Abstract: The MODIS/Terra Snow Cover Daily L3 Global 0.05Deg CMG (MOD10C1) data set contains snow cover and Quality Assessment (QA) data, latitudes and longitudes in compressed Hierarchical Data Format-Earth Observing System (HDF-EOS) format, and corresponding metadata. This data set consists of 7200 columns by 3600 rows of global arrays of snow cover in a 0.05 degree Climate Modeling Grid (CMG). MODIS snow cover data are based on a snow mapping algorithm that employs a Normalized Difference Snow Index (NDSI) and other criteria tests. Data are stored in HDF-EOS format, and are available from 24 February 2000 to present via FTP. Data can also be obtained in GeoTIFF format by ordering the data through the Data Pool.
Quality indicators for MODIS snow data can be found in the following places: * AutomaticQualityFlag and the ScienceQualityFlag metadata objects and their corresponding explanations: AutomaticQualityFlagExplanation and ScienceQualityFlagExplanation located in the CoreMetadata.0 global attributes * Custom local attributes associated with each SDS, for example, snow cover * Snow Spatial QA field. ... These quality indicators are generated during production or in post-production scientific and quality checks of the data product. For more information on local and global attributes, go to one of the following links: * MOD10C1 and MYD10C1 Local Snow Cover Attributes, Version 5 * MOD10C1 and MYD10C1 Global Snow Cover Attributes, Version 5 The AutomaticQualityFlag is automatically set according to conditions for meeting data criteria in the snow mapping algorithm. In most cases, the flag is set to either Passed or Suspect, and in rare instances, it may be set to Failed. Suspect means that a significant percentage of the data were anomalous and that further analysis should be done to determine the source of anomalies. The AutomaticQualityFlagExplanation contains a brief message explaining the reason for the setting of the AutomaticQualityFlag. The ScienceQualityFlag and the ScienceQualityFlagExplanation maybe updated after production, either after an automated QA program is run or after the data product is inspected by a qualified snow scientist. Content and explanation of this flag are dynamic so it should always be examined if present in the external metadata file. The algorithm tests for a variety of anomalous conditions and sets the pixel value accordingly if such conditions are detected. Summary statistics about missing data, the percent cloud cover, the percent of good or other quality data, and snow cover percent are calculated and placed in the metadata for each product. The Snow Spatial QA data field provides additional information on algorithm results for each pixel within a spatial context, and is used as a measure of usefulness for snow-cover data. The QA information tells if algorithm results were nominal, abnormal, or if other defined conditions were encountered for a pixel (Riggs, Hall, and Salomonson 2006). The NASA Goddard Space Flight Center: MODIS Land Quality Assessment Web site provides updated quality information for each product.
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
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Postal Code: 80309-0449
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