Abstract: The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument on the NASA Earth Observing System (EOS) Aqua satellite provides global passive microwave measurements of terrestrial, oceanic, and atmospheric variables for the investigation of water and energy cycles. These Level-3 Snow Water Equivalent (SWE) data sets contain SWE data and quality assurance flags mapped to Northern and Southern Hemisphere 25 km Equal-Area Scalable Earth Grids (EASE-Grids). Data are stored in Hierarchical Data Format - Earth Observing System (HDF-EOS) format, and are available from 19 June 2002 to the present via FTP.
Quality Assessment Each HDF-EOS file contains core metadata with Quality Assessment (QA) metadata flags that are set by the Science Investigator-led Processing System (SIPS) at the Global Hydrology and Climate Center (GHCC) prior to delivery to NSIDC. A separate metadata file in XML format is also delivered to NSIDC with the HDF-EOS file; it contains the same information as the core metadata. ... Three levels of QA are conducted with the AMSR-E Level-2 and Level-3 products: automatic, operational, and science QA. If a product does not fail QA, it is ready to be used for higher-level processing, browse generation, active science QA, archive, and distribution. If a granule fails QA, SIPS does not send the granule to NSIDC until it is reprocessed. Level-3 products that fail QA are never delivered to NSIDC (Conway 2002). Automatic QA Chang visually examined random samples of SWE products to ensure they were consistent with an understanding of climate and that no gross errors were present. Future validation will involve comparing retrieved SWE values with estimates from airborne gamma observations over the U.S. (Carroll 1997) and with snow gauge data (Carroll et al. 1995), as well as comparing snow extent with MODIS snow maps (Chang and Rango 2000). Operational QA AMSR-E Level-2A data arriving at GHCC are subject to operational QA prior to processing higher-level products. Operational QA varies by product, but it typically checks the following criteria for a given file (Conway 2002): * File is correctly named and sized * File contains all expected elements * File is in the expected format * Required EOS fields of time, latitude, and longitude are present and populated * Structural metadata is correct and complete * The file is not a duplicate * The HDF-EOS version number is provided in the global attributes * The correct number of input files were available and processed Science QA AMSR-E Level-2A data arriving at GHCC are also subject to science QA prior to processing higher-level products. If less than 50 percent of a granule's data is good, the science QA flag is marked 'suspect' when the granule is delivered to NSIDC. In the SIPS environment, the science QA includes checking the maximum and minimum variable values, and percent of missing data and out-of-bounds data per variable value. At the Science Computing Facility (SCF), also at GHCC, science QA involves reviewing the operational QA files, generating browse images, and performing the following additional automated QA procedures (Conway 2002): * Historical data comparisons * Detection of errors in geolocation * Verification of calibration data * Trends in calibration data * Detection of large scatter among data points that should be consistent Geolocation errors are corrected during Level-2A processing to prevent processing anomalies such as extended execution times and large percentages of out-of-bounds data in the products derived from Level-2A data. The Team Lead SIPS (TLSIPS) developed tools for use at SIPS and SCF for inspecting the data granules. These tools generate a QA browse image in Portable Network Graphics (PNG) format and a QA summary report in text format for each data granule. Each browse file shows Level-2A and Level-2B data. These are forwarded from Remote Sensing Systems (RSS) to GHCC along with associated granule information, where they are converted to HDF raster images prior to delivery to NSIDC. SWE is estimated for SD retrievals greater than 1 mm. Based on dthe 2002-2003 winter AMSR-E data and 38 coincident ground observations in the World Meteorological Organization (WMO) Global Telecommunications System (GTS) network, the standard error is 24.2 cm. Further validation is planned using multiple local, regional, and global data sets. See NSIDC's AMSR-E Validation Data for information about data used to check the accuracy and precision of AMSR-E observations.
City University of New York and NASA GSFC
Department of Earth and Atmosphere Sciences
City: New York
Province or State:
Postal Code: 10031
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