Search Results

You are looking at 1 - 9 of 9 items for

  • Author or Editor: Alberto Mugnai x
  • Refine by Access: All Content x
Clear All Modify Search
Eric A. Smith and Alberto Mugnai

Abstract

The time-dependent role of cloud liquid water in conjunction with its vertical heterogeneities on top-of-atmosphere (TOA) passive microwave brightness temperatures is investigated. A cloud simulation is used to specify the microphysical structure of an evolving cumulus cloud growing toward the rain stage. A one-dimensional multistream solution to the radiative transfer equation is used to study the upwelling radiation at the top of the atmosphere arising from the combined effect of cloud, rain, and ice hydrometeors. Calculations are provided at six window frequencies and one H2O resonance band within the EHF/SHF microwave spectrum. Vertically detailed transmission functions are used to help delineate the principal radiative interactions that control TOA brightness temperatures. Brightness temperatures are then associated with a selection of microphysical situations that reveal how an evolving cloud medium attenuates rainfall and surface radiation. The investigation is primarily designed to study the impact of cloud microphysics on space-based measurements of passive microwave signals, specifically as they pertain to the retrieval of precipitation over water and land backgrounds.

Results demonstrate the large degree to which the relationship between microwave brightness temperature (BT) and rainrate (RR) can be altered purely by cloud water processes. The relative roles of the cloud and rain drop spectra in emissive contributions to the upwelling radiation are assessed with a normalized absorption index, which removes effects due purely to differences in the magnitudes of the cloud and rain liquid water contents. This index is used to help explain why the amplitudes of the BT-RR functions decrease with respect to cloud evolution time and why below-cloud precipitation is virtually masked from detection at the TOA.

Although cloud water tends to obscure BT-RR relationships, it does so in a differential manner with respect to frequency, suggesting that the overall impact of cloud water is not necessarily debilitating to precipitation retrieval schemes. Furthermore, it is shown how a “surface” of “probability” can be defined, which contains an optimal time-dependent BT-RR function associated with an evolving cloud at a given frequency and removes ambiguities within the BT-RR functions at the critical retrieval frequencies. The influence of a land surface having varying emissivity characteristics is also examined in the context of an evolving cloud to show how the time-dependent cloud microphysics modulates the sign and magnitude of brightness temperature differences between various frequencies.

Model results are assessed in conjunction with a Nimbus-7 SMMR case study of precipitation within an intense tropical Pacific storm. It is concluded that in order to obtain a realistic estimation and distribution of rainrates, the effects of cloud liquid water content must be considered.

Full access
Alberto Mugnai and Eric A. Smith

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 atmosphere to simulate the evolution of rainfall in a precipitating cumulus cell. The effects of ice hydrometeors on upwelling brightness temperatures have been studied by placing several types of ice canopies over the cloud and rain layers. Both rough ocean and land backgrounds have been considered. The top-of-atmosphere brightness temperatures have been computed by means of a vertically and angularly detailed plane-parallel radiative transfer model for unpolarized microwave radiation.

Part I describes the modeling framework. In addition, it provides a detailed description of the single-scattering properties of the hydrometeors (model-cloud water drops, ice crystals and rain drops) in order to evaluate each component's role in influencing the upwelling radiation to space. We demonstrate that cloud water can have a major impact on the upwelling microwave radiation originating from both the surface and a rain layer placed below cloud base. The radiative properties of the model cloud are shown to be significantly different from those of an equivalent Marshall-Palmer treatment. It is the appearance of the large-drop mode (r> 100 μm) of the cumulus cloud drop distribution function that denotes the point at which cloud drops begin to attenuate the microwave signals, even at the lower frequencies, which are normally considered to be mostly unaffected by purely cloud processes. It is shown that at the early stages of cloud evolution, the model cloud acts mainly through absorption/emission processes. As the cloud develops, however, scattering plays an ever-increasing role. It is also demonstrated that the relative contribution by the small drop mode (r<100 μm) of the cloud to absorption/emission is always significant. It is concluded that the vertical variation of the microphysical structure of the rain-cloud plays an important role in the interpretation of passive microwave rainfall signatures and thus should be considered in precipitation retrieval algorithms.

