Snow depth and sea ice thickness derived from the measurements of SIMBA buoy 2019T65

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）是一种热敏电阻串式冰质量平衡浮标（thermistor string type IMB）（Jackson等，2013），可采集环境温度数据SIMBA-ET，以及对各传感器施加弱加热后热敏电阻周边的温度变化数据SIMBA-HT。在北极气候多学科漂流观测站（Multidisciplinary drifting Observatory for the Study of Arctic Climate, MOSAiC）科考航次的1a、1及3航段中，共计22台SIMBA设备被部署于北冰洋的分布式观测网（Distributed Network, DN）与中央观测站内。该SIMBA热敏电阻串总长5.12 m，布设有256支热敏电阻（Maxim Integrated DS28EA00），布设间距为0.02 m。研究人员基于人工识别方法，对SIMBA-ET与SIMBA-HT数据进行处理以反演积雪深度与冰厚。本研究结合两种最优方法——ET垂直梯度法与HT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ET垂直梯度法反演得到的雪/冰表面高度，进而确定积雪深度。本数据集未考虑雪冰（snow ice）与叠置冰（superposed ice）的形成过程。换言之，两处观测站点（2019T56与2019T72）的积雪深度数值已包含雪冰层厚度。通常情况下，叠置冰的占比可忽略不计。本研究采用HT升温比值法确定冰-水界面高度，进而计算冰厚。总体而言，积雪深度与冰厚的测量精度均为0.02 m。当积雪完全消融后，积雪深度出现负值则指示冰面融冻过程的启动。