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Daisuke Hotta, Tse-Chun Chen, Eugenia Kalnay, Yoichiro Ota, and Takemasa Miyoshi

, 2007 : Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter . Physica D , 230 , 112 – 126 , doi: 10.1016/j.physd.2006.11.008 . 10.1016/j.physd.2006.11.008 Ingleby , N. B. , and A. C. Lorenc , 1993 : Bayesian quality control using multivariate normal distribution . Quart. J. Roy. Meteor. Soc. , 119 , 1195 – 1225 , doi: 10.1002/qj.49711951316 . 10.1002/qj.49711951316 Isaksen , L. , M. Fisher , E. Andersson , and J. Barkmeijer , 2005

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Daryl T. Kleist and Kayo Ide

. Horizontal localization scale (km) utilized in the GSI hybrid (Gaussian decorrelation length scale) derived from a database of ensemble forecasts using streamfunction. For the data selection and the quality control, 3DHYB utilizes the same procedure as the 3DVar control does using the high-resolution background. However, the exact data selection and counts are allowed to differ for any given cycle based on GSI internal quality control checks such as gross error, as well as decisions made by the

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María E. Dillon, Yanina García Skabar, Juan Ruiz, Eugenia Kalnay, Estela A. Collini, Pablo Echevarría, Marcos Saucedo, Takemasa Miyoshi, and Masaru Kunii

1. Introduction Forecast errors from numerical weather prediction (NWP) models arise in part from imperfect initial conditions, as a result of the lack of sufficient observations as well as their suboptimal use. Different data assimilation systems (DASs) have been developed since the objective analysis of meteorological fields was introduced in the midtwentieth century; for example, Cressman (1959) developed the empirical successive corrections method and Gandin (1963) introduced optimal

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James A. Cummings and Ole Martin Smedstad

. The analysis makes full use of all sources of the operational ocean observations. Ocean observing systems currently assimilated by NCODA 3DVAR are listed in Table 1 , along with typical global data counts per day. After data thinning and preprocessing, NCODA routinely assimilates about 2.2 million observations per day onto the global HYCOM grid, which contains more than 520 million grid points. All ocean observations are subject to data quality control (QC) procedures prior to assimilation. The

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D. J. Lea, I. Mirouze, M. J. Martin, R. R. King, A. Hines, D. Walters, and M. Thurlow

window. The 0000 and 1200 UTC analyses each day are used to initialize the forecasts. The atmosphere observations are extracted from the Met Office’s observational database. Different types of satellite and in situ observations are assimilated, including temperature, wind, humidity, pressure, and direct radiances. A quality control check is first performed to remove any unrealistic observations [see Rawlins et al. (2007) for more details]. The observations are then compared to the trajectory

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Juanzhen Sun, Hongli Wang, Wenxue Tong, Ying Zhang, Chung-Yi Lin, and Dongmei Xu

pairs have been used as control variables in global DA systems and in some regional DA systems that primarily assimilate large-scale observations ( Derber and Bouttier 1999 ; Lorenc et al. 2000 ; Berre 2000 ; Ingleby 2001 ; Zupanski et al. 2005 ; Rawlins et al. 2007 ; Huang et al. 2009 ; Barker et al. 2004 , 2012 ; Wang et al. 2013a , b ; Xiao et al. 2005 ). In contrast, the UV control variables have been the choice for variational systems that emphasize mesoscale data assimilation using

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Chengsi Liu and Ming Xue

Zhang (2012) also applied the extended control variable approach to a 4DVar framework of a regional research model. Kuhl et al. (2013) implemented En4DVar within the Naval Research Laboratory Atmospheric Variational Data Assimilation System-Accelerated Representer (NAVDAS-AR) data assimilation framework. It was found that the forecast error was significantly reduced by their En4DVar system. These systems were all built on existing 4DVar capabilities that already have an adjoint model, and

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Hailing Zhang and Zhaoxia Pu

. Before data assimilation, all NCEP ADP data passed through a complex quality control procedure. The QuikSCAT ocean surface wind vectors used here are retrieved products (wind speed and direction at 10-m height at 25-km horizontal resolution) produced by the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) from the SeaWinds scatterometer sensors on board the QuikSCAT satellite with quality flags ( Hoffman and Leidner 2005 ). Observations with low- and high

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Daryl T. Kleist and Kayo Ide

(right) H-4DEnVar cases. The solid contours are the background 500-hPa geopotential height (dam) valid at (top) beginning, (middle) center, and (bottom) end of the assimilation window. 3. Constraints on high-frequency noise The 4DEnVar (and hybrid) option is implemented in such a way as to allow for the application of many of the standard features included in the 3D GSI such as variational quality control, variational satellite bias correction, the tangent-linear normal mode constraint (TLNMC

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Andrew C. Lorenc, Neill E. Bowler, Adam M. Clayton, Stephen R. Pring, and David Fairbairn

: Operational, sequential and variational . J. Meteor. Soc. Japan , 75 , 181 – 189 . Ingleby , N. B. , 2001 : The statistical structure of forecast errors and its representation in the Met Office global 3D variational data assimilation scheme . Quart. J. Roy. Meteor. Soc. , 127 , 209 – 231 , doi: 10.1002/qj.49712757112 . Ingleby , N. B. , A. C. Lorenc , K. Ngan , F. R. Rawlins , and D. R. Jackson , 2013 : Improved variational analyses using a nonlinear humidity control variable

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