Technical Note: The air quality modeling system Polyphemus

doi:10.5194/ACP-7-5479-2007

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Technical Note: The air quality modeling system Polyphemus

Journal Article•DOI•

Technical Note: The air quality modeling system Polyphemus

Vivien Mallet¹, Vivien Mallet², Denis Quélo³, Bruno Sportisse¹, Bruno Sportisse², M. Ahmed de Biasi¹, M. Ahmed de Biasi², Edouard Debry¹, Irène Korsakissok², Irène Korsakissok¹, Lin Wu², Lin Wu¹, Yelva Roustan¹, Yelva Roustan², Karine Sartelet¹, M. Tombette¹, H. Foudhil¹ - Show less +13 more•Institutions (3)

University of Paris¹, French Institute for Research in Computer Science and Automation², Institut de radioprotection et de sûreté nucléaire³

26 Oct 2007-Atmospheric Chemistry and Physics (Copernicus GmbH)-Vol. 7, Iss: 20, pp 5479-5487

TL;DR: Polyphemus is an air quality modeling platform which deals with applications from local scale to continental scale, using two Gaussian models and two Eulerian models to manage passive tracers, radioactive decay, photochemistry and aerosol dynamics.

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Abstract: Polyphemus is an air quality modeling platform which aims at covering the scope and the abilities of modern air quality systems. It deals with applications from local scale to continental scale, using two Gaussian models and two Eulerian models. It manages passive tracers, radioactive decay, photochemistry and aerosol dynamics. The structure of the system includes four independent levels with data management, physical parameterizations, numerical solvers and high-level methods such as data assimilation. This enables sensitivity and uncertainty analysis, primarily through multimodel approaches. On top of the models, drivers implement advanced methods such as model coupling or data assimilation.

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Journal Article•DOI•

Real-time air quality forecasting, part I: History, techniques, and current status

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Yang Zhang¹, Yang Zhang², Marc Bocquet³, Marc Bocquet⁴, Vivien Mallet³, Vivien Mallet⁴, Christian Seigneur⁴, Alexander Baklanov⁵ - Show less +4 more•Institutions (5)

Tsinghua University¹, North Carolina State University², French Institute for Research in Computer Science and Automation³, École des ponts ParisTech⁴, Danish Meteorological Institute⁵

01 Dec 2012-Atmospheric Environment

TL;DR: Real-time air quality forecasting (RT-AQF), a new discipline of the atmospheric sciences, represents one of the most farreaching development and practical applications of science and engineering, poses unprecedented scientific, technical, and computational challenges, and generates significant opportunities for science dissemination and community participations.

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359 citations

Cites background from "Technical Note: The air quality mod..."

...…(2001a) and Rouïl et al. (2009); www.prevair.org France/CEREA POLYPHEMUS ECMWF, MM5, WRF Polair3D None Regional Offline Mallet and Sportisse, 2006; Mallet et al., 2007; Debry et al., 2007; Sartelet et al., 2007; cerea.enpc.fr/polyphemus/ Denmark/DMU-ATMI THOR The US NCEP, Eta DEOM BUM OSPM DREAM…...
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...…Unified Online Uno et al. (2003), Carmichael et al. (2003) and Hadley et al. (2007) Chile/Meteo Chile POLYPHEMUS MM5 Polair3D None Regional Offline Mallet et al. (2007) and Mallet and Sportisse (2006), cerea.enpc.fr/polyphemus/ a The list of acronyms is provided in Appendix. b There are several…...
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...31 None Regional Offline Kallos et al. (2007, 2009), Mitsakou et al. (2008) and Spyrou et al. (2010); forecast.uoa.gr Italy/CETEMPS ForeChem MM5 CHIMERE None Regional Offline Curci (2010); pumpkin.aquila.infn.it/forechem/ China/IAP-CAS EMS-Beijing MM5 NAQPMS, CMAQ, CAMx None Regional Offline Wang et al. (2009) Japan/Kyushu University CFORS RAMS Parameterized chemical tracers in RAMS None Regional Unified Online Uno et al. (2003), Carmichael et al. (2003) and Hadley et al. (2007) Chile/Meteo Chile POLYPHEMUS MM5 Polair3D None Regional Offline Mallet et al. (2007) and Mallet and Sportisse (2006), cerea.enpc.fr/polyphemus/ a The list of acronyms is provided in Appendix. b There are several air quality systems used by regional air quality agencies (Association agréées de surveillance de la qualité de l’air (AASQAs)) and only the one for the Paris region is given here as an example. c FUMAPEX includes six UAQIFS model systems implemented in six cities in five countries, as labeled 1e6 under Model System, Meteorological Model (MetM), and Air Quality Model (AQM)....
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Journal Article•DOI•

Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

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Marc Bocquet¹, Marc Bocquet², Hendrik Elbern³, Henk Eskes⁴, Marcus Hirtl⁵, Rahela Žabkar⁶, Greg Carmichael⁷, Johannes Flemming⁸, Antje Inness⁸, Mariusz Pagowski⁹, J. L. Pérez Camaño¹⁰, Pablo E. Saide⁷, R. San José¹⁰, Mikhail Sofiev¹¹, Julius Vira¹¹, Alexander Baklanov¹², Claudio Carnevale¹³, Georg Grell⁹, Christian Seigneur¹ - Show less +15 more•Institutions (13)

École des ponts ParisTech¹, French Institute for Research in Computer Science and Automation², University of Cologne³, Royal Netherlands Meteorological Institute⁴, Central Institution for Meteorology and Geodynamics⁵, University of Ljubljana⁶, University of Iowa⁷, European Centre for Medium-Range Weather Forecasts⁸, National Oceanic and Atmospheric Administration⁹, Technical University of Madrid¹⁰, Finnish Meteorological Institute¹¹, World Meteorological Organization¹², University of Brescia¹³

18 May 2015-Atmospheric Chemistry and Physics

TL;DR: In this article, the authors review the current status of data assimilation in atmospheric chemistry models with a particular focus on future prospects for data-assimilation in Coupled Chemistry Meteorology Models (CCMM).

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Abstract: . Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of three-dimensional chemical (including aerosol) concentrations and perform inverse modeling of input variables or model parameters (e.g., emissions). Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. They offer the possibility to assimilate both meteorological and chemical data; however, because CCMM are fairly recent, data assimilation in CCMM has been limited to date. We review here the current status of data assimilation in atmospheric chemistry models with a particular focus on future prospects for data assimilation in CCMM. We first review the methods available for data assimilation in atmospheric models, including variational methods, ensemble Kalman filters, and hybrid methods. Next, we review past applications that have included chemical data assimilation in chemical transport models (CTM) and in CCMM. Observational data sets available for chemical data assimilation are described, including surface data, surface-based remote sensing, airborne data, and satellite data. Several case studies of chemical data assimilation in CCMM are presented to highlight the benefits obtained by assimilating chemical data in CCMM. A case study of data assimilation to constrain emissions is also presented. There are few examples to date of joint meteorological and chemical data assimilation in CCMM and potential difficulties associated with data assimilation in CCMM are discussed. As the number of variables being assimilated increases, it is essential to characterize correctly the errors; in particular, the specification of error cross-correlations may be problematic. In some cases, offline diagnostics are necessary to ensure that data assimilation can truly improve model performance. However, the main challenge is likely to be the paucity of chemical data available for assimilation in CCMM.

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194 citations

Journal Article•DOI•

Real-time air quality forecasting, part II: State of the science, current research needs, and future prospects

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Yang Zhang¹, Marc Bocquet, Vivien Mallet, Christian Seigneur, Alexander Baklanov² - Show less +1 more•Institutions (2)

North Carolina State University¹, Danish Meteorological Institute²

01 Dec 2012-Atmospheric Environment

TL;DR: A new generation of comprehensive RT-AQF model systems, to emerge in the coming decades, will be based on state-of-the-science 3-D RT- AQF models, supplemented with efficient data assimilation techniques and sophisticated statistical models, and supported with modern numerical/computational technologies and a suite of real-time observational data from all platforms.

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185 citations

Cites background from "Technical Note: The air quality mod..."

..., 1999), and a configuration of Polair3D from Polyphemus (Mallet et al., 2007)....
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...At present, heterogeneous reactions other than heterogeneous hydrolysis of N2O5 are not included in most RT-AQF models, although some models such as Polyphemus include also heterogeneous reactions of HO2, NO3, and NO2 on particles....
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...Similarly, SVOC emissions and transformation using the casting, part II: State of the science, current research needs, and future 2.02.041 hydrophobic/hydrophilic organic (H2O) molecular approach have been incorporated into Polyphemus to provide similar improvements and considerably reduce discrepancies between model predictions and ambient measurements (Couvidat et al., 2011)....
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...Kim et al. (2009) compared CB05 and RACM2 within Polyphemus and found that uncertainties in the kinetics of some major inorganic reactions (oxidation of NO by O3 and HO2) led to uncertainties commensurate with those due to the casting, part II: State of the science, current research needs, and future 2.02.041 organic chemistry (taking into account compensation of errors in the organic chemistry of the twomechanisms)....
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...The members of the ensemble can be either models developed by different teams (e.g., McKeen et al., 2005; van Loon et al., 2007) or models built within the same numerical platform (e.g., Mallet et al., 2007)....
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Journal Article•DOI•

