While the standard wind product (L2B) available operationally in near-real time from SeaWinds on QuikSCAT is only 25 km in resolution, QuikSCAT data can be enhanced to yield a 2.5 km ultra-high resolution (UHR) product. The latter can be used to help estimate Tropical Cyclone (TC) characteristics such as TC eye center and wind radii. Two studies are conducted in this thesis, in which QuikSCAT UHR wind product's effectiveness in estimating these TC characteristics is evaluated. First, a comparison is made between the analyst's choice of eye location based on UHR images and interpolated best-track position. In this analysis, the UHR images are divided into two categories, based on the analyst's confidence level of finding the eye center location. In each category, statistical error quantities are computed. UHR images within the high confidence category can provide, for a given year and basin, mean error distance as small as 19 km with a 10 km standard deviation. Second, a visual comparison of QuikSCAT's performance in estimating wind radii is made. QuikSCAT's performance is gauged against H*wind dataset and the Extended Best-Track (EBT) dataset. Results show that QuikSCAT UHR data yields a correct 34-kt wind radius most of the time regardless of the TC category when compared to both H*wind and EBT, whereas the 50- and 64-kt wind radii visual estimates do not always agree with H*wind and EBT. A more sophisticated method is also implemented to automatically estimate wind radii based on a model fit to QuikSCAT data. Results from this method are compared with EBT wind radii. Wind radii obtained from QuikSCAT model fit are generally highly correlated with EBT estimated wind radii. These two studies show that QuikSCAT UHR wind products are helpful in estimating TC eye location and wind radii, thus improving TC forecasting and analysis.