CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011

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DATA ASSIMILATION FOR ATMOSPHERIC CHEMISTRY In the regional version of MOCAGE-Valentina, we have performed several experiments assimilating surface ozone measurement. The experiments also differ by the choice of the BECM configuration, in which the correlations and standard deviations matrices come from the ensemble-based diagnostics or from a posteriori diagnostics. All the analyses from these experiments are very well correlated to the observations, what assimilated or validation stations. Comparisons of the analyses with the validation stations show that the use of a BECM with time-dependent length-scales gives the largest correlation. All the analyses have a better correlation with the observations than the direct MOCAGE simulation, but the differences between them are small and we cannot conclude which BECM formulation is the most appropriate to the ozone simulation over Europe. The impact of the BECM formulation has been also difficult to evaluate because the model MOCAGE shows systematic bias in situation with low ozone concentration. So the impact of the analysis process is mostly to remove this bias. 3.4 Development of linear chemistry schemes (S. Massart, D. Cariolle J. Flemming) During those past years a linearised ozone photochemical scheme has been developed for use within GCMs and CTMs. This scheme is widely used for climate simulations and data assimilation studies. The computational cost of this scheme is very low since it only requires an additional continuity equation to be solved in the large scale models. We had therefore extended the methodology to treat other chemical species, in particular a linearised scheme has been derived for CO and was implement in MOCAGE [DA3, DA12, DA4]. CO is one of the most important tropospheric trace gases. In particular because it affects the concentrations of the OH radical. Moreover the main sources of CO are incomplete fossil fuel and biomass burning, which lead to enhanced surface concentrations. And with a lifetime of a few months CO can serve as a tracer for regional and inter-continental transport of polluted air. Within MACC a major development effort of the Global Reactive Gases sub-project is the on-line integration of the chemistry in the IFS (known as C-IFS). C-IFS aims at a modular implementation of the chemical scheme used in several global CTMs including MOCAGE. To complement the complex schemes, linear scheme are explored in C-IFS for their potential in computational demanding application such as high resolution simulations and data assimilation. So, in parallel with the comprehensive detailed chemical schemes, we implemented in C-IFS the linearised parameterisation for CO. (a) GEMS reanalysis (b) High resolution simulation FIG. 3.4: CO concentration (in ppbv) at 500 hPa for the 19 th January 2008. 82 Jan. 2010 – Dec. 2011
DATA ASSIMILATION A two years simulation within C-IFS shows that the linear carbon monoxide chemical scheme produces similar tropospheric concentrations of CO than a more complete tropospheric chemical scheme available in C-IFS. But it underestimates the tropospheric concentrations by 10 to 50 ppbv both compared to the GEMS reanalysis and measurements from the Mozaic dataset. To reduce this tropospheric bias, we adjusted the production minus loss rate term of the linear scheme in order to obtain a similar evolution in the CO total mass than the one extracted from the GEMS reanalysis [5]. This allowed us to run another two years C-IFS simulation that produces global CO fields at a resolution of about 25 km (Fig. 3.4). The evaluation of this simulation in under progress. 3.5 References [4] E. Jaumouillé, S. Massart, A. Piacentini, V.-H. Peuch, and D. Cariolle, (2012), Impact of a time-dependent background error covariance matrix on air quality analysis, Geosci. Model Dev. to be submitted. [5] S. Massart, J. Flemming, D. Cariolle, V. H. Peuch, and L. Jones, (2012), Implementation of the linear carbon monoxide chemical scheme in the European Centre for Medium Range Weather Forecast’s Integrated Forecast System, Geosci. Model Dev. to be submitted. CERFACS ACTIVITY REPORT 83
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CERFACS Scientific Activity Report
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Table des matières 1 Foreword xiii
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9 Publications 40 9.1 Books . . . .
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3 The OpenPALM coupler 104 3.1 Intr
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Table des figures CERFACS chart as
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TABLE DES FIGURES 6 Computational F
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Foreword Welcome to the 2010-2011 S
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CERFACS STRUCTURE CERFACS organizat
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CERFACS STAFF NAME POSITION PERIOD
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CERFACS STAFF SILVA GARZON Ph.D stu
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CERFACS STAFF NAME POSITION PERIOD
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CERFACS Wide-Interest Seminars Pete
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1 Introduction 1.1 Introduction The
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PARALLEL ALGORITHMS PROJECT success
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PARALLEL ALGORITHMS PROJECT Visitor
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3 List of Members of HiePACS HiePAC
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4 Dense and Sparse Matrix Computati
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PARALLEL ALGORITHMS PROJECT Working
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5 Iterative Methods and Preconditio
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PARALLEL ALGORITHMS PROJECT 7.16 An
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Page 97 and 98: 1 Introduction Data assimilation is
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COMPUTATIONAL FLUID DYNAMICS rate-o
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COMPUTATIONAL FLUID DYNAMICS FIG. 2
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7 Aviation and Environment
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INTRODUCTION instead of regular ker
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SIMULATIONS OF AIRCRAFT WAKES AND R
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LARGE SCALE ATMOSPHERIC COMPOSITION
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LARGE SCALE ATMOSPHERIC COMPOSITION
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PUBLICATIONS 4.2 Technical Reports
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CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011

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CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011