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  • 1
    In: Tamsalu, Rein, A theoretical and experimetal study of the self-similarity concept /Rein Tamsalu and Kai Myrberg, Helsinki, 1998, (1998), 1
    In: year:1998
    In: number:1
    Type of Medium: Article
    Language: Undetermined
    Location Call Number Limitation Availability
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  • 2
    Publication Date: 2023-11-24
    Description: Temperatures were measured along a chain of thermistors. SIMBA 2020T85 (a.k.a. PRIC_09_06, IRIDIUM number 300234068704730) is an autonomous instrument that was installed on drifting sea ice in the Arctic Ocean during the 5th leg of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) in September 2020. The buoy was deployed over a ridge at the CO3 of MOSAiC. The thermistor chain was 5 m long and included 241 sensors with a regular spacing of 2cm. The 14th sensor from the top was set at the ice surface. The resulting time series describes the evolution of temperature as a function of depth and time between 19 September 2020 and 27 June 2021 in sample intervals of 6 hours for temperature and 24 hours for temperature differences. The temperature differences after two heating cycles of 30 and 120 s are unavailable. The near-surface air temperature was measured at 1 m over the ice surface. In addition to temperature, geographic position, barometric pressure, tilt and compass were measured.
    Keywords: 2020T85, PRIC_09_06; Arctic Ocean; mass balance; MOSAiC; MOSAiC20192020; MOSAiC-ICE; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/5; PS122/5_58-170; SAMS Ice Mass Balance buoy; Sea ice; SIMBA; Temperature
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Limitation Availability
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  • 3
    Publication Date: 2023-11-24
    Description: A thermistor string-based snow and ice mass balance apparatus (SIMBA) was deployed in the land-fast sea ice zone in Young sound, eastern Greenland, on 28 October 2020, and operated successfully until 10 April 2021. The SIMBA was manufactured by the Scottish Association for Marine Science (SAMS) (Jackson et al., 2013). Two types of temperatures were measured by the SIMBA. The temperature of air, snow, ice, and water where SIMBA thermistor sensors were placed, is named as SIMBA_ET. The temperature reading after each thermistor sensor was applied with an identical amount of heat, is named SIMBA_HT. The amount of heat was controlled by the duration of heating, often configured as the 30s and 120s, respectively. The SIMBA_ET and SIMBA_HT were measured four times per day and one time per day, respectively. So SIMBA_HT(30) and SIMBA_HT(120) represent the sensor temperature changes in air, snow, ice, and water after a heating cycle of the 30s and 120s, respectively. The length of the SIMBA thermistor chain is 4.8m. There are 240 thermistor sensors (DS28EA00, accurate to +/- 0.0625°C) with 0.02 m spacing. Combined with a SIMBA algorithm (Cheng et al., 2020) and manual analyses, snow depth and ice thickness can be derived from SIMBA_ET and SMMBA_HT observations. Overall, the measurement accuracy was 0.02 m for both the snow depth and ice thickness. The submitted data package includes 6 data files, i.e., SIMBA GPS position; snow depth; ice thickness; SIMBA_ET, as well as in situ snow depth and ice thickness measured by the local personnel.
    Keywords: Arctic Ocean; ice thickness; INTAROS; Integrated Arctic observation system; mass balance; snow depth; temperature gradient
    Type: Dataset
    Format: application/zip, 5 datasets
    Location Call Number Limitation Availability
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  • 4
    Publication Date: 2023-11-24
    Description: The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) that measures the environment temperature SIMBA-ET and temperature change (SIMBA-HT) after an identical heating element is applied to each sensor. This SIMBA (FMI02) was deployed in the high Arctic during the Polarstern Arctic cruise (ARK-XXVII/3) on 22, September 2012. The SIMBA thermistor chain is 4.8 m long and equipped with 240 thermistors at 0.02 m spacing. Snow depth and ice thickness were derived manually by investigating the SIMBA_ET vertical temperature profiles. This SIMBA was deployed on 22 Sep 2012 at 15:15 UTC. The initial position was Latitude: 88.81287 N Longitude: 57.53883 E. The initial ice thickness was 1.44 m; Freeboard was 0.21 m and the snow depth was 0.03 m. The submitted data package includes 3 data files, i.e., SIMBA GPS position; SIMBA snow depth and ice thickness and SIMBA environmental temperature (SIMBA_ET).
