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W. L. Smith and H. M. Woolf

the Nimbus-6 satellite, these results will be presented in a futurereport.I. Introduction In this paper techniques are developed for usingeigenvectors of covariance matrices of radiance, atmospheric temperature and water vapor mixing ratio forestimating cloud-free infrared sounding radiances, vertical temperature and water vapor profiles, and the vertical distribution of cloudiness from infrared and microwave sounding spectrometer observations obtainedfrom the Nimbus-6 satellite. The use of

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Jeffrey R. Tesmer and Thomas T. Wilheit

-understood physical principles of the atmosphere. Second, this paper will explore what microphysical changes in the model are forced by the observations. With microphysical changes added to the cloud model, the improved radiative transfer algorithm should be able to reproduce brightness temperatures observed by TOGA COARE microwave sensors. 2. Data The TCM-90 and the TOGA COARE data used in this study were obtained from the western Pacific in 1990 and 1993, respectively. The TCM-90 experiment contained collocated

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J. Turk, F. S. Marzano, and A. Mugnai

radiative transfer modeling. The input observations used by profiling algorithms can be obtained from radiometric, radar, or any other datasets (provided that the observation can be forward modeled), although most profiling algorithms have been appropriately designed around the passive microwave T B channels of the SSM/I. In this work, we used these TOGA COARE datasets as input to the profiling algorithm and approach of Marzano et al. (1995) and Marzano et al. (1996) , which the authors had

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Joseph S. Hogan, S. I. Rasool, and Thérèse Encrenaz

clouds, for boundary conditions suggested by recent observations. The resulting models are characterized by an extensive region of dynamical control above the cloud level, and a thermal inversion in themesosphere, produced by absorption of solar IR energy in the 3020 cm-x band of methane. The infraredand microwave spectra corresponding to the computed thermal models are/ound to be in generally goodagreement with observed infrared and microwave brightness temperatures of Jupiter. The effective

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Elizabeth E. Ebert and Michael J. Manton

1. Introduction Satellite remote sensing techniques have shown considerable promise for deriving estimates of rainfall on a global scale. Beginning in 1987 satellite rainfall estimates have been combined with surface observations to provide global monthly rainfall estimates for the Global Precipitation Climatology Project (GPCP) ( Arkin and Xie 1994 ). Both NOAA and NASA Goddard Space Flight Center currently use microwave satellite observations to produce global monthly rainfall estimates that

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Robbie E. Hood, Daniel J. Cecil, Frank J. LaFontaine, Richard J. Blakeslee, Douglas M. Mach, Gerald M. Heymsfield, Frank D. Marks Jr., Edward J. Zipser, and Michael Goodman

provided opportunities for joint missions with the NOAA WP-3D Orion (P-3) aircraft. Using data collected during CAMEX-3 and CAMEX-4, this study examines the relationship of three key sets of observations and the information they jointly provide regarding vertical precipitation profiles and convective intensity for tropical precipitation systems. In particular, this study explores how to optimally combine the information content of the multifrequency mapping of passive microwave brightness temperatures

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Clay B. Blankenship, Abdulrahman Al-Khalaf, and Thomas T. Wilheit

1. Introduction Water vapor is of critical importance in the earth’s atmosphere. The latent heat released by condensation of water vapor drives atmospheric circulation at many scales. The latent heat is also an important form of energy transport from the equatorial regions poleward. Radiatively, it is the most important of the greenhouse gases. The Special Sensor Microwave/Temperature-2 (SSM/T-2) microwave radiometer was launched in November 1991 aboard the F-11 spacecraft. This was the first

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Frédéric Fabry and Wanda Szyrmer

available over large regions is radar reflectivity, which has a complex dependence on the hydrometeor size distribution, morphology of the melting snowflake, and precipitation rate. However, if radar observations can be reproduced correctly by numerical models, then we should have good confidence that both the melting process and the physics of scattering of melting snowflakes are reasonably emulated. Many radar models of the melting layer, or bright band, exist, as they each used different

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Keigo Matsuda, Ryo Onishi, Masaaki Hirahara, Ryoichi Kurose, Keiko Takahashi, and Satoru Komori

. 2007 ; Stephens et al. 2008 ; Ellis and Vivekanandan 2011 ). In radar observations, microwave radiation is transmitted from an antenna toward a target cloud and the reflected microwaves received and analyzed. The relation between the transmitted power P t and the received power P r of the microwaves is given by the following radar equation: where G is the antenna gain, k m is the microwave wavenumber, R is the distance between the antenna and the cloud, K is the dielectric coefficient

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Y. P. Zhou, W.-K. Tao, A. Y. Hou, W. S. Olson, C.-L. Shie, K.-M. Lau, M.-D. Chou, X. Lin, and M. Grecu

retrieval algorithms ( Simpson et al. 1996 ). It has also been used in the TRMM algorithms to provide a link between latent heating profiles and TRMM Microwave Imager (TMI) and precipitation radar (PR) observations, because latent heating cannot be directly measured. Comparing GCE simulations with TMI retrievals provides a consistent check of the model and retrievals under different environmental conditions. Second, combined cloud and precipitation measurements from independent instruments provide a

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