Alberto Mugnai

Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. I: Brightness-temperature properties of a time-dependent cloud-radiation model

Abstract A cloud-radiation model is used to investigate the relationship between emerging microwave brightness temperatures (TBs) and vertically distributed mixtures of liquid and frozen hydrometeors as a means to establish the framework for a hybrid statistical-physical rainfall retrieval algorithm. The focus in this study is on the microwave characteristics of an intense hailstorm in which cold-rain microphysics dominate the precipitation process. The TB calculations exhibit a high degree of intercorrelation across a wide frequency range (15–128 GHz) due to the pervasive influence of large ice particles on attenuation of upwelling radiation emerging from the rain layers. When the radiative emission source is near blackbody, fluctuations of the mixing ratios of ice particles are wholly responsible for the TB variations, as opposed to fluctuations in the cloud-or raindrop mixing ratios. Supercooled cloud drops, suspended in the graupel layers, can exert influence on the TBs but only at the higher freque...

Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. II - Emission-source and generalized weighting-function properties of a time-dependent cloud-radiation model

Abstract We present the second part of a study on the development of a framework for precipitation retrieval from space-based passive microwave measurements using a three-dimensional time-dependent cloud model to establish the microphysical setting. We first develop the theory needed to interpret the vertically distributed radiative sources and the emission-absorption-scattering processes responsible for the behavior of frequency-dependent top-of-atmosphere brightness temperatures TBs. This involves two distinct types of vertical weighting functions for the TBs: an emission-source weighing function describing the origin of emitted radiation that eventually reaches a satellite radiometer, and a generalized weighting function describing emitted-scattered radiation undergoing no further interactions prior to interception by the radiometer. The weighting-function framework is used for an analysis of land-based precipitation processes within a hail-storm simulation originally described in Part I. The individ...

Results of WetNet PIP-2 Project

The second WetNet Precipitation Intercomparison Project (PIP-2) evaluates the performance of 20 satellite precipitation retrieval algorithms, implemented for application with Special Sensor Microwave/Imager (SSM/I) passive microwave (PMW) measurements and run for a set of rainfall case studies at full resolution‐instantaneous space‐timescales. The cases are drawn from over the globe during all seasons, for a period of 7 yr, over a 608N‐ 178S latitude range. Ground-based data were used for the intercomparisons, principally based on radar measurements but also including rain gauge measurements. The goals of PIP-2 are 1) to improve performance and accuracy of different SSM/I algorithms at full resolution‐instantaneous scales by seeking a better understanding of the relationship between microphysical signatures in the PMW measurements and physical laws employed in the algorithms; 2) to evaluate the pros and cons of individual algorithms and their subsystems in order to seek optimal ‘‘front-end’’ combined algorithms; and 3) to demonstrate that PMW algorithms generate acceptable instantaneous rain estimates. It is found that the bias uncertainty of many current PMW algorithms is on the order of 630%. This level is below that of the radar and rain gauge data specially collected for the study, so that it is not possible to objectively select a best algorithm based on the ground data validation approach. By decomposing the intercomparisons into effects due to rain detection (screening) and effects due to brightness temperature‐rain rate conversion, differences among the algorithms are partitioned by rain area and rain intensity. For ocean, the screening differences mainly affect the light rain rates, which do not contribute significantly to area-averaged rain rates. The major sources of differences in mean rain rates between individual algorithms stem from differences in how intense rain rates are calculated and the maximum rain rate allowed by a given algorithm. The general method of solution is not necessarily the determining factor in creating systematic rain-rate differences among groups of algorithms, as we find that the severity of the screen is the dominant factor in producing systematic group differences among land algorithms, while the input channel selection is the dominant factor in producing systematic group differences among ocean algorithms. The significance of these issues are examined through what is called ‘‘fan map’’ analysis. The paper concludes with a discussion on the role of intercomparison projects in seeking improvements to algorithms, and a suggestion on why moving beyond the ‘‘ground truth’’ validation approach by use of a calibration-quality forward model would be a step forward in seeking objective evaluation of individual algorithm performance and optimal algorithm design.

