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During the RU-Land_2021_Yakutia summer field campaign in August and September 2021 in the Verkhoyansk Mountain Range in Eastern Yakutia and in the Central Yakutian Lowland, multispectral drone-based images were acquired over 53 selected lakes to analyse the vegetation and shallow lake waters along shores and to record the current lake shorelines. The images were taken in the course of further investigations of the lakes during that summer expedition. Baisheva et al. (2022) gives an overview of the lakes studied and the corresponding hydrochemistry. In addition, we published datasets including water isotope data of the lake (Stieg et al. 2022) and vegetation surveys of the lakeshores (Stieg et al. 2022). The dataset with the corresponding processed lake images, the so-called orthomosaics, can be found here: https://doi.pangaea.de/10.1594/PANGAEA.956223. Here we provide the event list, which gives an overview of the relevant lake information. Due to the varying lake sizes, only sections of the shore were recorded for some lakes (see information on orthomosaic quality). Some orthomosaics contain several lakes because the lakes are small and are located close to each other. This is especially the case for the thermokarst lakes in the Central Yakutian lowland. Occasionally, there are multiple orthomosaics (indicated with _1 and _2) because either different sections of the shore have been recorded or they were acquired on different days. The lake sizes were calculated from the processed orthomosaics. For fragmented orthomosaics, additionally, Sentinel-2 satellite data was used to calculate the lake area provided in the metadata. All data were collected and processed by scientists from the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Germany, the University of Potsdam, Germany, Technische Universität Berlin (TUB), Germany and the North-Eastern Federal University of Yakutsk (NEFU), Russia.

The data is from a mesocosm experiment set up outside Lima, Peru to study the influence of upwelling of oxygen minimum zone (OMZ) water.The mesocosm bags were 2 m in diameter and extended from the surface down to 19 m depth, where the last 2 m was a conical sediment trap. Eight mesocosm bags were used and they were moored at 12.0555°S; 77.2348°W just north of Isla San Lorenzo where the water depth is ~30 m. The experiment was started 25 February 2017 by closing the mesocosm bags and were run for 50 days.Two treatments were used (water with different OMZ signature), each with four replicates. Water (100 m3) from the OMZ was collected from two locations and depths. The first was collected from 12.028323°S; 77.223603°W from 30 m depth, and the second one from 12.044333°S; 77.377583°W from 70 m depth. The original aim was to collect severe and moderate OMZ signature water (differing in e.g. nitrate concentrations) from the first and second site, respectively. This assumption was based on long-term monitoring data, however, the chemical properties (e.g. nitrate concentration) was more similar in these water masses than anticipated, rather reflecting low and very low OMZ signatures from site 1 and 2 respectively.To have a baseline of measured variables, the mesocosms where closed and environmental and biological variables were determined over 10 days. After this period, the OMZ water was added to the mesocosms in two steps on day 11 and 12 after the enclosure of the mesocosms. As the mesocosms contain a specific volume (~54 m3), the process of adding the OMZ water started with first removing water from the mesocosms. The water removed (~20 m3) was pumped out from 11-12 m depth. A similar volume of OMZ water, from both collection sites, was then pumped into four replicate mesocosms each. The OMZ water was pumped into the mesocosms moving the input hose between 14-17 m depth. The water collected at 30 m depth was pumped into mesocosms M1, M4, M5 and M8 having a low OMZ signature and water from 70 m depth into mesocosms M2, M3, M6 and M7 having a very low OMZ signature. Due a halocline at 12 m depth (see below), the added OMZ water was not immediately mixed throughout the mesocosm bag.Sampling took place every second day over a period of 50 days, and all variables were taken with an integrated water sampler (HydroBios, IWS) pre-programed to fill from 0 – 10 m depth and all samples consisted of this integrated samples from the upper 10 m. The samples were stored dark in cool boxes and brought back to the laboratory and processed right away. Sampling took place in the morning, and the samples were usually back in the laboratory around noon.Measured variables included inorganic nutrients, dissolved organic nutrients, extracellular enzyme activity: leucine aminopeptidase (LAP) and alkaline phosphatase activity (APA), and the phytoplankton and bacterial community composition. Bacteria are given in percent of total operational taxonomic unit.

Temperature and heating-induced temperature were measured along a chain of thermistors. Digital Thermistor Chain DTC33 is an autonomous instrument that was installed on drifting sea ice in the Arctic Ocean during the MOSAiC expedition on 22 November 2020. The thermistor chain was 5.12 m long and included sensors with a regular spacing of 2 cm. The resulting time series describes the evolution of temperature during the heating cycle of 20 s and after the heating cycle during the following 40 s as a function of geographic position (GPS), depth, and time between 22 November 2019 and 15 July 2020 in sample intervals of 6 hours. It also contains manually estimated positions of air-snow, snow-ice, and ice-water interfaces. The DTC was installed in undeformed second-year ice at Transect North: https://doi.org/10.1525/elementa.2022.00048. Radiation station 2020R14 was installed next to the DTC33: doi:10.1594/PANGAEA.948572. Temperature after the cooling cycle and temperature before the heating cycle both represent in situ temperature. The temperature before the heating cycle may contain errors in measurements and is provided for reference. It is recommended to use temperature after the cooling cycle and temperature difference after the heating cycle for further analysis.

