An Ocean Surface Wind Vector Model Function For A Spaceborne Microwave Radiometer And Its Application

Ocean surface wind vectors over the ocean present vital information for scientists and forecasters in their attempt to understand the Earth\u27s global weather and climate. As the demand for global wind velocity information has increased, the number of satellite missions that carry wind-measuring sensors has also increased; however, there are still not sufficient numbers of instruments in orbit today to fulfill the need for operational meteorological and scientific wind vector data. Over the last three decades operational measurements of global ocean wind speeds have been obtained from passive microwave radiometers. Also, vector ocean surface wind data were primarily obtained from several scatterometry missions that have flown since the early 1990\u27s. However, other than SeaSat-A in 1978, there has not been combined active and passive wind measurements on the same satellite until the launch of the second Advanced Earth Observing Satellite (ADEOS-II) in 2002. This mission has provided a unique data set of coincident measurements between the SeaWinds scatterometer and the Advanced Microwave Scanning Radiometer (AMSR). AMSR observes the vertical and horizontal brightness temperature (TB) at six frequency bands between 6.9 GHz and 89.0 GHz. Although these measurements contain some wind direction information, the overlying atmospheric influence can easily obscure this signal and make wind direction retrieval from passive microwave measurements very difficult. However, at radiometer frequencies between 10 and 37 GHz, a certain linear combination of vertical and horizontal brightness temperatures causes the atmospheric dependence to be nearly cancelled and surface parameters such as wind speed, wind direction and sea surface temperature to dominate the resulting signal. This brightness temperature combination may be expressed as ATBV-TBH, where A is a constant to be determined and the TBV and TBH are the brightness temperatures for the vertical and horizontal polarization respectively. In this dissertation, an empirical relationship between the AMSR\u27s ATBV-TBH and SeaWinds\u27 surface wind vector retrievals was established for three microwave frequencies: 10, 18 and 37 GHz. This newly developed model function for a passive microwave radiometer could provide the basis for wind vector retrievals either separately or in combination with scatterometer measurements

Inter-satellite Microwave Radiometer Calibration

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\u27s measurements to another. It uses Taylor\u27s series expansion around a source frequency to predict Tb of a desired frequency. The relationship between Tb\u27s 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\u27s Global Precipitation Mission which relies on a constellation of cooperative satellites with a variety of microwave radiometers to make global rainfall measurements

Evaluation Of A Microwave Radiative Transfer Model For Calculating Sat

Remote sensing is the process of gathering and analyzing information about the earth\u27s ocean, land and atmosphere using electromagnetic wireless techniques. Mathematical models, known as Radiative Transfer Models (RTM), are developed to calculate the observed radiance (brightness temperature) seen by the remote sensor. The RTM calculated brightness temperature is a function of fourteen environmental parameters, including atmospheric profiles of temperature, pressure and moisture, sea surface temperature, and cloud liquid water. Input parameters to the RTM model include data from NOAA Centers for Environmental Prediction (NCEP), Reynolds weekly Sea Surface Temperature and National Ocean Data Center (NODC) WOA98 Ocean Salinity and special sensor microwave/imager (SSM/I) cloud liquid water. The calculated brightness temperatures are compared to collocated measurements from the WindSat satellite. The objective of this thesis is to fine tune the RadTb model, using simultaneous environmental parameters and measured brightness temperature from the well-calibrated WindSat radiometer. The model will be evaluated at four microwave frequencies (6.8 GHz, 10.7 GHz, 18.7 GHz, and 37.0 GHz) looking off- nadir for global radiance measurement