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Snow depth, sea ice thickness and interface temperatures derived from measurements of SIMBA buoy 2020T75
No full textThe Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environmental temperature SIMBA-ET and a temperature change around the thermistors after a weak heating is applied to each sensor (SIMBA-HT). SIMBA 2020T75 (a.k.a. PRIC_1003) is an autonomous instrument that was installed on drifting sea ice in the Arctic Ocean (Polarstern PS122 (MOSAiC) in 2019/20) as part of the project PRIC. Its thermistor chain is 5 m long, and equipped with 241 thermistors (Maxim Integrated DS28EA00) at a spacing of 2 cm. Based on a manual classification method, the SIMBA-ET and SIMBA-HT were processed to obtain snow depth and ice thickness (smoothed with a 3-day running mean), as well as the thermistor number, the vertical position Z relative to the snow-ice interface and the measured SIMBA-ET at each detected interface (atmosphere-snow, snow-ice and ice-ocean) for the period between 2020-04-23T12:30:16 and 2020-07-14T12:30:16. To do this, we combined two derivatives of measured temperatures (the ET vertical gradient and HT rise ratio) to reduce the detection uncertainty of all interfaces considered. The snow or ice surface, consequentially the snow depth, is determined by the ET vertical gradient. Potential formation of snow ice is not explicitly considered in this data set, but may occur as depicted by vertical changes of the snow-ice interface position. The ice-ocean interface is usually determined using the HT rise ratio and serves as the lower limit for ice thickness. Overall, the accumulated error is 2 to 4 times the sensor spacing for both the snow depth and ice thickness. For interface temperatures, individual sensors in the chain measure with a temperature resolution of 0.0625°C, with the overall accuracy landing in the range of ± 2°C (Jackson et al., 2013). After the snow cover has melted, negative values for snow depth may indicate the onset of ice surface melt
Snow depth, sea ice thickness and interface temperatures derived from measurements of SIMBA buoy 2019T56
No full textThe Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environmental temperature SIMBA-ET and a temperature change around the thermistors after a weak heating is applied to each sensor (SIMBA-HT). SIMBA 2019T56 (a.k.a. FMI05-06) is an autonomous instrument that was installed on drifting sea ice in the Central Arctic Ocean (Polarstern PS122 (MOSAiC) in 2019/20) as part of the project FMI. Its thermistor chain is 5 m long, and equipped with 241 thermistors (Maxim Integrated DS28EA00) at a spacing of 2 cm. Based on a manual classification method, the SIMBA-ET and SIMBA-HT were processed to obtain snow depth and ice thickness (smoothed with a 3-day running mean), as well as the thermistor number, the vertical position Z relative to the snow-ice interface and the measured SIMBA-ET at each detected interface (atmosphere-snow, snow-ice and ice-ocean) for the period between 2019-11-02T01:44:49 and 2020-06-27T19:00:13. To do this, we combined two derivatives of measured temperatures (the ET vertical gradient and HT rise ratio) to reduce the detection uncertainty of all interfaces considered. The snow or ice surface, consequentially the snow depth, is determined by the ET vertical gradient. Potential formation of snow ice is not explicitly considered in this data set, but may occur as depicted by vertical changes of the snow-ice interface position. The ice-ocean interface is usually determined using the HT rise ratio and serves as the lower limit for ice thickness. Overall, the accumulated error is 2 to 4 times the sensor spacing for both the snow depth and ice thickness. For interface temperatures, individual sensors in the chain measure with a temperature resolution of 0.0625°C, with the overall accuracy landing in the range of ± 2°C (Jackson et al., 2013). After the snow cover has melted, negative values for snow depth may indicate the onset of ice surface melt
Snow depth, sea ice thickness and interface temperatures derived from measurements of SIMBA buoy 2016T44
