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.

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.

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.