This volume focuses on the topic of precipitation retrieval from passive microwave(PMW) satellite measurements and the progress that has been made in this area throughtwo internationally sanctioned intercomparison programs: the Precipitation Intercom-parisonProject (PIP) established within the National Aeronautical and Space Admin-istration'sWetNet Project, and the Algorithm Intercomparison Project (AIP) establishedas part of the Global Precipitation Climatology Project. Papers in this issue developedas an outgrowth of these projects, primarily from the second WetNet PIP, but also fromthe third AIP. Along with other things, both these projects stressed the intercomparisonof a number of satellite precipitation algorithms designed for use with measurementsfrom the Special Sensor Microwave/Imagers (SSM/Is) flown on Defense MeteorlogicalSatellite Program (DMSP) satellites.The Journal of the Atmospheric Sciences (JAS) has been chosen as a forum for thiscollection of papers because it is now evident that the PMW methodology of detectingrain and quantifying rain rate has matured to the point where we are able to makefundamental discoveries about precipitation on various scales that have been heretoforebeyond reach based on conventional measuring systems. Moreover, since many of therain algorithms are explicitly based on radiative transfer and cloud models of the at-mosphere,the algorithms themselves have become an integral part of mainstream at-mosphericscience. In this context, the expectation of making new discoveries concerningtropical latent heating processes, the role of low-latitude diabatic heating in forcingglobal circulation patterns, and the basic global climatological nature of precipitationwere the motivating factors behind the development of the joint U.S.–Japan TropicalRainfall Measuring Mission (TRMM), a newly launched satellite experiment that wentinto space on Thanksgiving Day, 27 November 1997.Therefore, although precipitation remote sensing has not been a major topic area forJAS in the past, there is now sufficient evidence that passive microwave remote sensingof rain and other hydrological variables can produce new knowledge about atmosphericbehavior. From this perspective, this special issue provides an opportunity for JAS readersto examine a possibly unfamiliar subject and to broaden their horizons in an area thathas become increasingly important in atmospheric science research.There are two basic categories of papers in this volume. The first involves studiesthat focus on the results, data, or general methods associated with the PIP-2 and AIP-3intercomparison projects. The second involves studies that examine the underlyingphysical principles of the subject of passive microwave sensing of rain. There are sixpapers that belong to the first category. Smith et al. and Ebert and Manton provide theresults summarizations on PIP-2 and AIP-3 projects, respectively. Berg et al. reviewthe performance of the first and second generation U.S. Navy operational SSM/I al-gorithms(D-Matrix and Cal/Val), which were important operational milestones in theearly days of SSM/I. The Kidd et al. paper adroitly tackles the oftentimes contentioussubject of the merits of statistical algorithms versus physical algorithms, and providesa provocative justification why the statistical approach is still a valid recourse in seekingto estimate rainfall. The Ferraro et al. paper addresses a specialized topic within satelliteprecipitation retrieval, the problem of precipitation detection (or screening in the lexiconof the algorithm developers), and describes straightforward methods to solve this prob-lemfor different types of oceanic and continental surfaces, methods that were developedfor the SSM/I operational rain algorithm at the National Environmental Satellite DataInformation Service. Finally in the first category of papers, Ritchie et al. examine the nature of differences that can be found in the various sources of SSM/I data, a particularlyimportant subject when trying to establish climate benchmarks from satellite datasets.In the second category of papers, Wentz and Spencer describe a new algorithmapproach that offers a consistent and systematic means to simultaneously retrieve surfacewind speed, water vapor, cloud liquid water, and precipitation from SSM/I measurementswithin a unified physical framework. Liu and Curry describe the basic slope relationshipbetween the low-frequency emission signature and the high-frequency scattering sig-naturefor different precipitation regimes as a means to better categorize different typesof precipitation and their climatological nature. Panegrossi et al. describe a detailedanalysis concerning the necessity for consistency in the measurement–model brightnesstemperature manifolds that arise with physical algorithms whose microphysical under-pinningsare derived from cloud model outputs of vertical hydrometeor profiles. Tesmerand Wilheit describe a new PMW cloud radiation model, based on recent microphysicalobservations available from the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) and designed to improve brightnesstemperature–rain rate relationships used in PMW precipitation algorithms. Turk et al.examine how spatial resolution degradation impacts the interpretation of the rain signalbased on analysis of high-resolution aircraft radiometer and radar measurements obtainedduring TOGA COARE. Spencer et al. investigate the properties of the rain and icesignals in SSM/I measurements after the 1991 eruption of Mount Pinatubo and theconcomitant cooling of SSTs and tropospheric temperatures, arguing the existence of afeedback link between the general thermodynamic state of the atmosphere and precip-itationefficiency. Finally, Bauer et al. explore the possibilities of combined optical–infrared–microwave algorithms in the context of the TRMM experiment, seeking im-provedways to overcome spatial resolution limitations in the PMW measurements.This is an exciting era for passive microwave-based remote sensing. As research onthe global hydrological cycle begins to accelerate, this type of measurement, treatedcarefully, can be used to detect much of the atmospheric water cycle process. In thenext era of satellites, in which PMW radiometers will have increased spatial resolution,better signal to noise properties, and more frequency diversity, and in which activecloud and precipitation radars will be used in conjunction with the advanced radiometers,analysis of the global water cycle will become highly dependent upon the satellitealgorithms used to transform radiation measurements into physical variables. The authorsof this volume hope these papers help elucidate some of the important concepts andmethods that will be used in these algorithms, as well as describing the current stateof the art in PMW precipitation retrieval science.