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Yalei You, Christa Peters-Lidard, Joseph Turk, Sarah Ringerud, and Song Yang

because that TB temporal variation is close to 0. The objective of this study is to present a new idea for enhancing precipitation retrievals by using TB temporal variation. We will explain where, when, and why TB temporal variation overcomes some of the limitations of the instantaneous TB for precipitation retrievals. This study is organized as follows. Section 2 describes the passive microwave observations from eight polar-orbiting satellites and the precipitation rate from the ground radar

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David B. Wolff and Brad L. Fisher

the most difficult physical quantities to measure accurately because of extreme variability both temporally and spatially, and insufficient observations over the planet’s oceans. Since the early 1970s, satellites have been used to quantitatively estimate precipitation by observing the emission and scattering processes associated with clouds and precipitation in the atmosphere. Multichannel passive microwave remote sensing techniques hold the most promise because these instruments sample rain

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Cheng-Zhi Zou and Wenhui Wang

. Geosci. Remote Sens. , 44 , 516 – 529 . 10.1109/TGRS.2005.863300 Zou, C-Z. , Goldberg M. , Cheng Z. , Grody N. , Sullivan J. , Cao C. , and Tarpley D. , 2006 : Recalibration of microwave sounding unit for climate studies using simultaneous nadir overpasses. J. Geophys. Res. , 111 , D19114 . doi:10.1029/2005JD006798 . 10.1029/2005JD006798 Zou, C-Z. , Gao M. , and Goldberg M. , 2009 : Error structure and atmospheric temperature trend in observations from the Microwave

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Fuzhong Weng, Tong Zhu, and Banghua Yan

observations, many attempts were made to improve hurricane analyses for forecasts. Krishnamurti et al. (1991) developed a method to physically initialize the Florida State University global cumulus parameterization spectral model, which mainly depends upon the surface rain rates derived from the Special Sensor Microwave Imager (SSM/I). A comparison study was conducted by Tibbetts and Krishnamurti (2000) to evaluate the performance of four different rain-rate algorithms in hurricane track forecast using

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Eun-Kyoung Seo, Svetla Hristova-Veleva, Guosheng Liu, Mi-Lim Ou, and Geun-Hyeok Ryu

time, the possibility to study rain-related climatology. One of the most valuable benefits that the TRMM mission has provided is the set of coincident rainfall estimations that come from two independent rainfall measurements provided by two very different, independent instruments—the TRMM Microwave Imager (TMI) and Precipitation Radar (PR). These complementary observations have allowed us to better understand the rainfall characteristics and resulted in a significant decrease of the uncertainty in

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Yves Quilfen, Bertrand Chapron, and Jean Tournadre

Remote Sensing (ERS), the Adaptive Domain Environment for Operating Systems (ADEOS), the Quick Scatterometer (QuikSCAT), and the Meteorological Operational (MetOp) satellites or synthetic aperture radars (SAR) on board the Environmental Satellite ( Envisat ) and Radarsat satellites, synoptic observations of surface wind and atmospheric water content generally reveal storm structures with impressive detail. However, most microwave sensors suffer severe limitations when attempting to retrieve the

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Jean-Pierre Chaboureau, Nathalie Söhne, Jean-Pierre Pinty, Ingo Meirold-Mautner, Eric Defer, Catherine Prigent, Juan R. Pardo, Mario Mech, and Susanne Crewell

analyzed on the 10-km grid mesh, which was comparable with the spatial resolution of the satellite microwave observations used in this study. This setup allows us to present an original application of the model-to-satellite approach by calculating categorical scores from observed and simulated BTs. The paper is organized as follows. Section 2 presents the Méso-NH model and its mixed-phase microphysical scheme, together with the radiative codes used to calculate the BTs. Section 3 contains an

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Andrew Manaster, Lucrezia Ricciardulli, and Thomas Meissner

1. Introduction Spaceborne active and passive microwave sensors have been monitoring global ocean surface winds for more than three decades ( Bourassa et al. 2010 ; Wentz et al. 2017 ). These measurements have been extensively validated versus in situ observations from anemometers on moored buoys and are highly accurate in the low to moderate wind regime (0–15 m s −1 ). In this wind regime, wind observations from satellites and buoys, converted to a reference height of 10 m, typically agree

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Patrick C. Meyers, Ralph R. Ferraro, and Nai-Yu Wang

-global rain-rate estimates every 3–4 h. The microwave spectrum is particularly sensitive to water in all states, allowing for retrievals of water vapor, liquid precipitation, and surface snow cover. Rainfall interacts with the microwave emissions from the earth’s surface, such that convective regions can be identified by the scattering of surface emissions by suspended snow, ice, and water ( Ferraro et al. 1998 ). Spaceborne passive microwave (PMW) imagers have been used to monitor global precipitation

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Stephen Po-Chedley and Qiang Fu

Wang W. , 2010 : Stability of the MSU-derived atmospheric temperature trend . J. Atmos. Oceanic Technol. , 27 , 1960 – 1971 . Zou, C.-Z. , and Wang W. , 2012 : Inter-satellite calibration of AMSU-A observations for weather and climate applications . J. Geophys. Res. , 116 , D23113 , doi:10.1029/2011JD016205 . Zou, C.-Z. , Goldberg M. D. , Cheng Z. , Grody N. C. , Sullivan J. T. , Cao C. , and Tarpley D. , 2006 : Recalibration of microwave sounding unit for climate

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