A surface-precipitation-rate retrieval algorithm for 13-channel Advanced Microwave Sounding Unit (AMSU) millimeter-wave spectral observations from 23 to 191 GHz is described. It was trained using cloudresolving fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) simulations over 106 global storms. The resulting retrievals from the U.S. N...

Precipitation is the meteorological parameter affecting people in the most direct way. Forecasting the spatial and temporal distribution of rain and snow is therefore one of the major challenges for the meteorological services. Satellite remote sensing of precipitation could help to improve these forecasts. The most direct method to retrieve precipitation from spaceborne measurements is based o...

This thesis describes the use of opaque microwave bands for global estimation of precipitation rate. An algorithm was developed for estimating instantaneous precipitation rate for the Advanced Microwave Sounding Unit (AMSU) on the NOAA-15, NOAA-16, and NOAA-17 satellites, and the Advanced Microwave Sounding Unit and Humidity Sounder for Brazil (AMSU/HSB) aboard the NASA Aqua satellite. The algo...

A methodology is described to construct fully parametric rainfall retrieval algorithms for a variety of passive microwave sensors that exist today and are planned for the future. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is used to retrieve nonraining geophysical parameters. The method then blends these background geophysical parameters with three-dimensional precipi...

The formulation and testing of an enhanced Statistical Hurricane Intensity Prediction Scheme (SHIPS) using new predictors derived from passive microwave imagery is presented. Passive microwave imagery is acquired for tropical cyclones in the Atlantic and eastern North Pacific basins between 1995 and 2003. Predictors relating to the inner-core (within 100 km of center) precipitation and convecti...

Satellite remote sensing is an indispensable means of measuring and monitoring precipitation on a global scale. The Tropical Rainfall Measuring Mission (TRMM) is continuing to make significant progress in helping the global features of precipitation to be understood, particularly with the help of a pair of spaceborne microwave sensors, the TRMM Microwave Imager (TMI) and precipitation radar (PR...

This study examines the spatial and temporal variability in the diurnal cycle of clouds and precipitation tied to topography within the North American Monsoon Experiment (NAME) tier-I domain during the 2004 NAME enhanced observing period (EOP, July–August), with a focus on the implications for highresolution precipitation estimation within the core of the monsoon. Ground-based precipitation ret...

Understanding the characteristics of cloud microphysics in precipitation is important to enable accurate rainfall estimation through space-borne radar and microwave radiometers on satellites (e.g., TRMM, GPM, and AMSR-E) (e.g., Masunaga et al. 2002). One basic need is clarification of the differences in cloud microphysical characteristics, such as the drop size distribution (DSD), in convective...

The images acquired by microwave sensors are blurry and have low resolution. On the other hand, the images obtained using infrared/visible sensors are often of higher resolution. In this paper, we develop a data fusion methodology and apply it to enhance the resolution of a microwave image using the data from a collocated infrared/visible sensor. Such an approach takes advantage of the spatial ...

This paper describes a new high-resolution multi-platform multi-sensor satellite rainfall product for Southern Africa covering the period 1993-2002. The Microwave Infra-Red Algorithm (MIRA) employed to generate the rainfall estimates combines high spatial and temporal resolution Meteosat infrared data with infrequent Special Sensor Microwave Imager (SSM/I) overpasses. A transfer function relati...