International Global Precipitation Measurement (GPM) Program and Mission: An Overview

Eric A. Smith , Ghassem Asrar , Yoji Furuhama , Amnon Ginati , Christian Kummerow , Vincenzo Levizzani , Alberto Mugnai , Kenji Nakamura , Robert Adler , Vincent Casse , Mary Cleave , Michele Debois , John Durning , Jared Entin , Paul Houser , Toshio Iguchi , Ramesh Kakar , Jack Kaye , Masahiro Kojima , Dennis Lettenmaier , Michael Luther , Amita Mehta , Pierre Morel , Tetsuo Nakazawa , Steven Neeck , Ken’ichi Okamoto , Riko Oki , Garudachar Raju , Marshall Shepherd , Erich Stocker , Jacques Testud , and Eric Wood 19

Use of Cloud Model Microphysics for Passive Microwave-Based Precipitation Retrieval: Significance of Consistency between Model and Measurement Manifolds

Precipitation estimation from passive microwave radiometry based on physically based profile retrieval algorithms must be aided by a microphysical generator providing structure information on the lower portions of the cloud, consistent with the upper-cloud structures that are sensed. One of the sources for this information is mesoscale model simulations involving explicit or parameterized microphysics. Such microphysical information can be then associated to brightness temperature signatures by using radiative transfer models, forming what are referred to as cloud‐radiation databases. In this study cloud‐radiation databases from three different storm simulations involving two different mesoscale models run at cloud scales are developed and analyzed. Each database relates a set of microphysical profile realizations describing the space‐time properties of a given precipitating storm to multifrequency brightness temperatures associated to a measuring radiometer. In calculating the multifrequency signatures associated with the individual microphysical profiles over model space‐time, the authors form what are called brightness temperature model manifolds. Their dimensionality is determined by the number of frequencies carried by the measuring radiometer. By then forming an analogous measurement manifold based on the actual radiometer observations, the radiative consistency between the model representation of a rain cloud and the measured representation are compared. In the analysis, the authors explore how various microphysical, macrophysical, and environmental factors affect the nature of the model manifolds, and how these factors produce or mitigate mismatch between the measurement and model manifolds. Various methods are examined that can be used to eliminate such mismatch. The various cloud‐radiation databases are also used with a simplified profile retrieval algorithm to examine the sensitivity of the retrieved hydrometeor profiles and surface rainrates to the different microphysical, macrophysical, and environmental factors of the simulated storms. The results emphasize the need for physical retrieval algorithms to account for a number of these factors, thus preventing biased interpretation of the rain properties of precipitating storms, and minimizing rms uncertainties in the retrieved quantities.

Bayesian estimation of precipitating cloud parameters from combined measurements of spaceborne microwave radiometer and radar

The objective of this paper is to evaluate the potential of a Bayesian inversion algorithm using microwave multisensor data for the retrieval of surface rainfall rate and cloud parameters. The retrieval scheme is based on the maximum a posteriori probability (MAP) method, extended for the use of both spaceborne passive and active microwave data. The MAP technique for precipitation profiling is also proposed to approach the problem of the radar-swath synthetic broadening; that is, the capability to exploit the combined information also where only radiometric data are available. In order to show an application to airborne data, two case studies are selected within the Tropical Ocean-Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE). They refer to a stratiform storm region and an intense squall line of two mesoscale convective systems, which occurred over the ocean on February 20 and 22, 1993, respectively. The estimated rainfall rates and columnar hydrometeor contents derived from the proposed algorithms are compared to each other and to radar estimates based on reflectivity-rainrate (Z-R) relationships. Results in terms of reflectivity profiles and upwelling brightness temperatures, reconstructed from the estimated cloud structures, are also discussed. A database of combined measurements acquired at nadir during various TOGA-COARE flights, is used for applying the radar-swath synthetic broadening technique in the case of an along-track radar-failure countermeasure. A simulated test of the latter technique is performed using the case studies of February 20 and 22, 1993.

Algorithms for the Retrieval of Rainfall from Passive Microwave Measurements.

