Precipitation is a dominating quantity in microwave radiometry. The large emission and scattering signals of rain and ice, respectively, introduce large contributions to the measured brightness temperature. While this allows for accurate sensing of precipitation, it also results in degraded performance when retrieving other geophysical parameters, such as near-surface ocean winds. In particular, the retrieval of wind direction requires precise knowledge of polarization, and nonspherical particles can result in a change in the polarization of incident radiation. The aim of this dissertation is to investigate the polarizing effects of precipitation in the atmosphere, including the existence of a precipitation signal in the third Stokes parameter, and compare these effects with the current sensitivities of passive wind vector retrieval algorithms. Realistic simulated precipitation profiles give hydrometeor water contents which are input into a vector radiative transfer model. Brightness temperatures are produced within the model using a reverse Monte Carlo method. Results are produced at three frequencies of interest to microwave polarimetry, 10.7 GHz, 18.7 GHz, and 37.0 GHz, for the first 3 components of the Stokes vector.

The removal of systematic brightness temperature (Tb) biases is necessary when producing decadal passive microwave data sets for weather and climate research. It is crucial to achieve Tb measurement consistency among all satellites in a constellation as well as to maintain sustained calibration accuracy over the lifetime of each satellite sensor. In-orbit inter-satellite radiometric calibration techniques provide a long term, group-wise solution; however, since radiometers operate at different frequencies and viewing angles, Tb normalizations are made before making intermediate comparisons of their near-simultaneous measurements. In this dissertation, a new approach is investigated to perform these normalizations from one satellite's measurements to another. It uses Taylor's series expansion around a source frequency to predict Tb of a desired frequency. The relationship between Tb's and frequencies are derived from simulations using an oceanic Radiative Transfer Model (RTM) over a wide variety of environmental conditions. The original RTM is built on oceanic radiative transfer theory. Refinements are made to the model by modifying and tuning algorithms for calculating sea surface emission, atmospheric emission and attenuations. Validations were performed with collocated WindSat measurements. This radiometric calibration approach is applied to establish an absolute brightness temperature reference using near-simultaneous pair-wise comparisons between a non-sun synchronous radiometer and two sun-synchronous polar-orbiting radiometers: the Tropical Rain Measurement Mission (TRMM) Microwave Imager (TMI), WindSat (on Coriolis) and Advanced Microwave Scanning Radiometer (AMSR) on Advanced Earth Observing System -II (ADEOSII), respectively. Collocated measurements between WindSat and TMI as well as between AMSR and TMI, within selected 10 weeks in 2003 for each pair, are collected, filtered and applied in the cross calibration. AMSR is calibrated to WindSat using TMI as a transfer standard. Accuracy prediction and error source analysis are discussed along with calibration results. This inter-satellite radiometric calibration approach provides technical support for NASA's Global Precipitation Mission which relies on a constellation of cooperative satellites with a variety of microwave radiometers to make global rainfall measurements.

After the launch of NASA's SeaWinds scatterometer in 1999, a radiometer function was implemented in the Science Ground Data Processing Systems to allow the measurement of the earth's microwave brightness temperature. This dissertation presents results of a comprehensive validation to assess the quality of QRad brightness temperature measurements using near-simultaneous ocean Tb comparisons between the SeaWinds on QuikSCAT (QRad) and WindSat polarimetric radiometer on Coriolis. WindSat was selected because it is a well calibrated radiometer that has many suitable collocations with QuikSCAT; and it has a 10.7 GHz channel, which is close to QRad frequency of 13.4 GHz. Brightness temperature normalizations were made for WindSat before comparison to account for expected differences in Tb with QRad because of incidence angle and channel frequency differences. Brightness temperatures for nine months during 2005 and 2006 were spatially collocated for rain-free homogeneous ocean scenes (match-ups) within 1° latitude x longitude boxes and within a ± 60 minute window. To ensure high quality comparison, these collocations were quality controlled and edited to remove non-homogenous ocean scenes and/or transient environmental conditions, including rain contamination. WindSat and QRad Tb's were averaged within 1° boxes and these were used for the radiometric inter-calibration analysis on a monthly basis. Results show that QRad calibrations are stable in the mean within ± 2K over the yearly seasonal cycle.

Microwave radiometers are highly sensitive receivers capable of measuring low levels of natural blackbody microwave emissions. Remote sensing by satellite microwave radiometers flying on low-earth, polar orbiting, satellites can infer a variety of terrestrial and atmospheric geophysical parameters for scientific and operational applications, such as weather and climate prediction. The objective of this thesis is to provide realistic simulated ocean brightness temperatures for the 3-channel Microwave Radiometer (MWR), which will be launched in May 2010 on the joint NASA/CONAE Aquarius/SAC-D Mission. These data will be used for pre-launch geophysical retrieval algorithms development and validation testing. Analyses are performed to evaluate the proposed MWR measurement geometry and verify the requirements for spatial/temporal sampling. Finally, a preliminary study is performed for the post-launch inter-satellite radiometric calibration using the WindSat polarimetric radiometer on the Coriolis satellite.