up about one third of the global coastline and are likely to witness some of the most dramatic changes linked to changing environmental conditions in the 21st century. Increasing sea level, warming sea temperatures, longer open water season and increasing open-water area all bear the potential to increase the impact on sediment and nutrient pathways in the nearshore zone. In this study, we focus on a well studied location, the Bykovsky Peninsula, southern Laptev Sea, Russia to provide high resolution estimations of organic carbon release from its coastline. We build on recently published datasets from studies related to coastal geomorphology, paleogeography and oceanography, all available at large scale, to map and determine the fluxes of carbon coming from the coast throughout the second half of the twentieth century and to provide prospective numbers on the release of organic carbon in the years to come.

Description: 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.

Description: This paper evaluates the simulated Arctic land snow cover duration, snow water equivalent, snow cover fraction, surface albedo and land surface temperature in the regional climate model HIRHAM5 during 2008-2010, compared with various satellite and reanalysis data and one further regional climate model (COSMO-CLM). HIRHAM5 shows a general agreement in the spatial patterns and annual course of these variables, although distinct biases for specific regions and months are obvious. The most prominent biases occur for east Siberian deciduous forest albedo, which is overestimated in the simulation for snow covered conditions in spring. This may be caused by the simplified albedo parameterization (e.g. non-consideration of different forest types and neglecting the effect of fallen leaves and branches on snow for deciduous tree forest). The land surface temperature biases mirror the albedo biases in their spatial and temporal structures. The snow cover fraction and albedo biases can explain the simulated land surface temperature bias of ca. -3 °C over the Siberian forest area in spring.

Description: 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.

Description: Energy and water vapour fluxes are important factors for the understanding of terrestrial ecosystems. While meteorological measurements provide necessary information for selected locations, an upscaling of the fluxes requires additional information, especially for heterogeneous environments like the polygonal tundra landscape. Spaceborne Synthetic Aperture Radar (SAR) is a valuable tool as it works independent from cloud cover and sunlight. SAR data can be used to determine spatial and temporal distribution of parameters such as soil moisture, changes in vegetation, timing of snowmelt during spring, freezing of active layer during autumn, and freezing and thawing of lakes, ponds and river arms.