Bruno Sportisse

Uncertainty in a chemistry-transport model due to physical parameterizations and numerical approximations: An ensemble approach applied to ozone modeling

This paper estimates the uncertainty in the outputs of a chemistry-transport model due to physical parameterizations and numerical approximations. An ensemble of 20 simulations is generated from a reference simulation in which one key parameterization (chemical mechanism, dry deposition parameterization, turbulent closure, etc.) or one numerical approximation (grid size, splitting method, etc.) is changed at a time. Intercomparisons of the simulations and comparisons with observations allow us to assess the impact of each parameterization and numerical approximation and the robustness of the model. An ensemble of 16 simulations is also generated with multiple changes in the reference simulation in order to estimate the overall uncertainty. The case study is a four-month simulation of ozone concentrations over Europe in 2001 performed using the modeling system Polyphemus. It is shown that there is a high uncertainty due to the physical parameterizations (notably the turbulence closure and the chemical mechanism). The low robustness suggests that ensemble approaches are necessary in most applications.

Development and validation of a fully modular platform for numerical modelling of air pollution: POLAIR

This paper describes a three-dimensional chemistry transport model, POLAIR, with a special focus on numerical aspects. POLAIR is a fully modular eulerian model. Several different chemical mechanisms are available, which can deal with photochemistry (Racm, Radm, etc.), continental impact (e.g. passive transport), mercury, aerosols, etc. POLAIR is designed to enable simulations from regional scales to continental scales. A few simulations at those scales have been conducted to assess and improve the code. Beyond forward simulations, inverse modelling and data assimilation can be performed, thanks to the tangent linear and adjoint versions of POLAIR, which are available through automatic differentiation.

A stochastic approach for the numerical simulation of the general dynamics equation for aerosols

We present in this article a stochastic algorithm based mainly on [Monte Carlo Methods and Applications 5(1) (1999) 1; Stochastic particle approximations for Smoluchowskis coagulation equation. Technical Report, Weierstrass-Institut for Applied Analysis and Stochastics, 2000. Preprint No. 585] applied to the integration of the General Dynamics Equation (GDE) for aerosols. This algorithm is validated by comparison with analytical solutions of the coagulation-condensation model and may provide an accurate reference solution in cases for which no analytical solution is available.

Numerical simulation of aqueous-phase atmospheric models: use of a non-autonomous Rosenbrock method

We present in this article an efficient numerical solver for the time integration of atmospheric multiphase chemical kinetics. This solver is based on a second-order Rosenbrock scheme, that has been proposed by Verwer et al. (SIAM J. Sci. Comput. 20 (4) (1999) 1456) for gas-phase chemical kinetics. We show that the stiff time dependence of cloudy events (through liquid water content) has to be solved by the numerical scheme and a non-autonomous version has to be used. We benchmark the non-autonomous ROS2 scheme with the classical LSODE solver for two kinetic schemes. For detailed schemes such as RADM2, the speed-up is of magnitude 5 for the same accuracy.

Numerical and theoretical investigation of a simplified model for the parameterization of below-cloud scavenging by falling raindrops

The aim of this article is to propose an appropriate framework for investigating the validity of usual parameterizations of below-cloud scavenging by falling raindrops. We recall the underlying models and we study an adimensionalized form of the exact model in a simplified case (monodisperse raindrops and passive tracer) by defining some key parameters. We show that these parameters control the validity of the parameterization that we recover through asymptotic expansion. Some numerical tests for species HNO3 and SO2 illustrate these results.

