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Surface Mass Balance and Snow Depth on Sea Ice Working Group (SUMup) accumulation on land ice subdataset, Greenland and Antarctica, 1987-2018

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NSF Arctic Data Center2019-01-01 更新2026-05-11 收录
下载链接:
https://arcticdata.io/catalog/#view/doi:10.18739/A2ZS2KD0Z
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资源简介:
This dataset includes accumulation on land ice measurements from both hemispheres. This dataset is a community effort to distribute easy to use in-situ data to improve surface mass balance modeling and remote sensing efforts. This dataset is a compilation of work from many individual researchers. When using this dataset please cite both the individual researchers who provided the data as listed in the Citation field as well as this dataset. The snow accumulation on land ice subdataset contains over 300,000 data points. The Arctic accumulation measurements, all within Greenland, contain 48% of the measurements with ~1% coming from Summit Station. The Antarctic contains the remaining 51% of the measurements. While most of the data are measurements of accumulation between 1950 and present (~97%), to coincide with the time span of many regional climate models and reanalysis products, some records (~3%) are included dating back to 1800. The measurement methods include ice cores, snow pits, radar isochrons, and stake measurements. Fields of data include the date taken, latitude, longitude, start year and end year (if not an annual measurement), year (if annual), accumulation, error, elevation, radar horizontal resolution, method, name of field campaign, and associated citation.

本数据集涵盖南北两个半球的陆地冰累积量实测资料。本数据集由社区共建,旨在发布易于使用的原位实测数据,以助力地表质量平衡模拟与遥感研究工作。本数据集整合了多位独立研究者的研究成果。使用本数据集时,请同时引用“引用”字段中列明的提供数据的研究者,以及本数据集本身。陆地冰积雪累积量子数据集包含超过30万个数据点。北极区域的累积量实测数据全部来自格陵兰岛,占总数据量的48%,其中约1%的数据源自峰点站(Summit Station)。南极区域的实测数据占总数据量的剩余51%。为适配多数区域气候模型与再分析产品的时间跨度,本数据集的实测数据多集中于1950年至今(约占97%);同时也收录了约3%可追溯至1800年的历史记录。实测方法涵盖冰芯、雪坑、雷达等时线法以及测杆测量。数据字段包含采集日期、纬度、经度、起始年份与终止年份(非年度测量时适用)、年份(年度测量时适用)、累积量、误差、海拔、雷达水平分辨率、测量方法、野外试验名称以及相关引用文献。
提供机构:
University of Colorado, Boulder; National Snow and Ice Data Center
创建时间:
2019-01-01
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