Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2020T79

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.

雪冰质量平衡阵列（Snow and Ice Mass Balance Array，SIMBA）是一款热敏电阻串式冰质量平衡测量系统（Ice Mass Balance，IMB，Jackson等，2013），可测量环境温度（SIMBA-ET），以及对每个传感器施加弱加热后热敏电阻周围的温度变化（SIMBA-HT）。在北极气候多学科漂流观测计划（Multidisciplinary drifting Observatory for the Study of Arctic Climate，MOSAiC）的航次1a、航次1与航次3期间，研究团队于北冰洋的分布式网络（Distributed Network，DN）与中心观测站区域共部署了22套SIMBA系统。该SIMBA热敏电阻串总长5.12 m，搭载256个美信集成DS28EA00（Maxim Integrated DS28EA00）热敏电阻，传感器间距为0.02 m。本数据集采用人工识别方法，对SIMBA-ET与SIMBA-HT数据进行处理以反演雪深与冰厚。本次研究结合两种最优方法——环境温度垂直梯度法与加热升温比值法——以降低反演不确定性。为保证数据一致性，本研究采用环境温度垂直梯度法确定的雪/冰表面，进而得到雪深数值。本数据集未考虑雪冰与叠加冰的形成过程，换言之，雪深数值包含了2019T56与2019T72两个测站处的雪冰层；通常情况下叠加冰占比可忽略不计。研究采用加热升温比值法确定冰水界面，进而计算得到冰厚。整体而言，雪深与冰厚的测量精度均为0.02 m。当积雪完全消融后，雪深的负值代表冰面融化阶段的起始时刻。

搜集汇总

背景与挑战

背景概述

该数据集包含2020年北极MOSAiC考察期间SIMBA浮标测量的雪深和海冰厚度数据，采用热敏电阻链技术测量，精度达0.02米，覆盖北纬81.29°-84.60°、东经0.28°-18.28°区域。