Download Free Tropical Cyclone Position And Intensity Analysis Using Satellite Data Book in PDF and EPUB Free Download. You can read online Tropical Cyclone Position And Intensity Analysis Using Satellite Data and write the review.

In tropical cyclones, a strong inverse relationship exists between the magnitude of the upper-tropospheric warm anomaly (UTWA) and minimum sea level pressure (MSLP). Uniquely poised to capture this warming aloft, the Advanced Microwave Sounding Unit (AMSU) flown aboard current National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites is capable of observing Tropical Cyclones (TC's) worldwide. A physical/statistical MSLP estimation algorithm based on AMSU brightness temperature anomalies (dTbs) has been operating in an experimental mode at the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (UW-CIMSS) for two years. The algorithm relies on a single AMSU channel (54.9 GHz) and shows great promise as a viable TC analysis tool. However, the radiances can be susceptible to environmental variability leading to sub-sampling and errors in MSLP. The goal of this research is to improve the existing single-channel algorithm by introducing an additional channel (55.5 GHz) that seeks to capture the true magnitude of the UTWA in instances when the single channel fails. By implementing the multi-channel approach, the goal is to create an operationally viable satellite-based guidance tool to help support tropical forecast and analysis centers worldwide.
A spiral analysis technique is developed which quantifies the spiral patterns of cloud bands observed in IR satellite images of tropical cyclones. The technique utilizes the Navy's SPADS (Satellite Data Processing and Display System) minicomputer for processing the digital IR data. The technique consists of best fitting spherical-logarithmic spirals to tropical cyclone spiral cloud bands and performing multiple Fourier analyses of the radiance field along spirals orthogonal to the bands. Linear regression techniques are used to establish a relationship between spiral parameters derived from the Fourier analyses and tropical cyclone intensity. Algorithms for current intensity, and 12 and 24 h forecasts are developed. Tests on an independent data set show significant skill in estimating current intensity and in making 12 h forecasts. The most important predictors selected are presistence and parameters related to the dominant spiral signal and maximum IR count of the analyzed radiance field. Biases in the forecast algorithms suggest that other parameters are necessary to more accurately predict tropical cyclone intensity. The results, however, demonstrate the usefulness of the technique as an aid to tropical cyclone forecasters.
This proposed study examines the potential use of satellite passive microwave rainfall measurements derived from Special Sensor Microwave/Imager (SSM/I) radiometers onboard the Defense Meteorological Satellite Program (DMSP) constellation to improve eastern North Pacific Ocean tropical cyclone intensity change forecasting techniques. Relationships between parameters obtained from an operational SSM/I-based rainfall measuring algorithm and 12-, 24-, 36-, 48-, 60- and 72-hour intensity changes from best track data records are examined in an effort to identify statistically significant predictors of intensity change. Correlations between rainfall parameters and intensity change are analyzed using tropical cyclone data from three years, 1992 to 1994. Stratifications based upon tropical cyclone intensity, rate of intensity change, climatology, translation, landfall and synoptic-scale environmental forcing variables are studied to understand factors that may affect a statistical relationship between rainfall parameters and intensity change. The predictive skill of statistically significant rainfall parameters is assessed by using independent tropical cyclone data from another year, 1995. In addition, case studies on individual tropical cyclones are conducted to gain insight on predictive performance and operational implementation issues.