Snow, ice, and glaciers have the highest albedo of any part of Earth's surface. The increase in melting of the polar ice sheet results in a rapid and sequential decrease in albedo and subsequently influences the global energy balance. The hydrological system derived from surface melt and basal meltwater will affect the dynamic stability of ice sheet and therefore mass balance. The dataset combined microwave radiometer product and optical albedo product, the daily, winter (June-August) averages and July averages of the former are used for layer-stacking, then Gram-Schmidt Spectral Sharpening was adapted to fuse the layer-stacking results with MODIS GLASS albedo product. The spatial resolution of fusion-results has been downscaled from 25 km to 0.05˚. By employing a threshold-based melt detection approach for each fusion-results pixel, Antarctic ice sheet surface melt daily product for 1985-1986, 2000-2001, 2015-2016 (DSSMIS) was generated. The spatial resolution of DSSMIS is higher than that of published data sets at home and abroad. Combined with the advantages of radiometer and albedo data, the spatial details characteristics are enhanced and consistent with the extraction range of the original radiometer products, effectively reducing the noise of the radiometer. It better reflects the melting gradient of mountainous area, groundline area and ice shelf over time, DSSMIS has a higher accuracy. DSSMIS’s data type is integer, where 1 is melted, 0 is not melted, 255 is masked area besides Antarctic ice sheet, and the data set is stored as *.nc.

File naming and required software

File name: the surface melting data is stored in NC format. The file name is "antarcticcdailysurfacemeltyyyy-yyyy. NC", where yyyy-yyyy represents the year. For example, ‘antarcticcdailysurfacemelt1985-1986.nc’ represents the NC file, which describes the surface melting range of the Antarctic ice sheet from July 1, 1985 to June 30, 1986. The NC file contains four variables: melt and polar_ Stereographic, x and y, respectively represent the melting pixel value, coordinate system information, X coordinate and Y coordinate in the projection coordinate system.

Data reading method: all NC files in the dataset can be directly read by panoply program （https://www.giss.nasa.gov/tools/panoply/download/ ）, select the variable melt , create the XY coordinate axis corresponding to the variable x and variable y for browsing, and change the time to browse the melting range of different dates. If you want to save it as a separate picture for display or analysis, you can use the "multidimensional tool - create NetCDF grid layer" tool in ArcGIS program to process the results and generate a file in TIF format, including the melting range of all days in the corresponding year. You can change the display time by opening "enable time in this layer" in the "attribute - time" tab. In addition, you can also select GDAL, NCO, CDO and other tools to open NC files or convert them to other formats.

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Cite as:

Wei, S. (2021). Antarctic Ice Sheet Surface Melt 0.05˚ Daily Data Set (1985-1986, 2000-2001, 2015-2016). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Cryos.tpdc.271848. CSTR: 18406.11.Cryos.tpdc.271848. (Download the reference： RIS | Bibtex )

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References literature

1.Zheng, L., Zhou, C., & Liang, Q. (2019). Variations in antarctic peninsula snow liquid water during 1999–2017 revealed by merging radiometer, scatterometer and model estimations. Remote Sensing of Environment, 232, 111219-. (View Details | Download )

2.Picard, G., & Fily, M. (2006). Surface melting observations in antarctica by microwave radiometers: correcting 26-year time series from changes in acquisition hours. Remote Sensing of Environment, 104(3), 325-336. (View Details | Download )

3.Trusel, L.D., Frey, K.E., & Das, S.B. (2012). Antarctic surface melting dynamics: enhanced perspectives from radar scatterometer data. Journal of Geophysical Research Earth Surface, 117(F2). (View Details | Download )

4.Zheng, L., & Zhou, C. (2019). Comparisons of snowmelt detected by microwave sensors on the shackleton ice shelf, east antarctica. International Journal of Remote Sensing(1). (View Details | Download )

5.Liu, H., Lei, W., & Jezek, K.C. (2006). Automated delineation of dry and melt snow zones in antarctica using active and passive microwave observations from space. IEEE Transactions on Geoscience & Remote Sensing, 44(8), 2152-2163. (View Details )

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