Operational model evaluation for particulate matter in Europe and North America in the context of AQMEII

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Efisio Solazzo, Roberto Bianconi, Guido Pirovano, Volker Matthias, Robert Vautard¹, Michael D. Moran², K. Wyat Appel³, Bertrand Bessagnet, Jørgen Brandt⁴, Jesper H. Christensen⁴, Charles Chemel⁵, Isabelle Coll⁶, Joana Ferreira⁷, Renate Forkel⁸, Xavier Vazhappilly Francis⁵, Georg Grell⁹, P. Grossi, A. B. Hansen⁴, Ana Isabel Miranda⁷, Uarporn Nopmongcol¹⁰, Marje Prank¹¹, Karine Sartelet¹², Martijn Schaap¹³, Jeremy D. Silver⁴, Ranjeet S. Sokhi⁵, Julius Vira¹¹, Johannes Werhahn⁸, Ralf Wolke¹⁴, Greg Yarwood¹⁰, Junhua Zhang², S. Trivikrama Rao³, Stefano Galmarini - Show less +28 more•Institutions (14)

Centre national de la recherche scientifique¹, Environment Canada², United States Environmental Protection Agency³, Aarhus University⁴, University of Hertfordshire⁵, Paris Diderot University⁶, University of Aveiro⁷, Karlsruhe Institute of Technology⁸, National Oceanic and Atmospheric Administration⁹, Business International Corporation¹⁰, Finnish Meteorological Institute¹¹, École des ponts ParisTech¹², Netherlands Organisation for Applied Scientific Research¹³, Leibniz Association¹⁴

01 Jun 2012-Atmospheric Environment

TL;DR: In this paper, the authors compare the results of ten state-of-the-science regional air quality (AQ) modeling systems for full-year simulations of 2006 in the context of AQMEII, whose main goals are model inter-comparison and evaluation.

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175 citations

Additional excerpts

...These are: 160 - CHIMERE (Bessagnet et al., 2004); - POLYPHEMUS (Sartelet et al., 2007; Mallet et al., 2007); - CAMx (Environ., 2010); - COSMO-MUSCAT (Multi Scale Chemistry Aerosol Model) (Wolke et al., 2004; Renner and Wolke, 2010); 165 - SILAM (Sofiev et al., 2006); - DEHM (Brandt et al., 2007);…...
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...These are: 160 - CHIMERE (Bessagnet et al., 2004); - POLYPHEMUS (Sartelet et al., 2007; Mallet et al., 2007); - CAMx (Environ., 2010); - COSMO-MUSCAT (Multi Scale Chemistry Aerosol Model) (Wolke et al., 2004; Renner and Wolke, 2010); 165 - SILAM (Sofiev et al., 2006); - DEHM (Brandt et al., 2007); - CMAQ (Foley et al., 2010); - LOTOS-EUROS (Long term Ozone simulation-European Operational Smog Model) (Schaap et al., 2008); 170 - AURAMS (Gong et al., 2006; Smyth et al., 2009) The CHIMERE, CAMx, CMAQ and DEHM models have been applied over both continents, while the POLYPHEMUS, COSMO-MUSCAT, SILAM, and LOTOS-EUROS models were applied for the EU only....
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...Most of the simulations for EU (CHIMERE, 175 POLYPHEMUS, CAMx, DEHM) used meteorological fields generated by different versions of the 5 th Generation Mesoscale Model (MM5; Dudhia, 1993)....
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..., 2004); - POLYPHEMUS (Sartelet et al., 2007; Mallet et al., 2007); - CAMx (Environ....
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Journal Article•DOI•

Model evaluation and ensemble modelling of surface-level ozone in Europe and North America in the context of AQMEII

