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Michael M. Bell, Wen-Chau Lee, Cory A. Wolff, and Huaqing Cai

airborne Doppler data contain both weather and nonweather echoes that require editing and quality control (QC) prior to wind synthesis, but interactive QC has been a hindrance for researchers because of the time and training required to properly identify nonweather radar echoes. To date, this interactive editing process has not been systematically documented. The purpose of the current study is to (i) document the characteristics of nonweather echoes in airborne Doppler radar, (ii) design an algorithm

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Valliappa Lakshmanan, Angela Fritz, Travis Smith, Kurt Hondl, and Gregory Stumpf

statistical anomalies in the way the NN inputs are computed, especially at the edges of echoes. A method of selective emphasis is followed here to ensure good performance on significant echoes. Last, the technique described in this paper removes or retains entire echo regions, not just individual pixels. A particular challenge in the quality control (QC) of radar reflectivity data is that errors in the QC process can be additive from the point of view of downstream applications. This effect is

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Jon K. Eischeid, C. Bruce Baker, Thomas R. Karl, and Henry F. Diaz

DECEMBER 1995 EISCHEID ET AL. 2787The Quality Control of Long-Term Climatological Data Using Objective Data Analysis JON K. EISCHEIDCooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, Colorado C. BRUCE BAKER AND THOMAS R. KARLNational Climatic Data Center, NOAA, Asheville, North Carolina HENRY F

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Daniel Vila, Ralph Ferraro, and Hilawe Semunegus

. 2003 ). The GPCC uses a method similar to SPHEREMAP ( Willmott et al. 1985 ) to interpolate the data to regular grids and to produce a 2.5° product. This product undergoes extensive quality control. The errors in the GPCC product vary as a function of terrain type and number of stations in the grid. Matchups between the SSM/I dual-satellite rainfall retrieval and GPCC monthly estimates were generated for the period January 1992–December 2007. In this case, the dual-satellite product has been used

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Youlong Xia, Trent W. Ford, Yihua Wu, Steven M. Quiring, and Michael B. Ek

in the United States lack harmonization through standardized quality control methods and protocols. The absence of consistent calibration and measurement standards among observation networks makes comparison of data collected by different networks very difficult. To overcome this limitation, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu ) was initiated in 2010 to serve as a centralized data hosting facility where globally available in situ soil moisture

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Imke Durre, Matthew J. Menne, Byron E. Gleason, Tamara G. Houston, and Russell S. Vose

National Technical Information Service, 5285 Port Royal Rd., Springfield, VA 22161, and online at http://www.ornl.gov/~webworks/cppr/y2002/rpt/101454.pdf ] . Eischeid , J. K. , C. B. Baker , T. Karl , and H. F. Diaz , 1995 : The quality control of long-term climatological data using objective data analysis. J. Appl. Meteor. , 34 , 2787 – 2795 . Eischeid , J. K. , P. A. Pasteris , H. F. Diaz , M. S. Plantico , and N. J. Lott , 2000 : Creating a serially complete, national

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P. Quintana-Seguí, P. Le Moigne, Y. Durand, E. Martin, F. Habets, M. Baillon, C. Canellas, L. Franchisteguy, and S. Morel

zones are used if necessary. First, SAFRAN does a quality control of the observations. This is an iterative procedure based on the comparison between observed and analyzed quantities at the observation location. The analyses of temperature, humidity, wind speed, and cloudiness are performed every 6 h using all available observations (see subsection below). For this part, the first guess comes from the large-scale operational weather prediction model Arpege ( Courtier et al. 1991 ) or from the ECMWF

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Debasish PaiMazumder and Nicole Mölders

.S. precipitation data. Bull. Amer. Meteor. Soc. , 75 , 215 – 227 . Groisman , P. Y. , V. V. Koknaeva , T. A. Belokrylova , and T. R. Karl , 1991 : Overcoming biases of precipitation measurement: A history of the USSR experience. Bull. Amer. Meteor. Soc. , 72 , 1725 – 1733 . Hanna , S. R. , 1994 : Mesoscale meteorological model evaluation techniques with emphasis on needs of air quality models. Mesoscale Modeling of the Atmosphere, Meteor. Monogr., No. 25, Amer. Meteor. Soc., 47

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Guang-Yu Shi, Tadahiro Hayasaka, Atsumu Ohmura, Zhi-Hua Chen, Biao Wang, Jian-Qi Zhao, Hui-Zheng Che, and Li Xu

, and S. Xu , 1998 : The description of Chinese radiation data and their quality control procedures (in Chinese). Meteor. Sci. , 2 , 53 – 56 . Maxwell , E. , S. Wilcox , and M. Rymes , 1993 : User’s manual for SERI QC software—Assessing the quality of solar radiation data. National Renewable Energy Laboratory Rep. NREL-TP-463-5608, NREL, 1617 pp . Muneer , T. , 2004 : Solar Radiation and Daylight Models . Elsevier, 392 pp . Muneer , T. , and M. S. Gul , 2000 : Evaluation

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Hilawe Semunegus, Wesley Berg, John J. Bates, Kenneth R. Knapp, and Christian Kummerow

and Grody, 1998 ; Jackson et al. 2002 ; Zhang et al. 2006 ). To improve geophysical parameters such as global rainfall estimation in support of the National Aeronautics and Space Administration (NASA) Global Precipitation Mission (GPM), Berg and Kummerow (2006) developed SSM/I quality control procedures that have been shown to significantly remove spurious geolocation, radiance, and climatologically anomalous data. Vila et al. (2010) have demonstrated the effectiveness of these statistically

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