    Keywords: Arctic Ocean; ice thickness; snow depth; temperature gradient
    Type: Dataset
    Format: application/zip, 3 datasets
    Location Call Number Limitation Availability
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  • 5
    Publication Date: 2023-12-18
    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.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_118; Akademik Fedorov; Arctic Ocean; DATE/TIME; ice thickness; Ice thickness; LATITUDE; LONGITUDE; Manual identification method; mass balance; Mosaic; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; PS122/1_1-175, 2019T72, FMI_06_05; SAMS Ice Mass Balance buoy; Sea ice; SIMBA; snow depth; Snow thickness
    Type: Dataset
    Format: text/tab-separated-values, 402 data points
    Location Call Number Limitation Availability
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  • 6
    Publication Date: 2023-12-18
    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.
    Keywords: 2019T64; AF-MOSAiC-1; AF-MOSAiC-1_122; Akademik Fedorov; Akademik Tryoshnikov; Arctic Ocean; AT-MOSAiC-1; AT-MOSAiC-1_5; DATE/TIME; ice thickness; Ice thickness; LATITUDE; LONGITUDE; Manual identification method; mass balance; Mosaic; MOSAiC; MOSAiC20192020; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; North Greenland Sea; PS122/1_1-225, 2019T64, PRIC_09_03; SAMS Ice Mass Balance buoy; Sea ice; SIMBA; snow depth; Snow thickness
    Type: Dataset
    Format: text/tab-separated-values, 594 data points
    Location Call Number Limitation Availability
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  • 7
    Publication Date: 2023-12-18
    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.
    Keywords: AF-MOSAiC-1; AF-MOSAiC-1_89; Akademik Fedorov; Arctic Ocean; DATE/TIME; ice thickness; Ice thickness; LATITUDE; LONGITUDE; Manual identification method; mass balance; Mosaic; MOSAiC; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; PS122/1_1-226, 2019T65, PRIC_09_04; SAMS Ice Mass Balance buoy; Sea ice; SIMBA; snow depth; Snow thickness
    Type: Dataset
    Format: text/tab-separated-values, 472 data points
    Location Call Number Limitation Availability
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  • 8
    Publication Date: 2023-12-18
    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.
    Keywords: 2020T74, PRIC_10_02; Arctic Ocean; DATE/TIME; ice thickness; Ice thickness; LATITUDE; LONGITUDE; Manual identification method; mass balance; Mosaic; MOSAiC; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/3; PS122/3_28-95; SAMS Ice Mass Balance buoy; Sea ice; SIMBA; snow depth; Snow thickness
    Type: Dataset
    Format: text/tab-separated-values, 226 data points
    Location Call Number Limitation Availability
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  • 9
    Publication Date: 2023-12-18
    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.
    Keywords: 2019T56, FMI_05_06; Arctic Ocean; DATE/TIME; ice thickness; Ice thickness; LATITUDE; LONGITUDE; Manual identification method; mass balance; Mosaic; MOSAiC; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/1; PS122/1_1-272; SAMS Ice Mass Balance buoy; Sea ice; SIMBA; snow depth; Snow thickness
    Type: Dataset
    Format: text/tab-separated-values, 490 data points
    Location Call Number Limitation Availability
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  • 10
    Publication Date: 2023-12-18
    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.
    Keywords: 2019T58; AF-MOSAiC-1; AF-MOSAiC-1_115; Akademik Fedorov; Akademik Tryoshnikov; Arctic Ocean; AT-MOSAiC-1; AT-MOSAiC-1_2; DATE/TIME; ice thickness; Ice thickness; LATITUDE; LONGITUDE; Manual identification method; mass balance; Mosaic; MOSAiC; MOSAiC20192020; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; North Greenland Sea; PS122/1_1-177, 2019T58, FMI_05_09; SAMS Ice Mass Balance buoy; Sea ice; SIMBA; snow depth; Snow thickness
    Type: Dataset
    Format: text/tab-separated-values, 572 data points
    Location Call Number Limitation Availability
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