The retrieval of rainfall intensity from radiances measured by spaceborne microwave radiometers can be understood in terms of well established physics. At frequencies below about 40 GHz over an ocean background the relationship between the rainfall and the observations is particularly well understood. In this part of the spectrum, the radiances are principally determined by the liquid hydrometeors with only a modest amount of ambiguity. In very intense convection, ice aloft may increase this ambiguity somewhat. At high frequencies, such as the 85.5 GHz channel of the SSM/I, scattering by the frozen hydrometeors becomes more significant and quantitative rainfall retrieval becomes more problematic. In spite of the ambiguities, the use of the higher frequencies is desirable on a number of counts including: applicability over land, spatial resolution and dynamic range. A total of 16 algorithms were submitted for the PIP‐1. These include algorithms that are based on high frequency (scattering) measurements and low frequency (emission) measurements with a few combinations and variations on these themes. The calibration of the algorithms varies from mostly empirical to essentially first principles with most falling somewhere in‐between. All of the algorithms retrieved rainfall and one also retrieved a profile of the liquid and frozen hydrometeors.

Simulation of Microwave Brightness Temperatures of an Evolving Hailstorm at SSM/I Frequencies

A simulation of the appearance of an intense hailstorm in the passive microwave spectrum is conducted in order to characterize the vertical sources of radiation that contribute to the top-of-atmosphere microwave brightness temperatures (TB) which can be measured by satellite-borne radiometers. The study focuses on four frequencies corresponding to those used on the USAF Special Sensor Microwave Imager (SSM/I), a recently launched payload flown on the U.S. Air Force DMSP satellites. Computation of the microwave brightness temperatures is based on a vertically, angularly, and spectrally detailed radiative transfer scheme that has been applied to the highly resolved thermodynamical and microphysical output from the three-dimensional Colorado State University (CSU) Regional Atmospheric Modeling System (RAMS). The RAMS model was used to carry out a 4-h simulation of an intense hailstorm that occurred on 11 July 1986 in the vicinity of Eldridge, Alabama. Initial conditions for the cloud model run were developed...

Radiative Transfer to Space through a Precipitating Cloud at Multiple Microwave Frequencies. Part I: Model Description

Abstract In a two-part study we investigate the impact of time-dependent cloud microphysical structure on the transfer to space of passive microwave radiation at several frequencies across the EHF and lower SHF portions of the microwave spectrum in order to explore the feasibility of using multichannel passive-microwave retrieval techniques for the estimation of precipitation from space-based platforms. A series of numerical sensitivity experiments have been conducted that were designed to quantify the impact of an evolving cumulus cloud in conjunction with a superimposed rain layer on the transfer to space of microwave radiation emitted and scattered from the cloud layers, rain layer and the underlying surface. The specification of cloud microphysics has been based on the results of a time-dependent two-dimensional numerical cumulus model developed by Hall (1980). An assortment of vertically homogeneous rain layers, described by the Marshall-Palmer rain drop distribution, has been inserted in the model a...

Intercomparison of microwave radiative transfer models for precipitating clouds

An intercomparison of microwave multiple scattering radiative transfer codes used in generating databases for satellite rainfall retrieval algorithms has been carried out to ensure that differences obtained from retrieval techniques do not originate from the underlying radiative transfer code employed for the forward modeling. A set of profiles containing liquid water and ice contents of cloud and rain water as well as snow, graupel and pristine ice were distributed to the participants together with a black box routine providing Mie single scattering, atmospheric background absorption and surface emissivity. Simulations were to be carried out for nadir and off-nadir (53.1/spl deg/) observation angles at frequencies between 10 and 85 GHz. Among the radiative transfer models were two-stream, multiple stream and Monte Carlo models. The results showed that there were two major sources of differences between the codes. 1) If surface reflection/emission was considered isotropic, simulated brightness temperatures were significantly higher than for specular reflection and this effect was most pronounced at nadir observation and over ocean-type surfaces. 2) Flux-type models including delta-scaling could partially compensate for the errors introduced by the two-stream approximation. Largest discrepancies occurred at high frequencies where atmospheric scattering is most pronounced and at nadir observation. If the same surface boundary conditions, the same multiple-stream resolution and the same scaling procedures are used, the models were very close to each other with discrepancies below 1 K.