No full textThe Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environmental temperature SIMBA-ET and a temperature change around the thermistors after a weak heating is applied to each sensor (SIMBA-HT). SIMBA 2016T44 (a.k.a. FMI_05) is an autonomous instrument that was installed on drifting sea ice in the Arctic Ocean (Polarstern PS101 (ARK30/3, KarasikSeamount) in 2016) as part of the project FMI. Its thermistor chain is 5 m long, and equipped with 240 thermistors (Maxim Integrated DS28EA00) at a spacing of 2 cm. Based on a manual classification method, the SIMBA-ET and SIMBA-HT were processed to obtain snow depth and ice thickness (smoothed with a 3-day running mean), as well as the thermistor number, the vertical position Z relative to the snow-ice interface and the measured SIMBA-ET at each detected interface (atmosphere-snow, snow-ice and ice-ocean) for the period between 2016-09-17T07:45:41 and 2016-10-22T01:51:20. To do this, we combined two derivatives of measured temperatures (the ET vertical gradient and HT rise ratio) to reduce the detection uncertainty of all interfaces considered. The snow or ice surface, consequentially the snow depth, is determined by the ET vertical gradient. Potential formation of snow ice is not explicitly considered in this data set, but may occur as depicted by vertical changes of the snow-ice interface position. The ice-ocean interface is usually determined using the HT rise ratio and serves as the lower limit for ice thickness. Overall, the accumulated error is 2 to 4 times the sensor spacing for both the snow depth and ice thickness. For interface temperatures, individual sensors in the chain measure with a temperature resolution of 0.0625°C, with the overall accuracy landing in the range of ± 2°C (Jackson et al., 2013). After the snow cover has melted, negative values for snow depth may indicate the onset of ice surface melt
Snow depth, sea ice thickness and interface temperatures derived from measurements of SIMBA buoy 2014T8
No full textThe Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environmental temperature SIMBA-ET and a temperature change around the thermistors after a weak heating is applied to each sensor (SIMBA-HT). SIMBA 2014T8 (a.k.a. Awi_41) is an autonomous instrument that was installed on drifting sea ice in the Antarctic Ocean (Polarstern PS82 (ANT29/9, FOS) in 2013/14) as part of the project Sea Ice Physics @ AWI (AWI_SeaIce). Its thermistor chain is 5 m long, and equipped with 240 thermistors (Maxim Integrated DS28EA00) at a spacing of 2 cm. Based on a manual classification method, the SIMBA-ET and SIMBA-HT were processed to obtain snow depth and ice thickness (smoothed with a 3-day running mean), as well as the thermistor number, the vertical position Z relative to the snow-ice interface and the measured SIMBA-ET at each detected interface (atmosphere-snow, snow-ice and ice-ocean) for the period between 2014-02-05T20:00:39 and 2014-08-19T08:00:40. To do this, we combined two derivatives of measured temperatures (the ET vertical gradient and HT rise ratio) to reduce the detection uncertainty of all interfaces considered. The snow or ice surface, consequentially the snow depth, is determined by the ET vertical gradient. Potential formation of snow ice is not explicitly considered in this data set, but may occur as depicted by vertical changes of the snow-ice interface position. The ice-ocean interface is usually determined using the HT rise ratio and serves as the lower limit for ice thickness. Overall, the accumulated error is 2 to 4 times the sensor spacing for both the snow depth and ice thickness. For interface temperatures, individual sensors in the chain measure with a temperature resolution of 0.0625°C, with the overall accuracy landing in the range of ± 2°C (Jackson et al., 2013). After the snow cover has melted, negative values for snow depth may indicate the onset of ice surface melt
Snow depth, sea ice thickness and interface temperatures derived from measurements of SIMBA buoy 2023T102
No full textThe Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environmental temperature SIMBA-ET and a temperature change around the thermistors after a weak heating is applied to each sensor (SIMBA-HT). SIMBA 2023T102 (a.k.a. PRIC_0903) is an autonomous instrument that was installed on drifting sea ice in the Arctic Ocean (Polarstern PS138-Arcwatch 2023) as part of the project PRIC. Its thermistor chain is 5 m long, and equipped with 241 thermistors (Maxim Integrated DS28EA00) at a spacing of 2 cm. Based on a manual classification method, the SIMBA-ET and SIMBA-HT were processed to obtain snow depth and ice thickness (smoothed with a 3-day running mean), as well as the thermistor number, the vertical position Z relative to the snow-ice interface and the measured SIMBA-ET at each detected interface (atmosphere-snow, snow-ice and ice-ocean) for the period between 2023-09-05T03:00:16 and 2023-11-14T03:00:16. To do this, we