ALBERT

Description: Temperature and heating-induced temperature differences were measured along a chain of thermistors. SIMBA 2019T47 (a.k.a. FMI_04_06, IRIDIUM number 300234064817930) is an autonomous instrument that was installed on drifting sea ice in the Arctic Ocean during the 1st leg of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) in October 2019. The buoy was deployed at a P site with initial thicknesses of snow and ice of 0.10 and 0.34 m, respectively, on 13 October 2019. The thermistor chain was 5 m long and included 240 sensors with a regular spacing of 2 cm. The depths for the sensors are 78 to -400 cm, referring to the initial interface between snow and ice. The resulting time series describes the evolution of temperature and temperature differences after two heating cycles of 30 and 120 s as a function of depth and time between 13 October 2019 and 8 February 2020 in sample intervals of 6 hours for temperature and 24 hours for temperature differences. In addition to temperature, geographic position were measured.

Description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environment temperature SIMBA-ET and temperature change around the thermistors after a weak heating applied to each sensor (SIMBA-HT). Totally, there were 22 SIMBAs deployed in the Arcitic Ocean over the Distributed Network (DN) and the Central Observatory during the Legs 1a, 1 and 3 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign. The SIMBA thermistor chain is 5.12 m long, and equipped with 256 thermistors (Maxim Integrated DS28EA00) at 0.02 m spacing. Based on a manual identification method, the SIMBA-ET and SIMBA-HT were processed to yield snow depth and ice thickness. Here, we combined the two optimal methods (the ET vertical gradient and HT rise ratio) to reduce the uncertainty. To keep the consistency, we use the snow or ice surface, consequentially the snow depth, determined by the ET vertical gradient. The formations of snow ice and superposed ice are not considered in this data set. That is to say, the value of snow depth includes the layers of snow ice at two sites (2019T56 and 2019T72). The superposed ice was generally negligible. We used the HT rise ratio to determine the ice-water interface, consequentially the ice thickness. Overall, the measurement accuracy was 0.02 m for both the snow depth and ice thickness. After the snow cover melted over, the negative values for the snow depth indicate the onset of ice surface melt. The submitted data package include 19 data files (for each buoy) and 1 buoy information file.

Description: The Paleocene-Eocene Thermal Maximum (PETM) is the most studied global warming event of a series of Paleocene-Eocene carbon cycle perturbations called hyperthermals. PETM origins have been associated with volcanic-related carbon emissions; however, other carbon cycle feedbacks were required to develop a large hyperthermal such as the PETM. The orbital configuration in which the PETM occurred is still unclear despite possible orbital controls on the PETM triggering. This dataset contains X-Ray Fluorescence (XRF) data (Fe, Ca, and Si) from Contessa Road (Italy), a sedimentary section with reduced calcium carbonate dissolution compared to deep ocean sites. Astrochronological age models and probabilistic assessments reveal that the PETM onset appeared close to both short and long eccentricity maxima, which suggests that orbitally controlled insolation variations may have thermally destabilized carbon reservoirs that worked as PETM positive carbon cycle feedbacks.

Description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environment temperature SIMBA-ET and temperature change around the thermistors after a weak heating applied to each sensor (SIMBA-HT). Totally, there were 22 SIMBAs deployed in the Arcitic Ocean over the Distributed Network (DN) and the Central Observatory during the Legs 1a, 1 and 3 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign. The SIMBA thermistor chain is 5.12 m long, and equipped with 256 thermistors (Maxim Integrated DS28EA00) at 0.02 m spacing. Based on a manual identification method, the SIMBA-ET and SIMBA-HT were processed to yield snow depth and ice thickness. Here, we combined the two optimal methods (the ET vertical gradient and HT rise ratio) to reduce the uncertainty. To keep the consistency, we use the snow or ice surface, consequentially the snow depth, determined by the ET vertical gradient. The formations of snow ice and superposed ice are not considered in this data set. That is to say, the value of snow depth includes the layers of snow ice at two sites (2019T56 and 2019T72). The superposed ice was generally negligible. We used the HT rise ratio to determine the ice-water interface, consequentially the ice thickness. Overall, the measurement accuracy was 0.02 m for both the snow depth and ice thickness. After the snow cover melted over, the negative values for the snow depth indicate the onset of ice surface melt.

Description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environment temperature SIMBA-ET and temperature change around the thermistors after a weak heating applied to each sensor (SIMBA-HT). Totally, there were 22 SIMBAs deployed in the Arcitic Ocean over the Distributed Network (DN) and the Central Observatory during the Legs 1a, 1 and 3 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign. This table contains buoy information, including the name of buoy archived in https://www.meereisportal.de/, the original names, the iridium number, deployment date, location, and site, as well as some joint deployments.

Description: During the MOSAIC expedition, we deployed in-ice light measuring buoys, lightharp, and lightchains into the ice to investigate light partitioning and irradiance at different layers and depths in sea ice. The dataset presented here contains processed data from both instrument systems, containing derived optical properties, PAR data, and auxiliary data for each deployment site. Auxiliary data gives information on the position, snow, and ice thickness statistics, and surface melt that changes the relative vertical position of the measurements. Auxiliary data was retrieved from SIMBA buoys deployed in the vicinity of the optical instruments. All data are provided in NetCDF format. The dataset includes processed data from the lightharp and three light chains (one redeployed on Leg5) from MOSAiC. The instruments were deployed at four different sites during MOSAiC: LM site (SYI dark coring site), L3 site, Pond site on Leg5 and within the Central Observatory (CO). The first part of the filenames reflects the deployment site. The second part gives the buoy name to which the optical sensors were connected and the last part the measurement period in YYMMDD. The NetCDF files were compiled using the profile_trajectory standard from CF conventions. Multiple directly measured and derived data layers are included with data coordinates depth and nominal_date. Nominal_date is the time of the uppermost valid measurement of a profile. Furthermore, files contain a set of already published auxiliary data describing the snow- and ice thickness statistics at the measurement sites (mean, max, min, and std) and a proxy for surface melt, that changes the vertical position of the frozen-in sensors. The lightharp data furthermore contains snow thickness from SIMBA buoy T62 and an individual surface melt approximation derived with temperature measurements at the optical sensors and surface melt rates. Data PIs and further helpful information is included in the attributes.

Description: This bibliography unites the individual data collected by different types of autonomous platforms deployed during MOSAiC in 2019/2020.

Description: Geographic position.

Description: Temperature profile from atmosphere through snow and ice into the ocean.

Description: Temperature rising around the thermistors after a weak heating applied to each sensor daily after 30 s.