ALBERT

Description: Abstract

Description: In coastal Arctic permafrost regions, thermokarst lagoons represent the transition state from a freshwater lacustrine to a marine environment, and receive little attention regarding their role for greenhouse gas production and release. The geochemical features of a thermokarst lagoon were compared with two thermokarst lakes on the Bykovsky Peninsula in northeastern Siberia. This data set includes pH, major cations and anions, alkalinity, salinity, and dissolved iron (ferric and ferrous) concentrations from porewater of lake and lagoon sediments; the concentration and stable isotopic signature of CH4 in small plug samples from the sediment cores; total carbon (TC), total organic carbon (TOC), total nitrogen (TN), and total sulfur (TS) measured from the bulk sediment; and several biomarker indices (e.g. CPI, Paq) were calculated based on n-alkane concentrations to characterize the origin of organic matter (OM) in the lakes.

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: Data file contains bore hole temperature measurements for Uomullyakh and Polar Fox lagoons carried out in April 2017 as well as porewater conductivity measurements carried out in the Laboratory. GeoPrecision temperature chains (accuracy of 0.1 °C and a resolution of 0.01 °C) remained in the borehole for 5 days at Polar Fox Lagoon and 11 days at Uomullyakh Lagoon. To account for drilling heat effects, the observed temperature drift for each thermistor was analysed following Lachenbruch (1982). For the calculation of freezing points the electrical conductivity of the porewater (referenced to 25 °C) was converted to molality (mol/kg) using the TEOS package in MATLAB (McDougall and Barker, 2010).

Description: The dataset presents the radiocarbon ages from samples from sediment cores PG2410 (Uomullyakh Lagoon) and PG2411 (Polar Fox Lagoon). Radiocarbon dates were calibrated using Calib 7.04 software after Reimer et al. (2013) and the IntCal13 calibration curve (Stuiver et al. 2020). Ages are given in 1000 years (ka).

Description: This dataset contains results of optically stimulated luminescence (OSL) dating for samples from sediment cores PG2410 (Uomullyakh Lagoon), PG2411 (Polar Fox Lagoon) and the neighbouring PG2412 (Goltsovoye Lake). Measurements were carried out at Aarhus University's Nordic Laboratory for Luminescence Dating (Roskilde, Denmark).

Description: Current warming, sea-level rise, coastal erosion and accelerated permafrost thaw is leading to increasing thermokarst lagoon formation along wide parts of the arctic coast. Entering seawater affects the temperature and salinity of former thermokarst lake taliks during their transition to the marine environment. Therefore, thermokarst lagoon formation is an important step in the process of mobilizing terrestrial permafrost carbon pools along rapidly changing Arctic coasts. This dataset presents results of sediment analyses (ice/water content, grain-size, bulk density, magnetic susceptibility), biogeochemical analyses (TC, TOC, TN, TOC/TN, d13C, d15N), pore water analyses (pH, electrical conductivity, DOC, stable water isotopes), freezing point calculations and radiocarbon dating of two sediment cores (〉 30m long). The cores were taken at Uomullyakh Lagoon (PG2410) and Polar Fox Lagoon (PG2411) located at the Bykovsky Peninsula in April 2017.

Description: An important outcome of Arctic Coastal Dynamics I was the segmentation and characterization of the entire circum-Arctic coastline by regional experts which is presented in this dataset. This dataset contains data on coastal morphology, composition, dominant processes, ground ice, and environmental forcing parameters such as wind speed, storm counts, melt season, and wave energy. A listing of the variables included in the coastal classification can be found in Appendix A of the ACD II Science and Implementation Plan (2006). This information is available for over 800 segments, covering the coastline of all eight regional seas of the Arctic Ocean. The length of individual segments is variable (median length is 38 km), and depends on classification parameters and data availability. The segmentation format is scalable, allowing the adoption of future digital coastlines and the integration of additional data at higher spatial resolution. An assessment of the data quality for the more important quantitative variables has just been completed and the data will be publicly released on an internet map server (IMS). The goal of the IMS will be to allow individual users to prepare their own maps displaying the region and variables of interest. The ACD Classification was conceived as a broad enough framework to encompass existing classification schemes while capturing fundamental information for the assessment of climate change impacts and coastal processes. The implementation of the classification was done by so-called "regional experts", who, based on digital and paper products and personal knowledge provided information which was subsequently gathered into a circum-Arctic coastal database. The classification was primarily geomorphological in nature and considered: (1) the shape or form of the subaerial part of the coastal tract, (2) the marine processes acting upon the coast, (3) the shape or the form of the subaqueous part of the coastal tract and (4) the lithofacies of the materials constituting the coastal zone The beta version of the classification is made of 1331 segments each characterized by a series of geomorphological quantitative and qualitative variables. The classification is stored as an ISO 19115-compliant personal geodatabase and is therefore mappable in off-the-shelf Geographical Information Systems (GIS)

Description: This data set contains a first‐order estimate of distribution, thickness and ice-content of submarine permafrost on the Arctic shelf based on a numerical heat transfer model. Our model uses dynamic upper boundary conditions that synthesize Earth System Model air temperature, ice mass distribution and thickness, and global sea level reconstruction and applies globally distributed geothermal heat flux as a lower boundary condition. Sea level reconstruction accounts for differences between marine and terrestrial sedimentation history. Sediment composition and pore water salinity are integrated in the model. Model runs for 450 ka for cross‐shelf transects were used to initialize the model for circumarctic modeling for the past 50 ka.This data set consists of current sea levels, and permafrost depth [m below sea floor(m bsf)], total ice-content [m³ / m²] and enthalpy [MJ / m²] at times 50ka, 25ka and 0a before industrialization for 15892 locations on the Arctic shelf. Additionally zonations for permafrost depth and ice-content are given as layer files. Based on the undertaken sensitivity studies zones with 〈100m permafrost are uncertain, zones with 100-300m are probable, and zones with 〉300m are confident.