Reduction of Multiphase Atmospheric Chemistry

The aim of this article is to investigate the dynamical behaviour ofmultiphase atmospheric chemical mechanisms. Reducing procedures areapplied to a multiphase chemical box model including gas-phasereactions, aqueous-phase reactions and interfacial mass transfer. The lumping of species is computed in an automatic wayusing an efficient algorithm (apla). The computed lumped species arerelated to the fast behaviour of chemical and microphysical processessuch as Chapman cycle, ionic dissociations within the cloud drops andinterfacial Henrys equilibria. Depending on some parameters (liquidwater content, droplet radius) mixed lumped species (including both phases) may also becomputed. We show the existence of hierarchical reduced models due to the existence ofmultiple timescales. We use a special algorithm (dan2) in order tosolve the reduced models. Such models are accurate and the relative errorremains under the threshold of 1%. The speed-up is up to a factor 5comparedwith a fully implicit method (Gear) for the same accuracy. The key pointis that it provides a good qualitative understanding for the behaviourof the kinetic scheme.

Solving reduced chemical models in air pollution modelling

This article follows [R. Djouad, B. Sportisse, Appl. Numer. Math. 43 (2002) 383] in which we have proposed an automatic method in order to generate reduced atmospheric chemical mechanisms. On the basis of the slow/fast behaviour of chemical kinetics the exact model is replaced by a differential-algebraic system. We propose here an easy to perform algorithm in order to integrate such systems with a low CPU cost. Comparison is made with some classical solvers such as Euler Backward Implicit (EBI), QSSA and the second-order Rosenbrock method ROS2. This proves the efficiency and the accuracy of the proposed algorithm. We also show that the classical QSSA-like methods cannot be used apart from the framework of reduction procedures, which explains their rather poor accuracy.

MICS Asia Phase II - Sensitivity to the aerosol module

In the framework of the model inter-comparison study - Asia Phase II (MICS2), where eight models are compared over East Asia, this paper studies the influence of different parameterizations used in the aerosol module on the aerosol concentrations of sulfate and nitrate in PM10. An intracomparison of aerosol concentrations is done for March 2001 using different configurations of the aerosol module of one of the model used for the intercomparison. Single modifications of a reference setup for model configurations are performed and compared to a reference case. These modifications concern the size distribution, i.e. the number of sections, and physical processes, i.e. coagulation, condensation/evaporation, cloud chemistry, heterogeneous reactions and sea-salt emissions. Comparing monthly averaged concentrations at different stations, the importance of each parameterization is first assessed. It is found that sulfate concentrations are little sensitive to sea-salt emissions and to whether condensation is computed dynamically or by assuming thermodynamic equilibrium. Nitrate concentrations are little sensitive to cloud chemistry. However, a very high sensitivity to heterogeneous reactions is observed. Thereafter, the variability of the aerosol concentrations to the use of different chemistry transport models (CTMs) and the variability to the use of different parameterizations in the aerosol module are compared. For sulfate, the variability to the use of different parameterizations in the aerosol module is lower than the variability to the use of different CTMs. However, for nitrate, for monthly averaged concentrations averaged over four stations, these two variabilities have the same order of magnitude.

Partitioning techniques and lumping computation for reducing chemical kinetics: APLA: an automatic partitioning and lumping algorithm

The time integration of Air Pollution Models is a difficult task due to numerical stiffness, nonlinearity and coupling between equations and implicit schemes are usually advocated. Based on the slow/fast behaviour of the chemical dynamics, reducing procedures are alternative efficient techniques leading to nonstiff systems. Reduced models are defined by a set of lumped species and algebraic constraints and their validity is related with the correct partitioning of dynamics (species and reactions). By using some axiomatic hypothesis and algebraic properties we propose in this paper an efficient partitioning technique and an algorithm in order to compute the lumping of species in an automatic way. This is applied to four atmospheric chemical mechanisms.

Box models versus eulerian models in air pollution modeling

Abstract Box models are widely used in air pollution modeling. They allow the use of simple computational tools instead of the simulation of 3D Eulerian grid models, given by a large set of partial differential equations. We investigate here the theoretical justification of such box models. The key point is the comparison with the underlying Eulerian model describing the dispersion of pollutants in the atmosphere. We restrict the study to a vertical monodimensional case for more clarity. The main result is that the nonlinearity of the chemical kinetics, which is a characteristic feature of chemistry, induces the loss of accuracy.