Spatial variability in sub-photic zone nitrate δ15N and surface mass balance across East Antarctica

Geographic information, surface mass balance (SMB) data, and sub-photic zone (>0.3 m) nitrate concentration and nitrogen isotopic composition (δ15NNO3) for 135 sites across East Antarctica. This database was used to examine and define the relationship between δ15NNO3 and SMB in Antarctica as part of the SCADI (Snow Core Accumulation from Delta-15N Isotopes) and EAIIST (East Antarctic International Ice Sheet Traverse) projects. Of these 135 sites, 92 are newly reported here while the other site data were previously published and are cited accordingly. Snow bearing nitrate was sampled from snow pits and firn/ice cores at different dates depending on the original scientific campaign, but predominately between 2010 and 2020, with the earliest sampling occurring in 2004. Nitrate was later extracted from the snow, concentrated, and analyzed for δ15NNO3. Surface mass balance data comes from a combination of previous ground-based observations (e.g., stakes, ice core data) and the output from Modèle Atmosphérique Régional version 3.6.4 with European Centre for Medium-Range Weather Forecasts “Interim” re-analysis data (ERA-interim) data, adjusted for observed model SMB biases. Elevation data were extracted from the Reference Elevation Model of Antarctica (REMA, https://doi.org/10.5194/tc-13-665-2019).

本数据集涵盖南极东部135个测点的地理信息、表面质量平衡（surface mass balance, SMB）数据、0.3米以下弱光带硝酸盐浓度与氮同位素组成（δ15NNO3）。本数据库作为雪芯积雪量反演（Snow Core Accumulation from Delta-15N Isotopes, SCADI）与南极东部国际冰盖考察（East Antarctic International Ice Sheet Traverse, EAIIST）项目的组成部分，用于探究并明确南极地区δ15NNO3与SMB之间的关联。在这135个测点中，92个为本次首次公开的新数据，其余测点数据均已在既往研究中发表并已对应标注引用来源。含硝酸盐雪样根据原始科学考察计划的时间节点进行采集，采样介质包括雪坑与粒雪/冰芯，采样时段主要集中于2010至2020年，最早的采样工作始于2004年。后续研究人员从雪样中提取硝酸盐，经浓缩处理后对其δ15NNO3进行分析测定。表面质量平衡数据整合了两类来源：一是既往地面观测数据（例如冰桩观测、冰芯数据），二是结合欧洲中期天气预报中心"Interim"再分析数据（ERA-interim）运行的区域大气模式（Modèle Atmosphérique Régional）3.6.4版本的模拟结果，并针对观测到的模式SMB偏差进行了校正。海拔数据提取自南极参考高程模型（Reference Elevation Model of Antarctica, REMA, https://doi.org/10.5194/tc-13-665-2019）。