This dataset contains CCN concentrations at five supersaturation levels, averaged to 1 min time resolution, measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using the model CCN-100 from Droplet Measurement Technologies (DMT, Boulder, USA). Detailed description of the measurement principle can be found in e.g. Roberts & Nenes (2005). The instrument was located behind an automated valve, which switched hourly between a total and an interstitial air inlet, with upper cutoff sizes of 40 and 1 µm respectively (Heutte et al., Submitted; Beck et al., 2022; Dada et al., 2022). The measurements were performed in 1-h cycles, with a 0.5 L/min sample flow and a 2 L/min make up flow, where the supersaturations 0.15, 0.2, 0.3, 0.5 and 1.0 % were measured. The supersaturation of 0.15 % is measured for 20 min, as it takes longer to equilibrate, and the remaining supersaturations were measured for 10 min each. The instrument was calibrated in July 2019 before the campaign, and in March and April 2020 during the campaign. Based on the inter-variability of the calculated supersaturation levels during these calibrations, we can expect values ranging from 0.15-0.20, 0.20-0.25, 0.29-0.33, 0.43-0.5, 0.78-1.0 % for the nominal supersaturations of 0.15, 0.2, 0.3, 0.5 and 1.0 %, respectively. The counting error for the CCNC is associated with the error in the optical counting of particles and is about 10 %. Data were removed during the cooling cycle (i.e., the time when the measurement cycle starts again and the temperature is cooled to set the lowest supersaturation), which corresponds roughly to the first 10 min of each hour (so 50 % of the 0.15 % supersaturation period). Additionally, the first minute of the transition between supersaturations was removed before averaging the data to 1 min time resolution. During some time periods, a difference pattern of mean and standard deviation of the measurements between even and odd hours was observed, most probably caused by a persistent pressure drop in the inlet lines, resulting in a proportional reduction of the concentration measurements. For correction, the 1-h arithmetic mean of interstitial inlet measurements and the mean of the two adjacent hours of total inlet measurements were subtracted, and the resulting difference was added as a constant to the data points of the interstitial inlet measurements. The dataset contains a pollution mask for local pollution (predominantly exhaust from the Research Vessel Polarstern) with 0 indicating clean, and 1 indicating polluted periods (Beck et al., 2022; Beck et al., 2022).

The records include the processed data from mooring AK3. Current velocities were quality-controlled based on thresholds defined for a variety of parameters. Data points meeting any of the following criteria were discarded: error velocities >10 cm/s, beam correlation <64%, percent-of-good <50%, pitch/roll >20°. Bins with >30% of discarded data points were removed entirely. Velocity flags indicate the evaluated quality of the data point (flag=0: good, flag=1: discarded; flag=2: enhanced error velocity (3-10 cm s-1) and or pitch/roll of 10-20°. Velocities were corrected for magnetic declination. The pressure-values provide the actual CTD pressure readings, depth-values provide the nominal instrument depth. Temperature and salinity flags indicate interpolated gaps in the time series. For more details, please refer to Ruiz-Castillo et al. (Structure and seasonal variability of the Arctic Boundary Current north of Severnaya Zemlya. Journal of Geophysical Research-Ocean, under review).The authors are grateful to the captains, crews and technical/scientific staff of the expeditions. Many individuals have contributed to the conception of the research, the preparation of the instruments, the deployment and recoveries, as well as to the retrieval of the data, which we greatly acknowledge. Time series data of physical oceanography (seawater conductivity, temperature, pressure, salinity) and ocean current velocities were obtained from mooring AK3 in the eastern Arctic Ocean north of Severnaya Zemlya (81.962 °N, 94.543 °E, water depth 1453 m) in 2015 - 2018. The mooring was deployed during Akademik Tryoshnikov expedition AT2015 as part of the NSF-funded NABOS (Nansen and Amundsen Basins Observational System) - program and recovered during AT2018, which was jointly organized between NABOS and the German BMBF-funded CATS (Changing Arctic Transpolar System)-project. The attached archive contains processed current velocities and hydrographic data recorded with Seabird SBE37 microcats, RDI Acoustic Doppler Current profilers and Aanderaa point current meters. Details on data processing can be found in the file description and in Ruiz-Castillo et al. (2022). Instruments types and serial numbers can be found in the attached document.

