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  • Author or Editor: Alberto Mugnai x
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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.

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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.

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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.

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