Lagrangian four‐dimensional variational data assimilation of chemical species

Fisher, Michael; Lary, D. J.

doi:10.1002/qj.49712152709

Cited by 161 publications

(117 citation statements)

References 25 publications

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“…However, applications of this methodology to photochemical models are fairly rare. The current work has been largely motivated by ideas introduced for the first time by Fisher and Lary [ 1995]. An overview of the existing conventional methods of satellite data mapping is given in the next section.…”

Section: Lyster Et Al [1997] For the First Time Have Used A Twodimenmentioning

confidence: 99%

Assimilation of photochemically active species and a case analysis of UARS data

Khattatov¹,

Gille²,

Lyjak³

et al. 1999

J. Geophys. Res.

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Abstract. We present a short overview of applications of estimation theory in atmospheric chemistry and discuss some common methods of gridding and mapping of irregular satellite observations of chemical constituents. It is shown that these methods are unable to produce truly synoptic maps of short-lived photochemically active species due to insufficient temporal and spatial density of satellite observations. The only way to overcome this limitation is to supplement observations with prior independent information given, for instance, by atmospheric numerical models and/or climatologies. Objective approaches to combining such prior information with observations are commonly referred to as data assimilation. Mathematical basis of data assimilation known as optimal estimation equations is presented following Lorenc [ 1986]. Two particular techniques of data assimilation, the variational method and the extended Kalman filter, are briefly described, and their applications to time-dependent numerical photochemical models are discussed. We investigate validity of the linear approximation which is utilized in both methods, present

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Section: Lyster Et Al [1997] For the First Time Have Used A Twodimenmentioning

confidence: 99%

Assimilation of photochemically active species and a case analysis of UARS data

Khattatov¹,

Gille²,

Lyjak³

et al. 1999

J. Geophys. Res.

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“…Early applications of the four-dimensional variational (4D-Var) data assimilation were presented by Fisher and Lary [3] for a stratospheric photochemical box model with trajectories. Khattatov et al [4] implemented both the 4D-Var and a Kalman filter method using a similar model.…”

Section: Introductionmentioning

confidence: 99%

Data Assimilation in Multiscale Chemical Transport Models

Zhang

Sandu

2007

Computational Science – ICCS 2007

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Abstract. In this paper we discuss variational data assimilation using the STEM atmospheric Chemical Transport Model. STEM is a multiscale model and can perform air quality simulations and predictions over spatial and temporal scales of different orders of magnitude. To improve the accuracy of model predictions we construct a dynamic data driven application system (DDDAS) by integrating data assimilation techniques with STEM. We illustrate the improvements in STEM field predictions before and after data assimilation. We also compare three popular optimization methods for data assimilation and conclude that L-BFGS method is the best for our model because it requires fewer model runs to recover optimal initial conditions.

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“…This provides a means to study the quality of the chemistry scheme and description of advection and convection in the model. For instance, Fisher and Lary (1995) have shown how a 4-D-Var variational assimilation of a few chemical observations can provide strong constraints on a chemical model with an extensive set of species. This work has inspired several recent assimilation studies on stratospheric and tropospheric chemistry (see, for instance, Khattatov et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Global ozone forecasting based on ERS-2 GOME observations

2002

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Abstract. The availability of near-real time ozone observations from satellite instruments has recently initiated the development of ozone data assimilation systems. In this paper we present the results of an ozone assimilation and forecasting system, in use since Autumn 2000. The forecasts are produced by an ozone transport and chemistry model, driven by the operational medium range forecasts of ECMWF. The forecasts are initialised with realistic ozone distributions, obtained by the assimilation of near-real time total column observations of the GOME spectrometer on ERS-2. The forecast error diagnostics demonstrate that the system produces meaningful total ozone forecasts for up to 6 days in the extratropics. In the tropics meaningful forecasts of the small anomalies are restricted to shorter periods of about two days with the present model setup. It is demonstrated that important events, such as the breakup of the South Pole ozone hole and mini-hole events above Europe can be successfully predicted 4-5 days in advance.

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Lagrangian four‐dimensional variational data assimilation of chemical species

Cited by 161 publications

References 25 publications

Assimilation of photochemically active species and a case analysis of UARS data

Assimilation of photochemically active species and a case analysis of UARS data

Data Assimilation in Multiscale Chemical Transport Models

Global ozone forecasting based on ERS-2 GOME observations

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