Surface melt-related multi-source remote-sensing and climate model data over Larsen C Ice Shelf, Antarctica for segmentation and machine learning applications

This dataset contains high-resolution satellite-derived snow/ice surface melt-related data on a common 100 m equal area grid (Lambert azimuthal equal area projection; EPSG 9820) over Larsen C Ice Shelf and surrounding areas in Antarctica. The data is prepared to be used as part of a machine learning framework that aims to fill data gaps in computed meltwater fraction on the 100 m grid using a range of methods, results of which will be published separately.
<br><br><br>The data include fraction of a grid cell covered by meltwater derived from Sentinel-1 synthetic aperture radar (SAR) backscatter, satellite-derived passive microwave (PMW) brightness temperatures, snowpack liquid water content within the first meter of snow and atmospheric and radiative variables from the Modéle Atmosphérique Règional (MAR) regional climate model, a static digital elevation model (DEM), and an ice sheet mask.
<br><br><br>A similar dataset has been produced for Helheim Glacier, Greenland and is also available through the US Antarctic Program Data Center.

本数据集包含南极拉森C冰架及其周边区域的高分辨率卫星反演冰雪表面融冻相关数据，采用统一的100米等面积格网（兰伯特方位等面积投影，Lambert azimuthal equal area projection；EPSG 9820）。本数据集将作为机器学习框架的组成部分，该框架旨在通过多种方法填补100米格网融水占比计算中的数据空白，相关研究成果将另行发表。

数据包含基于Sentinel-1合成孔径雷达（SAR）后向散射反演得到的格网单元融水覆盖占比、卫星反演被动微波（PMW）亮温、积雪表层1米内的积雪液态水含量，以及区域气候模型Modéle Atmosphérique Règional（MAR）输出的大气与辐射变量、静态数字高程模型（DEM）和冰盖掩膜数据。

格陵兰黑尔海姆冰川也曾构建同类数据集，该数据集同样可通过美国南极计划数据中心获取。