Abstract:
The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument on the NASA EOS Aqua satellite provides global passive microwave measurements of terrestrial, oceanic, and atmospheric variables for the investigation of global water and energy cycles.
These near real-time (NRT) products are generated within 3 hours of the last observations in the file, by the ... Land Atmosphere Near real-time Capability for EOS (LANCE) at the AMSR-E Science Investigator-led Processing System (AMSR-E SIPS). The AMSR-E/Aqua Level-2B rain product includes instantaneous rain rate and rain type over ice-free and snow-free land and ocean between 70 degrees north and south latitudes at 5.4 km, generated by the GPROF algorithm using Level-2A TBs. Data are stored in HDF-EOS format, and are available via FTP from the LANCE system.
If data latency is not a primary concern, please consider using science quality products. Science products are created using the best available ancillary, calibration and ephemeris information. Science quality products are an internally consistent, well-calibrated record of the Earth¹s geophysical properties to support science. Science quality AMSR-E products are available from NSIDC DAAC.
Quality
Differences between the LANCE NRT and standard products are currently under investigation. Known, but not yet quantified, differences include • the ephemeris files (LANCE uses predicted ephemeris and standard products use definitive ephemeris) and • standard product generation includes more sophisticated, dynamic cross ... calibration and geolocation processes.
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 with a .xml file extension is also delivered to NSIDC with the HDF-EOS file, and it contains the same information as the core metadata. Three levels of QA are conducted with the AMSR-E Level 2 and 3 products: automatic, operational, and science. 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).
Access Constraints
You must register using the EOSDIS User Registration System in order to access LANCE NRT AMSR-E data. You can register at https://users.eosdis.nasa.gov/urs/.
GHRC User Services Office
Global Hydrology Resource Center (GHRC)
320 Sparkman Drive
City:
Huntsville
Province or State:
AL
Postal Code:
35805
Country:
USA
Publications/References
Conway, D. 2002. Advanced Microwave Scanning Radiometer - EOS Quality Assurance Plan. Huntsville, AL Global Hydrology and Climate Center.
Ferraro, R. R. 1997. SSM/I Derived Global Rainfall Estimates for Climatological Applications. Journal of Geophysical Research 102:16,715-16,735.
Ferraro, R. R. and G. F. Marks. 1995. The Development of SSM/I ... Rain Rate Retrieval Algorithms Using Ground Based Radar Measurements. Journal of Atmos. Oceanic Technology 12 755-770. Grody, N. C. 1991. Classification of Snow Cover and Precipitation Using the Special Sensor/Microwave Imager (SSM/I). Journal of Geophysical Research 96:7423-7435.
Kummerow, C., Y. Hong, W. S. Olson, S. Yang, R. F. Adler, J. McCollum, R. Ferraro, G. Petty, D. B. Shin, and T. T. Wilheit. 2001. The Evolution of the Goddard Profiling Algorithm (GPROF) for Rainfall Estimation from Passive Microwave Sensors. Journal of Applied Meteorology 40: 1801-1820.
Kummerow, C., W. Olson, and L. Giglio. 1996. The Evolution of the Goddard Profiling Algorithm (GPROF) for Rainfall Estimation from Passive Microwave Sensors. IEEE Transactions on Geosciences and Remote Sensing 34: 1213-1232.
McCollum, J., and R. Ferraro. 2003. Next Generation of NOAA/NESDIS TMI, SSM/I, and AMSR-E Microwave Land Rainfall Algorithms. Journal of Geophysical Research - Atmospheres 108(D8): art. no. 8382.
McCollum, J. R., A. Gruber, and M. B. Ba. 1999. Discrepancy between gauges and satellite estimates of rainfall in equatorial Africa. Journal Appl. Meteor 41 1065-1080.
Wilheit, T., C. Kummerow, and R. Ferraro. 2003. Rainfall algorithms for AMSR-E. IEEE Transactions on Geosciences and Remote Sensing 41(2): 204-214.
Kummerow, C., and R. Ferraro. 2007. Algorithm Theoretical Basis Document: EOS/AMSR-E Level-2 Rainfall. Fort Collins, Colorado, USA: Colorado State University. (View PDF File)