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Efisio Solazzo, Roberto Bianconi, Robert Vautard¹, K. Wyat Appel², Michael D. Moran³, Christian Hogrefe², Bertrand Bessagnet, Jørgen Brandt⁴, Jesper H. Christensen⁴, Charles Chemel⁵, Isabelle Coll⁶, Hugo Denier van der Gon⁷, Joana Ferreira⁸, Renate Forkel, Xavier Vazhappilly Francis⁵, George Grell⁹, P. Grossi, A. B. Hansen⁴, Amela Jeričević¹⁰, Lukša Kraljević¹⁰, Ana Isabel Miranda⁸, Uarporn Nopmongcol¹¹, Guido Pirovano, Marje Prank¹², Angelo Riccio¹³, Karine Sartelet¹⁴, Martijn Schaap⁷, Jeremy D. Silver⁴, Ranjeet S. Sokhi⁵, Julius Vira¹², Johannes Werhahn, Ralf Wolke¹⁵, Greg Yarwood¹¹, Junhua Zhang³, S. Trivikrama Rao², Stefano Galmarini - Show less +32 more•Institutions (15)

Centre national de la recherche scientifique¹, United States Environmental Protection Agency², Environment Canada³, Aarhus University⁴, University of Hertfordshire⁵, Paris Diderot University⁶, Netherlands Organisation for Applied Scientific Research⁷, University of Aveiro⁸, National Oceanic and Atmospheric Administration⁹, Croatian Meteorological and Hydrological Service¹⁰, Business International Corporation¹¹, Finnish Meteorological Institute¹², Applied Science Private University¹³, École des ponts ParisTech¹⁴, Leibniz Association¹⁵

01 Jun 2012-Atmospheric Environment

TL;DR: In this paper, the authors investigated the optimal ensemble size and quality of the members based on a clustering methodology to build a skilful ensemble based on model association and data clustering, which makes no use of priori knowledge of model skill.

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157 citations

Additional excerpts

...The AQ models participating in the exercise, listed below, have been extensively documented in the scientific literature (including sensitivity tests and evaluation studies): - CMAQ (Byun and Schere, 2006) - CAMx (ENVIRON, 2010) - CHIMERE (Schmidt et al., 2001; Bessagnet et al., 2004) - MUSCAT (Wolke et al., 2004; Renner and Wolke, 2010) - DEHM (Brandt et al., 2007) - POLYPHEMUS (Mallet et al., 2007; Sartelet et al., 2012) - EUROS (Schaap et al., 2008) - SILAM (Sofiev et al., 2006) - AURAMS (Gong et al., 2006; Smyth et al., 2009) - EMEP (Simpson et al., 2003; Jeri cevi c et al., 2010) - WRF/Chem (http://www.acd.ucar.edu/wrf-chem/) The combination of meteorological and chemical transport models varies for each group (with the only exception being theWRF model with the WRF/Chem model, which was used twice for EU), thus allowing analysis of a diversified set of model output, which is necessary to sample the spectrumof uncertaintywithin anensemble....
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..., 2007) - POLYPHEMUS (Mallet et al., 2007; Sartelet et al., 2012) - EUROS (Schaap et al....
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...…(Schmidt et al., 2001; Bessagnet et al., 2004) - MUSCAT (Wolke et al., 2004; Renner and Wolke, 2010) - DEHM (Brandt et al., 2007) - POLYPHEMUS (Mallet et al., 2007; Sartelet et al., 2012) - EUROS (Schaap et al., 2008) - SILAM (Sofiev et al., 2006) - AURAMS (Gong et al., 2006; Smyth et al.,…...
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References

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Journal Article•DOI•

A limited memory algorithm for bound constrained optimization

[...]

Richard H. Byrd, Peihuang Lu, Jorge Nocedal, Ciyou Zhu

01 Sep 1995-SIAM Journal on Scientific Computing

TL;DR: An algorithm for solving large nonlinear optimization problems with simple bounds is described, based on the gradient projection method and uses a limited memory BFGS matrix to approximate the Hessian of the objective function.

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Abstract: An algorithm for solving large nonlinear optimization problems with simple bounds is described. It is based on the gradient projection method and uses a limited memory BFGS matrix to approximate the Hessian of the objective function. It is shown how to take advantage of the form of the limited memory approximation to implement the algorithm efficiently. The results of numerical tests on a set of large problems are reported.

...read moreread less

5,079 citations

Journal Article•DOI•

Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics

[...]

Geir Evensen

15 May 1994-Journal of Geophysical Research

TL;DR: In this article, a new sequential data assimilation method is proposed based on Monte Carlo methods, a better alternative than solving the traditional and computationally extremely demanding approximate error covariance equation used in the extended Kalman filter.

