An ensemble Kalman filter for short‐term forecasting of tropospheric ozone concentrations

Eben, Kryštof; Juruš, Pavel; Resler, Jaroslav; Belda, Michal; Pelikán, Emil; Krüger, B. C.; Keder, Josef

doi:10.1256/qj.05.110

Cited by 30 publications

(18 citation statements)

References 14 publications

(12 reference statements)

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“…RegCMCAMx4 further replaces the O'Brien (1970) method for calculating the coefficients of vertical turbulent diffusion (which is required by CAMx) with the newer Byun (1999) scheme (as used in CMAQ model), which provides better agreement of model results with measurements, as shown by Eben et al (2005) in a CAMx application over the same region and at similar horizontal resolution like in this study.…”

Section: Atmosmentioning

confidence: 90%

On the long-term impact of emissions from central European cities on regional air quality

2016

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Abstract. For the purpose of qualifying and quantifying the impact of urban emission from Central European cities on the present-day regional air quality, the regional climate model RegCM4.2 was coupled with the chemistry transport model CAMx, including two-way interactions. A series of simulations was carried out for the 2001-2010 period either with all urban emissions included (base case) or without considering urban emissions. Further, the sensitivity of ozone production to urban emissions was examined by performing reduction experiments with −20 % emission perturbation of NO x and/or non-methane volatile organic compounds (NMVOC).The modeling system's air quality related outputs were evaluated using AirBase, and EMEP surface measurements showed reasonable reproduction of the monthly variation for ozone (O 3 ), but the annual cycle of nitrogen dioxide (NO 2 ) and sulfur dioxide (SO 2 ) is more biased. In terms of hourly correlations, values achieved for ozone and NO 2 are 0.5-0.8 and 0.4-0.6, but SO 2 is poorly or not correlated at all with measurements (r around 0.2-0.5). The modeled fine particulates (PM 2.5 ) are usually underestimated, especially in winter, mainly due to underestimation of nitrates and carbonaceous aerosols.European air quality measures were chosen as metrics describing the cities emission impact on regional air pollution. Due to urban emissions, significant ozone titration occurs over cities while over rural areas remote from cities, ozone production is modeled, mainly in terms of number of exceedances and accumulated exceedances over the threshold of 40 ppbv. Urban NO x , SO 2 and PM 2.5 emissions also significantly contribute to concentrations in the cities themselves (up to 50-70 % for NO x and SO 2 , and up to 60 % for PM 2.5 ), but the contribution is large over rural areas as well (10-20 %). Although air pollution over cities is largely determined by the local urban emissions, considerable (often a few tens of %) fraction of the concentration is attributable to other sources from rural areas and minor cities. For the case of Prague (Czech Republic capital), it is further shown that the inter-urban interference between large cities does not play an important role which means that the impact on a chosen city of emissions from all other large cities is very small. At last, it is shown that to achieve significant ozone reduction over cities in central Europe, the emission control strategies have to focus on the reduction of NMVOC, as reducing NO x (due to suppressed titration) often leads to increased O 3 . The influence over rural areas is however always in favor of improved air quality, i.e. both NO x and/or NMVOC reduction ends up in decreased ozone pollution, mainly in terms of exceedances.

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Section: Atmosmentioning

confidence: 90%

On the long-term impact of emissions from central European cities on regional air quality

2016

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“…The same issue causes loss of spread in ensembles generated by perturbations of initial conditions. The sample covariance matrices generated by the ensemble become ill-conditioned, and covariance inflation or similar methods have to be used to avoid divergence of ensemble filters (Eben et al, 2005;Constantinescu et al, 2007).…”

Section: Data Assimilation Of Chemical Speciesmentioning

confidence: 99%

A review of operational, regional-scale, chemical weather forecasting models in Europe

et al. 2012

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Abstract. Numerical models that combine weather forecasting and atmospheric chemistry are here referred to as chemical weather forecasting models. Eighteen operational chemical weather forecasting models on regional and continental scales in Europe are described and compared in this article. Topics discussed in this article include how weather forecasting and atmospheric chemistry models are integrated into chemical weather forecasting systems, how physical processes are incorporated into the models through parameterization schemes, how the model architecture affects the predicted variables, and how air chemistry and aerosol processes are formulated. In addition, we discuss sensitivity analysis and evaluation of the models, user operational requirements, such as model availability and documentation, and output availability and dissemination. In this manner, this article allows for the evaluation of the relative strengths and weaknesses of the various modelling systems and modelling approaches. Finally, this article highlights the most prominent gaps of knowledge for chemical weather forecasting models and suggests potential priorities for future research Published by Copernicus Publications on behalf of the European Geosciences Union. J. Kukkonen et al.: A review of operational, regional-scale, chemical weather forecasting models in Europedirections, for the following selected focus areas: emission inventories, the integration of numerical weather prediction and atmospheric chemical transport models, boundary conditions and nesting of models, data assimilation of the various chemical species, improved understanding and parameterization of physical processes, better evaluation of models against data and the construction of model ensembles.

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“…Kalman filters have been used with atmospheric chemistry models by Ménard et al (2000). The numerical cost of this algorithm was addressed by the use of the ensemble Kalman filter and variants thereof in Segers et al (2000), Eben et al (2005), Hanea et al (2007), Wu et al (2008), and Sekiyama et al (2011). In order to address rank deficiencies and sampling issues, localisation and inflation have been used in this context (Constantinescu et al, 2007a, b;Schutgens et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes: L95-GRS (v1.0)

Haussaire

Bocquet

2016

Geosci. Model Dev.

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Abstract. Bocquet and Sakov (2013) introduced a low-order model based on the coupling of the chaotic Lorenz-95 (L95) model, which simulates winds along a mid-latitude circle, with the transport of a tracer species advected by this zonal wind field. This model, named L95-T, can serve as a playground for testing data assimilation schemes with an online model. Here, the tracer part of the model is extended to a reduced photochemistry module. This coupled chemistry meteorology model (CCMM), the L95-GRS (generic reaction set) model, mimics continental and transcontinental transport and the photochemistry of ozone, volatile organic compounds and nitrogen oxides. Its numerical implementation is described. The model is shown to reproduce the major physical and chemical processes being considered. L95-T and L95-GRS are specifically designed and useful for testing advanced data assimilation schemes, such as the iterative ensemble Kalman smoother (IEnKS), which combines the best of ensemble and variational methods. These models provide useful insights prior to the implementation of data assimilation methods into larger models. We illustrate their use with data assimilation schemes on preliminary yet instructive numerical experiments. In particular, online and offline data assimilation strategies can be conveniently tested and discussed with this low-order CCMM. The impact of observed chemical species concentrations on the wind field estimate can be quantitatively assessed. The impacts of the wind chaotic dynamics and of the chemical species non-chaotic but highly nonlinear dynamics on the data assimilation strategies are illustrated.

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An ensemble Kalman filter for short‐term forecasting of tropospheric ozone concentrations

Cited by 30 publications

References 14 publications

On the long-term impact of emissions from central European cities on regional air quality

On the long-term impact of emissions from central European cities on regional air quality

A review of operational, regional-scale, chemical weather forecasting models in Europe

A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes: L95-GRS (v1.0)

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