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

, 2003 : A semianalytical cloud retrieval algorithm using backscattered radiation in 0.4–2.4 μ m spectral region. J. Geophys. Res. , 108 , 4008 . doi:10.1029/2001JD001543 . Kummerow , C. , and Coauthors , 2001 : The evolution of the Goddard Profiling Algorithm (GPROF) for rainfall estimation from passive microwave sensors. J. Appl. Meteor. , 40 , 1801 – 1820 . Kurino , T. , 1997 : A satellite infrared technique for estimating ‘deep/shallow’ precipitation. Adv. Space Res. , 19

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Feyera A. Hirpa, Mekonnen Gebremichael, and Thomas Hopson

) with that from the more frequent (but indirect) infrared (IR) to take advantage of the complementary strengths. The combination has been done in a variety of ways. The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT method ( Huffman et al. 2007 ) uses MW data to calibrate the IR-derived estimates and creates estimates that contain MW-derived rainfall estimates when and where MW data are available and the calibrated IR estimates where MW data are not

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Rémy Roca, Philippe Chambon, Isabelle Jobard, Pierre-Emmanuel Kirstetter, Marielle Gosset, and Jean Claude Bergès

WAM requires in-depth analysis of this multiscale variability of rainfall. Satellite observations are a powerful tool to cover these scales and to be used for these much needed meteorological investigations over the WAM where the pluviograph network is scarce. The recent generation of combined infrared (IR) and microwave (MW) products ( Hsu et al. 1997 ; Herman et al. 1997 ; Huffman et al. 2001 ; Joyce et al. 2004 ; Ushio et al. 2009 ; Huffman et al. 2007 ; Levizzani et al. 2007 ; Bergès et

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

becoming available, can supplement infrared-only data during both daytime and nighttime. Although incorporating the visible channel is promising, there are issues that need to be considered. First, snow on the ground may pose a limitation during the cloud-patch-type identification and rain-rate estimation steps because it can be confused with thick clouds. Second, the albedo normalization process used in this study is simple, and it assumes that the reflected radiation field is isotropic; thus, it is

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M. Tugrul Yilmaz, Paul Houser, Roshan Shrestha, and Valentine G. Anantharaj

1. Introduction Precipitation and radiation are the most important input forcings driving land surface models (LSM), whereas land cover, soil properties, and topography are secondary effects that influence the partitioning of these forcings between canopy interception, soil layers, runoff, and atmosphere ( Wei et al. 2008 ). Knowledge of temporal and spatial distributions of precipitation is crucial for producing realistic land surface simulations that enhance our understanding of hydrologic

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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

–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev. , 129 , 569 – 585 . Chou , M-D. , and M. J. Suarez , 1999 : A solar radiation parameterization for atmospheric studies. NASA Tech. Rep. NASA/TM-1999-10460, Vol. 15, 38 pp . Chou , M-D. , and M. J. Suarez , 2001 : A thermal infrared radiation parameterization for atmospheric studies. NASA/TM-2001-104606, Vol. 19, 55 pp . Cooper , K. A. , M. R. Hjelmfelt , R. G

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

-based precipitation retrieval algorithm for attenuating radars. J. Appl. Meteor. , 41 , 272 – 285 . Liebe , H. , 1989 : MPM89–An atmospheric mm-wave propagation model. Int. J. Infrared Millimeter Waves , 10 ( 6 ) 631 – 650 . Liou , K. N. , 1992 : Radiation and Cloud Processes in the Atmosphere . Oxford University Press, 487 pp . Loveland , T. R. , B. C. Reed , J. F. Brown , D. O. Ohlen , Z. Zhu , L. Yang , and J. W. Merchant , 2000 : Development of a global land cover

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

, corresponding to about 25 km (information available online at ). Global analyses of wind, temperature, surface pressure, humidity, and ozone are produced twice daily using a four-dimensional variational assimilation system (4D-Var; Rabier et al. 2000 ) with a 12-h time window. Assimilated observations include in situ conventional data, satellite radiances from polar orbiters [from instruments such as the Advanced Microwave Sounding Unit (AMSU) and the Infrared

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

1. Introduction The successful understanding and modeling of the global climate system requires detailed observation and knowledge of the global water cycle ( Trenberth et al. 2007 ; Allan and Liepert 2010 ). Especially over the global oceans, measurements of the required quantities are difficult to obtain and ship and buoy measurements suffer from inherent spatial and temporal undersampling. Microwave and infrared radiometers flown aboard polar orbiting satellites enable us to establish

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

skill of numerical weather prediction exceeds that of the High Resolution Infrared Radiation Sounder (HIRS) since infrared data are more strongly affected by the presence of clouds. Until the recent launch of a new generation of advanced infrared sounders, AMSU-A represented the single most important instrument in NWP. In a satellite constellation framework, some components of the space network could be devoted to the observation of specific regions. Regionalized analyses are becoming of increasing

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