Description: The data was collected with an IRIS Syscal Pro Deep Marine resistivity system that was equipped with a GPS and an echo-sounder to record water depths. The geoelectric cable had an electrode separation of 10 m and the electrodes were arranged in a reciprocal Wenner Schlumberger array. The offset between the first electrode and the boat was approximately 10 m.

Description: The data was collected with an IRIS Syscal Pro Deep Marine resistivity system that was equipped with a GPS and an echo-sounder to record water depths. The geoelectric cable had an electrode separation of 10 m and the electrodes were arranged in a reciprocal Wenner Schlumberger array. The offset between the first electrode and the boat was approximately 10 m.

Description: The data was collected with an IRIS Syscal Pro Deep Marine resistivity system that was equipped with a GPS and an echo-sounder to record water depths. The geoelectric cable had an electrode separation of 10 m and the electrodes were arranged in a reciprocal Wenner Schlumberger array. The offset between the first electrode and the boat was approximately 10 m.

Description: The data was collected with an IRIS Syscal Pro Deep Marine resistivity system that was equipped with a GPS and an echo-sounder to record water depths. The geoelectric cable had an electrode separation of 10 m and the electrodes were arranged in a reciprocal Wenner Schlumberger array. The offset between the first electrode and the boat was approximately 10 m.

Description: The data was collected with an IRIS Syscal Pro Deep Marine resistivity system that was equipped with a GPS and an echo-sounder to record water depths. The geoelectric cable had an electrode separation of 10 m and the electrodes were arranged in a reciprocal Wenner Schlumberger array. The offset between the first electrode and the boat was approximately 10 m.

Description: In July 2017, we collected apparent resistivity data (ohm-m) in a sub-aquatic permafrost environment on the southern coastline of the Bykovsky Peninsula in northeast Siberia. The project goal was to determine the depth to the top of frozen sediment for multiple submerged landscapes. The submerged landscapes included ice-rich Yedoma permafrost, permafrost that had undergone prior thermokarst (Alases), and a former lagoon (i.e. offshore at the lagoon's coastline positions in earlier years). The data was collected with an IRIS Syscal Pro Deep Marine resistivity system that was equipped with a GPS and an echo-sounder to record water depths. The geoelectric cable had an electrode separation of 10 m and the electrodes were arranged in a reciprocal Wenner Schlumberger array. The offset between the first electrode and the boat was approximately 10 m.

Description: We present results of analyses on a sediment core from Lake Karakul, located in the eastern Pamir Mountains, Tajikistan. The core spans the last ~29 cal ka. We investigated and assessed processes internal and external to the lake to infer changes in past moisture availability. Among the variables used to infer lake-external processes, high values of grain-size end-member (EM) 3 (wide grain-size distribution that reflects fluvial input) and high Sr/Rb and Zr/Rb ratios (coinciding with coarse grain sizes), are indicative of moister conditions. High values in EM1, EM2 (peaks of small grain sizes that reflect long-distance dust transport or fine, glacially derived clastic input) and TiO 2 (terrigenous input) are thought to reflect greater influence of dry air masses, most likely of Westerly origin. High input of dust from distant sources, beginning before the Last Glacial Maximum (LGM) and continuing to the late glacial, reflects the influence of dry Westerlies, whereas peaks in fluvial input suggest increased moisture availability. The early to early-middle Holocene is characterised by coarse mean grain sizes, indicating constant, high fluvial input and moister conditions in the region. A steady increase in terrigenous dust and a decrease in fluvial input from 6.6 cal ka BP onwards points to the Westerlies as the predominant atmospheric circulation through to present, and marks a return to drier and even arid conditions in the area. Proxies for productivity (TOC, TOC/TN, TOC Br ), redox potential (Fe/Mn) and changes in the endogenic carbonate precipitation (TIC, d18 O) indicate changes within the lake. Low productivity characterised the lake from the late Pleistocene until 6.6 cal ka BP, but productivity increased rapidly afterwards. Lake level remained low until the LGM, but water depth increased to a maximum during the late glacial and remained high into the early Holocene. Subsequently, the water level decreased to its present stage. Today the lake system is mainly climatically controlled, but the depositional regime is also driven by internal limnogeological processes.

Description: Arctic permafrost landscapes are among the most vulnerable and dynamic landscapes globally, but due to their extent and remoteness most of the landscape changes remain unnoticed. In order to detect disturbances in these areas we developed an automated processing chain for the calculation and analysis of robust trends of key land surface indicators based on the full record of available Landsat TM, ETM +, and OLI data. The methodology was applied to the ~ 29,000 km**2 Lena Delta in Northeast Siberia, where robust trend parameters (slope, confidence intervals of the slope, and intercept) were calculated for Tasseled Cap Greenness, Wetness and Brightness, NDVI, and NDWI, and NDMI based on 204 Landsat scenes for the observation period between 1999 and 2014. The resulting datasets revealed regional greening trends within the Lena Delta with several localized hot-spots of change, particularly in the vicinity of the main river channels. With a 30-m spatial resolution various permafrost-thaw related processes and disturbances, such as thermokarst lake expansion and drainage, fluvial erosion, and coastal changes were detected within the Lena Delta region, many of which have not been noticed or described before. Such hotspots of permafrost change exhibit significantly different trend parameters compared to non-disturbed areas. The processed dataset, which is made freely available through the data archive PANGAEA, will be a useful resource for further process specific analysis by researchers and land managers. With the high level of automation and the use of the freely available Landsat archive data, the workflow is scalable and transferrable to other regions, which should enable the comparison of land surface changes in different permafrost affected regions and help to understand and quantify permafrost landscape dynamics.

Description: Lakes are a ubiquitous landscape feature in northern permafrost regions. They have a strong impact on carbon, energy and water fluxes and can be quite responsive to climate change. The monitoring of lake change in northern high latitudes, at a sufficiently accurate spatial and temporal resolution, is crucial for understanding the underlying processes driving lake change. To date, lake change studies in permafrost regions were based on a variety of different sources, image acquisition periods and single snapshots, and localized analysis, which hinders the comparison of different regions. Here we present, a methodology based on machine-learning based classification of robust trends of multi-spectral indices of Landsat data (TM,ETM+, OLI) and object-based lake detection, to analyze and compare the individual, local and regional lake dynamics of four different study sites (Alaska North Slope, Western Alaska, Central Yakutia, Kolyma Lowland) in the northern permafrost zone from 1999 to 2014. Regional patterns of lake area change on the Alaska North Slope (-0.69%), Western Alaska (-2.82%), and Kolyma Lowland (-0.51%) largely include increases due to thermokarst lake expansion, but more dominant lake area losses due to catastrophic lake drainage events. In contrast, Central Yakutia showed a remarkable increase in lake area of 48.48%, likely resulting from warmer and wetter climate conditions over the latter half of the study period. Within all study regions, variability in lake dynamics was associated with differences in permafrost characteristics, landscape position (i.e. upland vs. lowland), and surface geology. With the global availability of Landsat data and a consistent methodology for processing the input data derived from robust trends of multi-spectral indices, we demonstrate a transferability, scalability and consistency of lake change analysis within the northern permafrost region.