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Meike Kühnlein, Boris Thies, Thomas Nauß, and Jörg Bendix

higher rainfall probability than cloud areas with a low optical thickness and a small effective particle radius. Recently, Thies et al. (2008c) showed the possibility of separating areas of differing precipitation processes and rainfall intensities within rain areas by using cloud properties retrieved with the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Instrument (SEVIRI). The day and night techniques for precipitation process separation and rainfall

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Alan J. Geer, Peter Bauer, and Christopher W. O’Dell

errors in the 20ICA are acceptably small for this kind of study. c. Optimal approach The optimal approach of O’Dell et al. (2007) is also tested here, because it is a candidate for data assimilation use in the future. It is compared to real observations for the first time here. The optimal approach attempts to replicate the performance of the ICA, but using a far smaller number of subcolumns. The idea is that subcolumns are binned together where they have similar optical properties at the

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J. J. Shi, W-K. Tao, T. Matsui, R. Cifelli, A. Hou, S. Lang, A. Tokay, N-Y. Wang, C. Peters-Lidard, G. Skofronick-Jackson, S. Rutledge, and W. Petersen

made to the Goddard radiation package before it was added into WRF: 1) the shortwave radiation code was optimized for computational speed (by a factor of 2), 2) cloud optical properties were made to be consistent with the assumptions in the Goddard microphysics, 3) stratospheric layers can be optionally added above the top of the model pressure level, and 4) the aerosol direct effect on both longwave and shortwave radiation has been accounted for ( Matsui et al. 2007 ). The Goddard SDSU is an end

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Mark S. Kulie and Ralf Bennartz

uncertainties due to the assumed model employed to represent frozen hydrometeors, and recently published optical property databases of nonspherical ice particle models ( Hong 2007 ; Kim et al. 2007 ; Liu 2004 , 2008b ) are utilized to illustrate this potentially significant source of uncertainty. Section 2 describes the data used in this study, and section 3 provides a methodology overview of the radar reflectivity factor calculation and conversion procedure. Global and regional results, as well as

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Cristian Mitrescu, Tristan L’Ecuyer, John Haynes, Steven Miller, and Joseph Turk

used to characterize the global distribution of clouds ( Mace et al. 2009 ) and to study the impact of aerosols on cloud optical and microphysical properties ( Lebsock et al. 2008 ). A near-real-time application of CPR scans and associated products are already being applied ( Mitrescu et al. 2008 ). 3. CloudSat light precipitation profiling algorithm The CPR on board CloudSat measures backscatter reflectivity as a function of distance from both distributed (i.e., hydrometeors) and solid (i

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Ali Behrangi, Koulin Hsu, Bisher Imam, and Soroosh Sorooshian

-patch classification system (CCS) labeled PERSIANN-CCS that relies on infrared-only images. PERSIANN-CCS implements image processing and pattern classification techniques to derive rain rate through the following steps: 1) cloud patches are segmented using a fixed threshold 253 K, using the incremental temperature threshold (ITT) method; 2) cloud-patch features, representing cloud-patch coldness, geometry and texture properties are extracted; 3) the extracted features are classified into a number of groups using

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Frank S. Marzano, Domenico Cimini, Tommaso Rossi, Daniele Mortari, Sabatino Di Michele, and Peter Bauer

compatible orbit is that its trajectory in the rotating reference frame constitutes a closed loop with assigned repetition time. The FC theory explains how to place satellites on the same relative trajectory so that the whole constellation is made of satellites that fly along relative trajectories, one after another. Repeating ground track is not a unique property of Flower constellations, but the innovative concept of the Flower constellations is based on two main properties: compatibility and phasing

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Axel Andersson, Christian Klepp, Karsten Fennig, Stephan Bakan, Hartmut Grassl, and Jörg Schulz

surface. Additionally, regionally limited measurements acquired by rawinsondes and the radiative transfer calculations underlying the satellite retrieval algorithms as well as the reanalyses lead to locally different results in the wind speed. The large differences over the monsoon regions of the Bay of Bengal and the Arabian Sea are likely to originate from lack of input data representing the specific atmospheric and sea surface properties in these regions due to atmospheric advection and oceanic

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