Peat cores were taken in late August, 2016, with a box-shaped 65 mm x 37 mm peat corer, except in the wet TP site where a 60 mm x 60 mm corer was used. Roots were manually separated and visually identified. Drying temperature for roots was 40 °C

This dataset contains particle number size distributions between 1.06-16.1 μm (aerodynamic diameter) and total concentration averaged to 1 min time resolution, measured with a commercial Aerodynamic Particle Sizer spectrometer (APS model 3321, TSI Incorporated, Minnesota, USA) during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern.

Time series data of physical oceanography (seawater conductivity, temperature, pressure, salinity) and ocean current velocities were obtained from mooring AK7 in the eastern Arctic Ocean north of Severnaya Zemlya (82.586 °N, 95.50 °E, water depth 3019 m) in 2015 - 2018. The mooring was deployed during Akademik Tryoshnikov expedition AT2015 as part of the NSF-funded NABOS (Nansen and Amundsen Basins Observational System) - program and recovered during AT2018, which was jointly organized between NABOS and the German BMBF-funded CATS (Changing Arctic Transpolar System)-project. The attached archive contains processed current velocities and hydrographic data recorded with Seabird SBE37 microcats, RDI Acoustic Doppler Current profilers and Aanderaa point current meters. Details on data processing can be found in Ruiz-Castillo et al. (2022). Instruments types and serial numbers can be found in the attached document. The records include the processed data from mooring AK7. For details on processing and scientific content, please refer to Ruiz-Castillo, E., Janout, M., Hölemann, J., Kanzow, T., Schulz, K., Ivanov, V., Structure and seasonal variability of the Arctic Boundary Current north of Severnaya Zemlya. Journal of Geophysical Research-Ocean, under review.The authors are grateful to the captains, crews and technical/scientific staff of the expeditions. Many individuals have contributed to the conception of the research, the preparation of the instruments, the deployment and recoveries, as well as to the retrieval of the data, which we greatly acknowledge.

These datasets contain the total particle number concentrations and normalized size distributions (dN/dlogDp) of excited, fluorescent, and hyper-fluorescent particles of sizes 0.5 to 20 μm (optical diameter). The normalized size distribution datasets are split into 20 size bins: 0.5 - 0.6 μm, 0.6 - 0.72 μm, 0.72 - 0.87 μm, 0.87 - 1.05 μm, 1.05 - 1.26 μm, 1.26 - 1.51 μm, 1.51 - 1.82 μm, 1.82 - 2.19 μm, 2.19 - 2.63 μm, 2.63 - 3.16 μm, 3.16 - 3.8 μm, 3.8 - 4.57 μm, 4.57 - 5.5 μm, 5.5 - 6.61 μm, 6.61 - 7.95 μm, 7.95 - 9.56 μm, 9.56 - 11.50 μm, 11.5 - 13.83 μm, 13.83- 16.63 μm and 16.63 - 20 μm. The data were measured by a WIBS-NEO (Wideband Integrated Bioaerosol Sensor, model New Electronics option) by droplet measurement techniques ltd. The data were processed using the IGOR WIBS toolkit V1.36 (DMT) and python version 3.9.7. These datasets have been averaged to 1 hour time resolution. The datasets were cleaned from local pollution sources by applying a pollution flag developed by Beck et al. (2022a,b), which is based on the rate of change in particle number concentration with 1 min time resolution. Data points with more than 10 polluted minutes within an hour were removed from the WIBS datasets. Time periods with zero filter measurements and time periods with unstable flow that affected number concentrations have been removed from the dataset. The WIBS measures the size, asymmetry and fluorescence of particles with an optical diameter of 0.5 – 20 µm. Detected particles are excited by two UV flashlamps at wavelengths of 280 and 370 nm and their emitted fluorescence is measured by two photomultipliers with bandwidths of 310 - 400 nm, and 420 - 650 nm. The WIBS counts excited particles at a maximum frequency of 125 Hz, which corresponds to a maximum concentration of 2.5*104 particles/L with a sample flow of 0.3 L/min. Excited particles were classified as fluorescent if their fluorescent intensity exceeded the background intensity by three standard deviations (3σ) and as hyper-fluorescent if the fluorescent intensity exceeded the background intensity by 9σ. Excited particles with a lower fluorescent intensity were considered to be non-fluorescent. The background fluorescence was determined by measuring the fluorescent signal in the measurement chamber in absence of particles. Background measurements were performed every 26 h. The combination of two excitation wavelengths and two detector wavebands allows the classification of fluorescent particles into seven types: A, B, C, AB, AC, BC, and ABC (Perring et al. (2015); Savage et al. (2017)). For further information about the instrumental setup, refer to Heutte et al. (Submitted).