NASA Scientific and Technical Aerospace Reports

for the largest term in the series. Since the l950s the improvement in the measurement of the motion of the Earth’s pole have
made its observation a powerful probe of the structure of the Earth.
DTIC
Earth Core; Nutation; Precession; Rigid Structures
20040120981 NASA Goddard Space Flight Center, Greenbelt, MD, USA
EOS Aqua AMSR-E Arctic Sea Ice Validation Program: Arctic2003 Aircraft Campaign Flight Report
Cavalieri, D. J.; Markus,T.; September 2003; 44 pp.; In English
Report No.(s): NASA/TM-2003-212247; Rept-2003-02602-0; No Copyright; Avail: CASI; A03, Hardcopy
In March 2003 a coordinated Arctic sea ice validation field campaign using the NASA Wallops P-3B aircraft was
successfully completed. This campaign was part of the program for validating the Earth Observing System (EOS) Aqua
Advanced Microwave Scanning Radiometer (AMSR-E) sea ice products. The AMSR-E, designed and built by the Japanese
National Space Development Agency for NASA, was launched May 4, 2002 on the EOS Aqua spacecraft. The AMSR-E sea
ice products to be validated include sea ice concentration, sea ice temperature, and snow depth on sea ice. This flight report
describes the suite of instruments flown on the P-3, the objectives of each of the seven flights, the Arctic regions overflown,
and the coordination among satellite, aircraft, and surface-based measurements. Two of the seven aircraft flights were
coordinated with scientists making surface measurements of snow and ice properties including sea ice temperature and snow
depth on sea ice at a study area near Barrow, AK and at a Navy ice camp located in the Beaufort Sea. Two additional flights
were dedicated to making heat and moisture flux measurements over the St. Lawrence Island polynya to support ongoing
air-sea-ice processes studies of Arctic coastal polynyas. The remaining flights covered portions of the Bering Sea ice edge, the
Chukchi Sea, and Norton Sound.
Author
Arctic Regions; Air Sea Ice Interactions; Heat Flux; Sea Ice; Snow; Surface Properties
20040121122 NASA Marshall Space Flight Center, Huntsville, AL, USA
Evaluation of the AMSR-E Data Calibration Over Land
Njoku, E.; Chan, T.; Crosson, W.; Limaye, A.; [2004]; 1 pp.; In English; No Copyright; Avail: Other Sources; Abstract Only
Land observations by the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E),
particularly of soil and vegetation moisture changes, have numerous applications in hydrology, ecology and climate.
Quantitative retrieval of soil and vegetation parameters relies on accurate calibration of the brightness temperature
measurements. Analyses of the spectral and polarization characteristics of early versions of the AMSR-E data revealed
significant calibration biases over land at 6.9 GHz. The biases were estimated and removed in the current archived version
of the data Radiofrequency interference (RFI) observed at 6.9 GHz is more difficult to quanti@ however. A calibration analysis
of AMSR-E data over land is presented in this paper for a complete annual cycle from June 2002 through September 2003.
The analysis indicates the general high quality of the data for land applications (except for RFI), and illustrates seasonal trends
of the data for different land surface types and regions.
Author
Microwave Radiometers; Land; Scanners; Earth Observing System (EOS); Data Acquisition; Calibrating
20040121126 NASA Marshall Space Flight Center, Huntsville, AL, USA
Landcover Based Optimal Deconvolution of PALS L-band Microwave Brightness Temperature
Limaye, Ashutosh S.; Crosson, William L.; Laymon, Charles A.; Njoku, Eni G.; [2004]; 1 pp.; In English; No Copyright;
Avail: Other Sources; Abstract Only
An optimal de-convolution (ODC) technique has been developed to estimate microwave brightness temperatures of
agricultural fields using microwave radiometer observations. The technique is applied to airborne measurements taken by the
Passive and Active L and S band (PALS) sensor in Iowa during Soil Moisture Experiments in 2002 (SMEX02). Agricultural
fields in the study area were predominantly soybeans and corn. The brightness temperatures of corn and soybeans were
observed to be significantly different because of large differences in vegetation biomass. PALS observations have significant
over-sampling; observations were made about 100 m apart and the sensor footprint extends to about 400 m. Conventionally,
observations of this type are averaged to produce smooth spatial data fields of brightness temperatures. However, the
conventional approach is in contrast to reality in which the brightness temperatures are in fact strongly dependent on
landcover, which is characterized by sharp boundaries. In this study, we mathematically de-convolve the observations into
brightness temperature at the field scale (500-800m) using the sensor antenna response function. The result is more accurate
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