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.

Accurate tropical cyclone (TC) intensity estimates are best achieved from satellite observations. The Advanced Microwave Sounding Unit (AMSU) has operated since 1998 on polar-orbiting environmental satellites and is able to measure the warm temperature anomaly in the upper troposphere above a TC's center. Through hydrostatic equilibrium, this warm anomaly is roughly proportional to the TC's sea-level pressure anomaly. Based on this principle, the Cooperative Institute for Meteorological Satellite Studies (CIMSS) provides near real-time AMSU-based estimates of TC minimum sea-level pressure (MSLP) to forecast centers worldwide. These estimates are as accurate as the benchmark Dvorak technique, but are subject to error caused by precipitation effects (primarily brightness temperature reduction by scattering) on the AMSU 55 GHz channels sensitive to upper-tropospheric temperature. Simulated AMSU brightness temperatures (TB's) are produced by a polarized reverse Monte Carlo radiative transfer model using representative TC precipitation profiles. Results suggest that precipitation depression of high-frequency window channel TB's is correlated with depression of sounding channel TB's and can be used to correct for scattering effects on the AMSU channels used in TC intensity estimates. Analysis of AMSU data over the tropical oceans confirms this, and forms the basis for an empirical scattering correction using AMSU 31 and 89 GHz TB's. This scattering correction reduces CIMSS TC MSLP algorithm RMS error by 10% in a 7-year, 497 observation sample.

Remote Sensing of Aerosols, Clouds, and Precipitation compiles recent advances in aerosol, cloud, and precipitation remote sensing from new satellite observations. The book examines a wide range of measurements from microwave (both active and passive), visible, and infrared portions of the spectrum. Contributors are experts conducting state-of-the-art research in atmospheric remote sensing using space, airborne, and ground-based datasets, focusing on supporting earth observation satellite missions for aerosol, cloud, and precipitation studies. A handy reference for scientists working in remote sensing, earth science, electromagnetics, climate physics, and space engineering. Valuable for operational forecasters, meteorologists, geospatial experts, modelers, and policymakers alike. - Presents new approaches in the field, along with further research opportunities, based on the latest satellite data - Focuses on how remote sensing systems can be designed/developed to solve outstanding problems in earth and atmospheric sciences - Edited by a dynamic team of editors with a mixture of highly skilled and qualified authors offering world-leading expertise in the field

The National Oceanic and Atmospheric Administration (NOAA) uses precipitation data in many applications including hurricane forecasting. Currently, NOAA uses data collected from the Tropical Rainfall Measuring Mission (TRMM) satellite that was launched in 1997 by NASA in cooperation with the Japan Aerospace Exploration Agency. NASA is now making plans to launch the Global Precipitation Measurement (GPM) mission in 2013 to succeed TRMM, which was originally intended as a 3 to 5 year mission but has enough fuel to orbit until 2012. The GPM mission consists of a "core" research satellite flying with other "constellation" satellites to provide global precipitation data products at three-hour intervals. This book is the second in a 2-part series from the National Research Council on the future of rainfall measuring missions. The book recommends that NOAA begin its GPM mission preparations as soon as possible and that NOAA develop a strategic plan for the mission using TRMM experience as a guide. The first book in the series, Assessment of the Benefits of Extending the Tropical Rainfall Measuring Mission (December 2004), recommended that the TRMM mission be extended as long as possible because of the quality, uniqueness, and many uses of its data. NASA has officially extended the TRMM mission until 2009.