combined two derivatives of measured temperatures (the ET vertical gradient and HT rise ratio) to reduce the detection uncertainty of all interfaces considered. The snow or ice surface, consequentially the snow depth, is determined by the ET vertical gradient. Potential formation of snow ice is not explicitly considered in this data set, but may occur as depicted by vertical changes of the snow-ice interface position. The ice-ocean interface is usually determined using the HT rise ratio and serves as the lower limit for ice thickness. Overall, the accumulated error is 2 to 4 times the sensor spacing for both the snow depth and ice thickness. For interface temperatures, individual sensors in the chain measure with a temperature resolution of 0.0625°C, with the overall accuracy landing in the range of ± 2°C (Jackson et al., 2013). After the snow cover has melted, negative values for snow depth may indicate the onset of ice surface melt
Snow depth, sea ice thickness and interface temperatures derived from measurements of SIMBA buoy 2018T50
No full textThe Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environmental temperature SIMBA-ET and a temperature change around the thermistors after a weak heating is applied to each sensor (SIMBA-HT). SIMBA 2018T50 (a.k.a. Awi_32r) is an autonomous instrument that was installed on drifting sea ice in the Arctic Ocean (Alert MAPLI in 2018) as part of the project Sea Ice Physics @ AWI (AWI_SeaIce). Its thermistor chain is 5 m long, and equipped with 240 thermistors (Maxim Integrated DS28EA00) at a spacing of 2 cm. Based on a manual classification method, the SIMBA-ET and SIMBA-HT were processed to obtain snow depth and ice thickness (smoothed with a 3-day running mean), as well as the thermistor number, the vertical position Z relative to the snow-ice interface and the measured SIMBA-ET at each detected interface (atmosphere-snow, snow-ice and ice-ocean) for the period between 2018-05-05T01:00:14 and 2018-07-10T01:00:14. To do this, we combined two derivatives of measured temperatures (the ET vertical gradient and HT rise ratio) to reduce the detection uncertainty of all interfaces considered. The snow or ice surface, consequentially the snow depth, is determined by the ET vertical gradient. Potential formation of snow ice is not explicitly considered in this data set, but may occur as depicted by vertical changes of the snow-ice interface position. The ice-ocean interface is usually determined using the HT rise ratio and serves as the lower limit for ice thickness. Overall, the accumulated error is 2 to 4 times the sensor spacing for both the snow depth and ice thickness. For interface temperatures, individual sensors in the chain measure with a temperature resolution of 0.0625°C, with the overall accuracy landing in the range of ± 2°C (Jackson et al., 2013). After the snow cover has melted, negative values for snow depth may indicate the onset of ice surface melt
Snow depth, sea ice thickness and interface temperatures derived from measurements of SIMBA buoy 2019T58
No full textThe Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environmental temperature SIMBA-ET and a temperature change around the thermistors after a weak heating is applied to each sensor (SIMBA-HT). SIMBA 2019T58 (a.k.a. FMI05-09) is an autonomous instrument that was installed on drifting sea ice in the Central Arctic Ocean (Polarstern PS122 (MOSAiC) in 2019/20) as part of the project FMI. Its thermistor chain is 5 m long, and equipped with 241 thermistors (Maxim Integrated DS28EA00) at a spacing of 2 cm. Based on a manual classification method, the SIMBA-ET and SIMBA-HT were processed to obtain snow depth and ice thickness (smoothed with a 3-day running mean), as well as the thermistor number, the vertical position Z relative to the snow-ice interface and the measured SIMBA-ET at each detected interface (atmosphere-snow, snow-ice and ice-ocean) for the period between 2019-10-08T01:00:14 and 2020-07-08T07:00:14. To do this, we combined two derivatives of measured temperatures (the ET vertical gradient and HT rise ratio) to reduce the detection uncertainty of all interfaces considered. The snow or ice surface, consequentially the snow depth, is determined by the ET vertical gradient. Potential formation of snow ice is not explicitly considered in this data set, but may occur as depicted by vertical changes of the snow-ice interface position. The ice-ocean interface is usually determined using the HT rise ratio and serves as the lower limit for ice thickness. Overall, the accumulated error is 2 to 4 times the sensor spacing for both the snow depth and ice thickness. For interface temperatures, individual sensors in the chain measure with a temperature resolution of 0.0625°C, with the overall accuracy landing in the range of ± 2°C (Jackson et al., 2013). After the snow cover has melted, negative values for snow depth may indicate the onset of ice surface melt