Full access
Giorgio Fiocco, Gerald Grams, and Alberto Mugnai

Abstract

A previous analysis (Fiocco et al., 1975) of the energetic equilibrium of small particles in the earth's upper atmosphere is extended to the 0–60 km region. The analysis is based on establishing a balance among the energy absorbed from solar and planetary radiation fields, the energy radiated by the particles, and the sensible heat exchanged through collisions with the ambient gas. The planetary radiation field is calculated as a function of altitude and includes radiation from the surface as well as emission and absorption by the infrared bands of CO2, O3, and H2O The various energy term change as a function of radius and altitude of the particles, season, time of day and the earth's albedo. Thus aerosols may beat or cool the atmosphere and their temperature may. differ from the ambient gas temperature. Maximum and average values for the heating rates induced by the particles into the ambient gas are computed for summer and winter 45°N conditions.

Full access
Alberto Mugnai, Eric A. Smith, and Gregory J. Tripoli

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 TB's. This involves two distinct types of vertical weighting functions for the TB's: 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 individual roles of cloud drops, rain drops, graupel particles, ice crystals, and snow aggregates—as well as absorbing gases, the earth's surface, and cosmic background—on generating and modulating the frequency-dependent TB's are examined in detail. The analysis emphasizes how microwave TB measurements are highly regulated by mixtures of hydrometeors, with particular emphasis on the importance of the vertical profile structures. We demonstrate how scattering produces sequential, frequency-dependent, vertical “break aways” of the peak amplitudes in the generalized weighting functions, thus explaining how a multichannel radiometer can be used to depth probe a precipitating cloud. We also seek to explain the extent to which 19-, 37-, and 85-GHz TB's are responding to separate and distinct processes in precipitating cells in an unambiguous fashion, helping to elucidate the two key aspects of these standard satellite frequencies. That is, 1) they are best suited to decipher certain microphysical profile features above the main rain layers and near cloud top, and 2) they are ill suited for directly sensing precipitation intensity information within the main rain layers, particularly the surface rain rates. Finally, a summary of the various components of a hybrid statistical-physical rainfall algorithm used to produce liquid-ice profile information, as well as surface rain rates, is given. The algorithm employs the cloud model to provide a consistent and objectively generated source of detailed microphysical information as the underpinnings to an inversion-based perturbative retrieval scheme.

Full access
Alberto Mugnai, Harry J. Cooper, Eric A. Smith, and Gregory J. Tripoli

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 from the 1986-COHMEX data archive.

Two types of vertically resolved radiative structure functions referred to as a “generalized weighting function” and an “emission source weighting function” are used to describe the process by which radiation originates and reaches the satellite radiometer. In addition, these weighting functions are subdivided into individual contributions by the various hydrometeor species generated by the cloud model. Along with the surface contribution and cosmic background radiation, these weighting functions provide a normalized description of where radiation originates and how it ultimately reaches the satellite. It is emphasized that this information provides an indepth understanding of how precipitation retrieval algorithms should be designed vis-à-vis the passive microwave problem.

Full access
Eric A. Smith, F. Joseph Turk, Michael R. Farrar, Alberto Mugnai, and Xuwu Xiang

Abstract

This study presents research in support of the design and implementation of a combined radar–radiometer algorithm to be used for precipitation retrieval during the Tropical Rainfall Measuring Mission (TRMM). The combined algorithm approach is expected to overcome various difficulties that arise with a radar-only approach, particularly related to estimates of path-integrated attenuation (PIA) along the TRMM radar beam. A technique is described for estimating PIA at the 13.8-GHz frequency of the TRMM precipitation radar (PR) from 10.7-GHz brightness temperature T B measurements obtained from the TRMM microwave imager. Because the PR measures at an attenuating frequency, an independent estimate of PIA is used to constrain the solution to the radar equation, which incorporates effects of attenuation propagation along a radar beam. Through the use of variational or probabilistic techniques, the independent PIA calculations provide a means to adjust for errors that accumulate in estimates of range-dependent rain rates at progressively increasing range positions from radar reflectivity vectors. The accepted radar approach for obtaining PIA from ocean-viewing radar reflectivity measurements is called the surface reference technique, a scheme based on the difference in ocean surface cross sections between cloud-free and raining radar pixels. This technique has encountered problems, which are discussed and analyzed with the aid of coordinated aircraft radar (Airborne Rain Mapping Radar) and radiometer (Advanced Microwave Precipitation Radiometer) measurements obtained during the west Pacific Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment in 1993. The derived relationship expressing 13.8-GHz PIAs as a function of 10.7-GHz T B’s is based on statistical fitting of many thousands of radiative transfer (RTE) calculations in which the relevant physical and radiative parameters affecting transmission, absorption, and scattering in a raining column and the associated emission-scattering properties of the wind-roughened ocean surface are systematically varied over realistic range intervals. The results demonstrate that the T B–PIA relationship is stable, with a dynamic range up to about 8 dB. The RTE calculations are used to examine the relative merits of different viewing configurations of the radar and radiometer, and the associated uncertainty variance as the viewing configuration changes, since PIA uncertainty is an important control factor in the prototype TRMM combined algorithm.