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Abstract: A new sequential data assimilation method is discussed. It is based on forecasting the error statistics using Monte Carlo methods, a better alternative than solving the traditional and computationally extremely demanding approximate error covariance equation used in the extended Kalman filter. The unbounded error growth found in the extended Kalman filter, which is caused by an overly simplified closure in the error covariance equation, is completely eliminated. Open boundaries can be handled as long as the ocean model is well posed. Well-known numerical instabilities associated with the error covariance equation are avoided because storage and evolution of the error covariance matrix itself are not needed. The results are also better than what is provided by the extended Kalman filter since there is no closure problem and the quality of the forecast error statistics therefore improves. The method should be feasible also for more sophisticated primitive equation models. The computational load for reasonable accuracy is only a fraction of what is required for the extended Kalman filter and is given by the storage of, say, 100 model states for an ensemble size of 100 and thus CPU requirements of the order of the cost of 100 model integrations. The proposed method can therefore be used with realistic nonlinear ocean models on large domains on existing computers, and it is also well suited for parallel computers and clusters of workstations where each processor integrates a few members of the ensemble.

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4,816 citations

"Technical Note: The air quality mod..." refers methods in this paper

...3.2 Data assimilation Four data assimilation algorithms are available in Polyphemus: optimal interpolation, ensemble Kalman filter (Evensen, 1994), reduced-rank square root Kalman filter (Heemink et al., 2001) and 4D-Var (Le Dimet and Talagrand, 1986)....
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...Four data assimilation algorithms are available in Polyphemus: optimal interpolation, ensemble Kalman filter (Evensen, 1994), reduced-rank square root Kalman filter (Heemink et al....
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Journal Article•DOI•

A parametric model of vertical eddy fluxes in the atmosphere

[...]

Jean-François Louis¹•Institutions (1)

European Centre for Medium-Range Weather Forecasts¹

01 Sep 1979-Boundary-Layer Meteorology

TL;DR: In this paper, a model for the representation of vertical eddy fluxes of heat, momentum and water vapour in a forecast model is presented, and two tests are presented, using the scheme in a one-dimensional model: the simulation of the diurnal cycle and the transformation of a polar air mass moving over the warm sea.

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Abstract: A scheme for the representation of the vertical eddy fluxes of heat, momentum and water vapour in a forecast model is presented. An important feature of the scheme is the dependence of the diffusion coefficients on the static stability of the atmosphere. Two tests are presented, using the scheme in a one-dimensional model: the simulation of the diurnal cycle, and the transformation of a polar air mass moving over the warm sea.

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2,357 citations

Report•DOI•

A limited-memory algorithm for bound-constrained optimization

[...]

Richard H. Byrd, L. Peihuang, Jorge Nocedal

01 Mar 1996

TL;DR: An algorithm for solving large nonlinear optimization problems with simple bounds is described, based on the gradient projection method and uses a limited-memory BFGS matrix to approximate the Hessian of the objective function.

...read moreread less

Abstract: An algorithm for solving large nonlinear optimization problems with simple bounds is described. It is based on the gradient projection method and uses a limited-memory BFGS matrix to approximate the Hessian of the objective function. We show how to take advantage of the form of the limited-memory approximation to implement the algorithm efficiently. The results of numerical tests on a set of large problems are reported.

...read moreread less

1,581 citations

"Technical Note: The air quality mod..." refers methods in this paper

...The minimization is performed by L-BFGS (Byrd et al., 1995), using gradients of the cost function....
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Journal Article•DOI•

Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects

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François-Xavier Le Dimet, Olivier Talagrand¹•Institutions (1)

École Normale Supérieure¹

01 Mar 1986-Tellus A

TL;DR: In this paper, two general algorithms for solving constrained minimization problems are presented and discussed in the context of analysis and assimilation of meteorological observations, in particular in terms of their computational cost.

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Abstract: Two general algorithms for solving constrained minimization problems are presented and discussed in the context of analysis and assimilation of meteorological observations. In both algorithms, the original constrained problem is transformed by appropriate modifications into one unconstrained problem, or into a sequence of unconstrained problems. The main advantage of proceeding in this way is that the new unconstrained problems can be solved by classical descent algorithms, thus avoiding the need of directly solving the Euler-Lagrange equations of the original constrained problem. The first algorithm presented in the augmented lagrangian algorithm. It generalizes the more classical penalty and duality algorithms. The second algorithm, inspired from optimal control techniques, is based on an appropriate use of an adjoint dynamical equation, and seems to be particularly well adapted to the assimilation of observations distributed in time. Simple numerical examples show the ability of these algorithms to solve non-linear minimization problems of the type encountered in meteorology. Their possible use in more complex situations is discussed, in particular in terms of their computational cost. DOI: 10.1111/j.1600-0870.1986.tb00459.x

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1,572 citations