Determining Selected Tropical Cyclone Characteristics Using QuikSCAT's Ultra-High Resolution Images

Operational SeaWinds on QuikSCAT data can be enhanced to yield a 2.5 km ultra-high resolution (UHR) wind product, which can be used to help estimate tropical cyclone (TC) characteristics such as TC center and wind radii. This paper provides the results of two studies in which the QuikSCAT UHR wind product's effectiveness in estimating these TC characteristics is evaluated. First, a comparison is made between an analyst's choice of center 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 center location. In each category, statistical error quantities between the analyst's choice of center location and interpolated best track location 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 comparison of QuikSCAT's performance in estimating wind radii is made. QuikSCAT's performance is gauged against the H*wind dataset and the extended best track (EBT) dataset. Results show that QuikSCAT UHR data yields the 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 kt and 64 kt wind radii estimates do not always agree with H*wind and EBT. A more sophisticated method is implemented to automatically estimate wind radii based on a model fit to QuikSCAT data. Results from this method are compared with EBT wind radii. The 50 kt and 64 kt wind radii obtained from QuikSCAT model fit are generally highly correlated with EBT estimated wind radii.