A reformulation of the background error covariance in the ECMWF global data assimilation system

Derber, John; Bouttier, François

doi:10.1034/j.1600-0870.1999.t01-2-00003.x

Cited by 305 publications

(289 citation statements)

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“…At ECMWF, the error covariance matrix model described in Derber and Bouttier (1999) was used until recently. A new formulation due to Fisher (2003Fisher ( , 2004, currently operational, allows a better representation of the spatial variability of horizontal correlations with respect to the more rigid Derber and Bouttier (1999) formulation, thanks to the introduction of the 'wavelet' J b . In this approach, the properties of the B-matrix are modelled by using the mathematical framework of wavelet-like, non-orthogonal base functions having simultaneous localisation both in space and wave number.…”

Section: A Statistical Model For the Aerosol Background Error Covariamentioning

confidence: 99%

Background error statistics for aerosols

Benedetti

Fisher

2007

Quart J Royal Meteoro Soc

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As part of the European initiative for Global Monitoring for Environment and Security (GMES), the Global and regional Earth-system Monitoring using Satellite and in situ data (GEMS) project has been funded to provide forecasts and analysis of atmospheric constituents such as aerosols, and greenhouse and reactive gases. In this context, the development of an aerosol analysis system based on a four-dimensional variational (4D-Var) assimilation was started in March 2005 at the European Centre for Medium-Range Weather Forecasts (ECMWF). As part of the main building blocks of the system, an error background covariance matrix for aerosol mixing ratio was built based on background statistics constructed from aerosol forecasts. These statistics were generated from the differences between the 48-hour and 24-hour forecasts of aerosol mixing ratios for sea salt, desert dust and continental particulate, using the NMC method. This method has been widely used by many numerical weather prediction centres to build background error statistics for state variables. This is the first time, to our knowledge, that it has been applied to a novel variable such as an aerosol mixing ratio, in the context of a global model. Aerosol assimilation systems have been successfully run with either observationally-derived or model-prescribed error covariance matrices with pre-assigned correlation lengths. In this study, the aerosol vertical and horizontal structures of these error correlations as derived with the aid of a state-of-the-art model are investigated and discussed in depth. Successively these error correlations are modelled through a spectral/wavelet approach and used to construct a background error covariance matrix. Application of this background matrix in the context of a single observation 4D-Var experiment produced successful preliminary analyses of the total aerosol mixing ratio.

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Section: A Statistical Model For the Aerosol Background Error Covariamentioning

confidence: 99%

Background error statistics for aerosols

Benedetti

Fisher

2007

Quart J Royal Meteoro Soc

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“…Quantification of the loss of information as a result of suboptimal weighting, and implementation of efficient procedures to adjust the error covariance parameters to a configuration that improves the forecasts' skill, are areas of active research. Synergistic efforts include the development of error covariance models for NWP applications (Derber and Bouttier, 1999;Gaspari and Cohn, 1999;Lorenc, 2003;Fisher, 2003;Bannister, 2008aBannister, , 2008bFrehlich, 2011;Bishop et al, 2011;Raynaud et al, 2011) and of computationally feasible techniques for diagnosis, estimation, and tuning of the error covariance parameters (Wahba et al, 1995;Dee, 1995;Dee and Da Silva, 1999;Andersson et al, 2000;Desroziers and Ivanov, 2001;Cardinali et al, 2004;Buehner et al, 2005;Chapnik et al, 2006;Zupanski and Zupanski, 2006;Trémolet, 2007;Anderson, 2007;Liu and Kalnay, 2008;Desroziers et al, 2009;Li et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Error covariance sensitivity and impact estimation with adjoint 4D‐Var: theoretical aspects and first applications to NAVDAS‐AR

Daescu

Langland²

2012

Quart J Royal Meteoro Soc

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“…This is believed to be an appropriate approximation on the basis of the strong coupling between the surface layer air and the surface. The statistics were derived previously using the so-called NMC (National Meteorological Center) method (Parrish and Derber, 1992;Derber and Bouttier, 1999) and correspond to the statistics used in the current operational global NWP system. Figures 7-9 show profiles of analysis increments obtained using the various TL/AD configurations.…”

Section: Temperature Increments From Near-surface Wind Data Assimilationmentioning

confidence: 99%

An equivalent neutral wind observation operator for variational assimilation of scatterometer ocean surface wind data

Tardif¹,

Laroche²

2012

Quart J Royal Meteoro Soc

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This article describes a new observation operator developed for improved variational data assimilation of scatterometer ocean wind vectors. The forward operator is designed explicitly to take into account the equivalent neutral calibration of scatterometer wind retrievals. The corresponding tangent linear and adjoint (TL/AD) operators are developed for the calculation of near-surface increments based explicitly on parametrizations of surface-layer turbulent momentum transfer. Tangent linear and adjoint operators are formulated using the Jacobian of the forward operator estimated using the perturbation method. Various TL/AD configurations are investigated in more detail to assess the impact of sensitivities affecting the vertical gradient of surface-layer temperature during assimilation of ocean surface wind data. It is argued that these sensitivities should be neglected in the context of a stand-alone atmospheric prediction system. The complete form of the operator has, however, the potential to be a key component of a coupled atmosphere-ocean data assimilation system. Two data assimilation experiments were performed using distinct scatterometer observation operators, i.e. new equivalent neutral versus the simpler operational configuration using stability-dependent (real) background winds. Associated medium-range forecasts were run for a complete impact assessment. The impact of the new operator is tracked through the entire data assimilation and forecast process by comparing analyses and forecasts from both experiments. A significant sensitivity of the data assimilation system to the configuration of the observation operator has been found. Modest but beneficial impacts are obtained with the equivalent neutral wind observation operator with respect to short-range forecasts of ocean surface winds and medium-range forecasts of extratropical geopotential heights.

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A reformulation of the background error covariance in the ECMWF global data assimilation system

Cited by 305 publications

References 1 publication

Background error statistics for aerosols

Background error statistics for aerosols

Error covariance sensitivity and impact estimation with adjoint 4D‐Var: theoretical aspects and first applications to NAVDAS‐AR

An equivalent neutral wind observation operator for variational assimilation of scatterometer ocean surface wind data

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