Full access
Kwo-Sen Kuo, Eric A. Smith, Ziad Haddad, Eastwood Im, Toshio Iguchi, and Alberto Mugnai

Abstract

In developing the upcoming Global Precipitation Measurement (GPM) mission, a dual-frequency Ku–Ka-band radar system will be used to measure rainfall in such a fashion that the reflectivity ratio intrinsic to the measurement will be sensitive to underlying variations in the drop size distribution (DSD) of rain. This will enable improved techniques for retrieving rain rates, which are dependent upon several key properties of the DSD. This study examines this problem by considering a three-parameter set defined by liquid water content (W), DSD effective radius (r e), and DSD effective variance (υ e). Using radiative transfer simulations, this parameter set is shown to be related to a radar reflectivity factor and specific attenuation in such a fashion that details of the DSDs are immaterial under constant W, and thus effectively represent important variations in DSD that affect rain rate but with a minimal number of parameters. The analysis also examines the effectiveness of including some measure of mean Doppler fall velocity of raindrops (υ), given that the fundamental properties of a given precipitation situation are uniquely defined by a combination of a drop mass spectrum and drop vertical velocity spectrum. The results of this study have bearing on how future dual-frequency precipitation retrieval algorithms could be formulated to optimize the sensitivity to underlying DSD variability, a problem that has greatly upheld past progress in radar rain retrieval.

Full access
Eric A. Smith, Harry J. Cooper, Xuwu Xiang, Alberto Mugnai, and Gregory J. Tripoli

Abstract

A cloud-radiation model is used to investigate the relationship between emerging microwave brightness temperatures (T B's) 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 T B 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 T B 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 T B's but only at the higher frequencies. Emission by the large ice particles themselves becomes an important radiative source to the emerging T B's at the top of the atmosphere as the graupel-mixing ratios increase and effectively block the radiative sources from within the liquid layers.

Strong relationships are found between the emerging T B's and various rain parameters, but these correlations are misleading in that the T B's are largely controlled by fluctuations in ice-particle mixing ratios, which in turn are highly correlated to fluctuations in liquid-particle mixing ratios. This does not negate the use of empirically based brightness-temperature-rain-rate (T B-RR) algorithms as useful tools for estimating precipitation (i.e., graupel particles ultimately fall out as rain), but it does point to a basic problem that remote-sensing methodology must address. More specifically, the hydrometeor profiles used for T B-RR algorithms must not be specified in an ad hoc fashion. It is argued that a cloud model can overcome the ad hoc assumptions.

It is shown that the lowest SSM/I frequency (19 GHz) is actually a better estimator of columnar ice water content than the highest frequency (85 GHz). This is because both cloud-water emission and multiple scattering by ice particles are more prevalent at 85 GHz than at 19 GHz (which tends to be mostly influenced by single scattering). As a consequence, 85 GHz is much more sensitive to the configurational details of the vertical distribution of large ice particles and to the presence of supercooled cloud drops within the lower ice layers.

Full access
Giulia Panegrossi, Stefano Dietrich, Frank S. Marzano, Alberto Mugnai, Eric A. Smith, Xuwu Xiang, Gregory J. Tripoli, Pao K. Wang, and J. P. V. Poiares Baptista

Abstract

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.

Full access