Length and weight of F0 wild-caught adults Gasterosteus aculeatus (males and females) used for breeding in heatwave experiment
No full textFish were brought to the laboratory at the AWI Wadden Sea Station Sylt and used as breeding adults for a multi-generation laboratory experiment investigating the effects of marine heatwaves on stickleback fitness-related traits. These F0 generation wild-caught adults (males and females) were acclimated to three heatwave scenarios (no heatwave control, single heatwave or double heatwave) for three months before breeding (starting 12 June 2022) via artificial fertilization
X-ray µ-CT data reconstruction, image stacks of selected samples from IODP Site 385-U1546
No full textThis contribution comprises true-3D volume datasets (Digital drill cores), acquired by a X-ray Computed Microtomography (µ-CT) survey on selected drill core material recovered from Site U1546, Hole C, drilled by IODP Expedition 385 in the Guaymas Basin, Gulf of California (for more details see Teske et al., 2021). The four samples are igneous material from a single igneous 75 m thick sill intrusion. The samples were scanned as quarter cores and selected along the sill thickness to enable visualization of the main textural variations found along the sill (see Galerne et al., in Rev). The X-ray μ-CT scans were performed using the ZEISS Xradia 520 Versa system of the MAPEX Center for Materials and Processes at the University of Bremen, Germany. This µ-CT survey has been conducted as part of IODP Expedition 385 Post-cruise research led and secured by Christophe Galerne (German Research Foundation (DFG) funding priority program SPP 527. Project number 447431016). The samples were quarter cores or irregularly shaped pieces. The reconstructed image material has resolutions between 8.05 and 16.1 µm/voxel (depending on the sample size and geometry). The µ-CT-derived image volumes comprise the true 3-D spatial arrangement of fabric compounds in the rock. In the reconstructed 16-bit greyscale volume data, areas of highly attenuating phases (e.g. sulfides, calcite) are encoded in light grey values, whereas areas of low X-ray absorption are color-coded in dark grey (e.g. clays) or black (e.g. voids, cracks). In order to facilitate straightforward access to the digital drill core image material, the volume data is provided as a zipped stack of tif images. In addition, each digital drill core is characterized by three types of visualization: (i) shaded and classical texture-based volume rendering (volren), (ii) maximum intensity projection (volren-MIP): visualization of the highest intensity in a data volume along the current line of sight, and (iii) three perpendicular virtual cutting planes (3-slices). As an added value to the non-destructive visualization procedure, the reconstructed X-ray micro-CT scans of the studied drill core material provide volume reconstructions which can serve as digitypes that may be studied as digital facsimile without the necessity of consulting / modifying / destructive interactions of the actual type specimens (e. g. for investigations regarding the fabric relations). These image data can be used for quantitative 3D image analysis, e. g. to derive empirical relations between porosity, the extent of replacement of primary phases, and the distribution of secondary phases (and many more)
Oceanographic conditions in the Coquimbo upwelling system during the year 2023
No full textA series of discrete measurements were obtained on a near-monthly basis in a subtropical upwelling area of the Humboldt Current System during the year 2023. These included temperature, salinity, dissolved oxygen, fluorescence, and pH profiles, as well as measurements of zooplankton biomass and chlorophyll- and particulate organic carbon (POC) concentrations. The CTD information was analyzed through temporal section and S-T diagrams depicting the oxygen concentration. The measurements were conducted under distinct warm events associated with the ENSO dynamic. The objective of this study was to evaluate the influence of remote (ENSO) and upwelling forcing on the intraseasonal variability of zooplankton biomass