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Beatriz M. Funatsu, Chantal Claud, and Jean-Pierre Chaboureau

end, we use the data provided by the Advanced Microwave Sounding Unit (AMSU) radiometer to detect moderate and heavy precipitating areas and their embedded upper-level environment. AMSU observations allows a screening of precipitation over the whole of the Mediterranean basin, including the sea, where in situ observations are scarce, providing a complementary picture from studies based on reanalysis and ground station data. In addition, operational analyses data of sea surface temperature (SST

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John Lewis, Christopher Hayden, and John Derber

substantially improved. This procedure is computationally intensive, however, and undermines our goal of providing a simple model whichmight be used at small installations to process hourlyobservations of wind and radiance. So we have chosennot to go to the additional effort and expense to producethis model, particularly given the limited observing capabilities of the VAS. It is worth noting that microwave observations aremore attractive for this application for a number ofreasons. For measurements in

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Randhir Singh, C. M. Kishtawal, P. K. Pal, and P. C. Joshi

measurements provides a unique way to remotely derive these heat fluxes over open oceans and complement in situ observations. The main deficiency of the satellite method however is the difficulty of the estimation of the near-surface specific humidity ( Q a ) and air temperature ( T a ). Liu (1986 , hereafter L86 ) developed empirical relation between the monthly mean total precipitable water ( W ), which can be measured by satellite, and monthly mean near surface specific humidity ( Q a ). Using this

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Olli M. Turpeinen, Louis Garand, Robert Benoit, and Michel Roch

, initially of the order of 9 hours, could be practically eliminated. The forecastprecipitation rates in the frontal zone agreed closely with Nimbus-7 SMMR microwave observations as earlyas 1-2 hours after the initialization.1. Introduction Despite continuous progress during recent years,numerical weather prediction models arc still plaguedby a slowness to forecast appropriate amounts of precipitation-during the first few (12) hours of integration.This is the so-called spin-up problem of

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Shu-Hua Chen, Zhan Zhao, Jennifer S. Haase, Aidong Chen, and Francois Vandenberghe

. B. , and F. J. Wentz , 2005 : Global microwave satellite observations of sea surface temperature for numerical weather prediction and climate research. Bull. Amer. Meteor. Soc. , 86 , 1097 – 1115 . Chen , S-H. , 2007 : The impact of assimilating SSM/I and QuikSCAT satellite winds on Hurricane Isidore simulations. Mon. Wea. Rev. , 135 , 549 – 566 . Chen , S-H. , and W-Y. Sun , 2002 : A one-dimensional time-dependent cloud model. J. Meteor. Soc. Japan , 80 , 99 – 118

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E. B. Rodgers and R. F. Adler

506 MONTHLY WEATHER REVIEW VOLUM~ 109Tropical Cyclone Rainfall Characteristics as Determined from a Satellite Passive Microwave Radiometer E. B. ROVO-RS AND R. F. ADLER NASA, Goddard Space Flight Center, Greenbelt, MD 20771(Manuscript received 8 May 1980, in final form 10 October 1980)ABSTRACT Data from the Nimbus-5 Electrically Scanning Microwave Radiometer (ESMR-5) have

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David F. Parrish and John C. Derber

pressure, mixing ratio, and Special Sensor Microwave/Imager(SSM/I) total precipitable water can be used as the observation variables. Soon to be added are the scatterometersurface winds. This paper provides a detailed description of the SSI and presents a few results.1. Introduction ~ Most of the major operational NWP centers assimilate observations into forecast models using some formof statistical or optimum interpolation (OI). Thesesystems are based on the ideas of Gandin (1963) andEliassen (1954

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F. Martin Ralph, Paul J. Neiman, and Gary A. Wick

Geostationary Operational Environmental Satellites (GOES) also furnished observations. A Special Sensor Microwave Imager (SSM/I) was carried on three Defense Meteorological Satellite Program polar orbiters ( F11, F13, F14 ) that circled the globe once every ∼102 min. Tropospheric integrated water vapor (IWV) ( Schluessel and Emery 1990 ), cloud liquid water (CLW) ( Weng and Grody 1994 ), rain rate (RR) ( Ferriday and Avery 1994 ), and ocean-surface wind speed (SPD) ( Goodberlet et al. 1990 ) were

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Udai Shimada, Masahiro Sawada, and Hiroyuki Yamada

; Olander et al. 2004 ; Olander and Velden 2007 ), satellite microwave sounding data ( Brueske and Velden 2003 ; Herndon and Velden 2004 ; Demuth et al. 2004 ; Oyama 2014 ), or satellite microwave imager data ( Bankert and Tag 2002 ; Hoshino and Nakazawa 2007 ; Sakuragi et al. 2014 ). The Dvorak technique is an empirical method based on past reconnaissance observations and the subjective classification of cloud patterns, although the advanced Dvorak technique is a fully automated method ( Olander

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Vance Moyer, James R. Scoggins, Nine-Min Chou, and Gregory S. Wilson

HighResolution Infrared Radiation Sounder (HIRS) and Scanning Microwave Spectrometer (SCAMS) radiancesare assessed by comparison with similar dat~ from weighted means of the rawinsonde observations (raobs)that bracketed the time of the satellite orbit across the east central United States for a case study on 25August 1975. With notable exceptions, the HIRS-SCAMS temperature profiles are fairly good approximations of the weighted-mean raob profiles; those exceptions occur near the surface and near the

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