EOS PM-1 Advanced Microwave Scanning Radiometer (AMSR) Science Team Meeting
- Elena Lobl (elena.lobl@msfc.nasa.gov), Team Coordinator, Earth System Science Laboratory, University of Alabama in Huntsville
The second U.S. EOS PM-1 AMSR Science Team meeting was held 13 June 1996 at Goddard Space Flight Center. The agenda included hardware status from the EOS PM Project Office, and presentations on current research from team members. The afternoon was taken up by toolkit and HDF implementation discussions. C. Kummerow and F. Wentz showed a brief status of the Precipitation and Ocean Suite Algorithm Theoretical Basis Documents (ATBDs), for which they are the leads.
Roy Spencer started the meeting by welcoming the two new team members: Al Chang, GSFC, is developing the snow depth and snow water content algorithms; and Eni Njoku, JPL, is leading the land surface classification and surface wetness algorithm development. A short discussion about the ADEOS II AMSR Workshop revealed that our team representation would consist of Spencer, Chang, and Wentz, although all Team members were invited by NASDA to attend the workshop.
Bernie Graf, PM Project Office AMSR Instrument manager, reported on the EOS PM AMSR hardware status. Mitsubishi Electric Corporation (MELCO), the instrument builder, and TRW, the spacecraft vendor, have had an interface meeting, and agreed on the electrical interface and the power consumption; issues still exist with the thermal and mechanical subsystems. Frank Wentz, after defining the independent variables for retrieving brightness temperatures: salt water dielectric constant, wind-induced sea-surface emissivity, wind direction, oxygen absorption, water vapor, and liquid cloud and rain water absorption, discussed the ocean suite retrieval algorithm. The algorithm starts with an initial guess of the independent variable values, which are then used in an iterative process where the Sum of Squares (SOS), ratio of the square of the difference between the observed and the calculated TBs and the square of the noise temperatures, is minimized. With SSM/I data this process converges within 0.1 K in only four iterations. Peter Ashcroft, Remote Sensing Systems, is supporting F. Wentz in developing the Level-1c product algorithm. The first release of a simulated Level-1c data set is expected in March 1997; the data in this set will have real location information, but will have bogus TBs.
John Alishouse followed with some precipitation information obtained from SSM/I that can be used as verification data for the AMSR precipitation algorithm.
Don Cavalieri is working on improving current sea-ice algorithms and on developing new algorithms for extracting additional sea-ice information. Recent advances include the improved discrimination between sea-ice and weather effects and the development of two new sea-ice algorithms. Working with K. St. Germain at the University of Nebraska, a new method for deriving sea-ice temperature has been developed and is currently being tested using data from NOAA Arctic Ocean buoys and AVHRR imagery. The other new algorithm retrieves information on sea-ice drift. The technique is based on a wavelet analysis of SSM/I 85-GHz radiances. This work, being done in collaboration with A. Liu at Goddard Space Flight Center, is expected to provide daily sea-ice velocities for the entire Arctic and Antarctic regions.
Joey Comiso introduced his presentation with problem areas in validation. He also discussed the studies he is involved in for sea-ice concentration and type. The last topic presented from his research was the summer and perennial ice cover; he showed images of melt onset, meltponding, freeze-up, and a comparison between multiyear and summer ice cover.
C. Kummerow presented the 'Goddard profiling' (Gprof) precipitation retrieval algorithm, which will be the basis of the AMSR team precipitation algorithm. He discussed briefly the overall structure of this algorithm and showed the plan for its development, such as sensitivity to input models, convective/stratiform cloud separation, latent heating, and error modeling. Other data planned to be used are global microwave from SSM/I, localized experimental rainfall data from AMPR, geostationary IR data, and rain gauge data.
Al Chang presented his plan for retrieval of snow parameters using AMSR data. His algorithm will be an improved SMMR snow algorithm. From the inter-comparison studies conducted for snow cover and snow storage with ground observations, it was concluded that the SMMR algorithm underestimates the snow storage amount. Chang will make use of a Geographic Information System (GIS) to correct and improve this algorithm for use with the AMSR data.
Roy Spencer's research involves the temperature dependence of some of the AMSR retrievals. His work will point out any temperature cross-talk that the AMSR algorithms might have in time to correct the at-launch versions.
Two TRMM Science Data and Information System (TSDIS) members took most of the afternoon and discussed lessons learned from TRMM algorithm development.
The meeting closed with a tour of the laboratory where the TRMM spacecraft (including the TRMM Microwave Imager) is tested. The next AMSR meeting will be at the end of October, shortly before the ATBDs are due to the Project Science Office (November 15, 1996).
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