Abstract
The task of providing an optimal analysis of the state of the atmosphere requires the development of novel computational tools that facilitate an efficient integration of observational data into models. In this paper we discuss some of the computational tools developed for the assimilation of chemical data into atmospheric models. We perform a theoretical analysis of discrete and continuous adjoints for stiff differential equation solvers. Software tools particularly tailored for direct and adjoint sensitivity analysis of chemical systems are presented. The adjoint of the state-of-the-art model STEM-III is discussed, together with ozone assimilation results for a realistic test problem.
Chapter PDF
Similar content being viewed by others
References
R. Byrd, P. Lu, and J. Nocedal. A limited memory algorithm for bound constrained optimization. SIAM J. Sci. Stat. Comput., 16(5):1190–1208, 1995.
D. G. Cacuci. Sensitivity theory for nonlinear systems. I. Nonlinear functional analysis approach. J. Math. Phys., 22:2794–2802, 1981.
D. G. Cacuci. Sensitivity theory for nonlinear systems. II. Extensions to additional classes of responses. J. Math. Phys., 22:2803–2812, 1981.
W.P.L. Carter. Implementation of the SAPRC-99 Chemical Mechanism into the Models-3 Framework. Technical report, Report to the United States Environmental Protection Agency, January 2000.
D. Daescu, A. Sandu, and G.R. Carmichael. Direct and Adjoint Sensitivity Analysis of Chemical Kinetic Systems with KPP: II-Numerical Validation and Applications. submitted to Atmospheric Environment, 2002.
V. Damian, A. Sandu, M. Damian, F. Potra, and G.R. Carmichael. The kinetic pre-processor kpp — a software environment for solving chemical kinetics. (Computers and Chemical Engineering), 26:1567–1579, 2002.
A. M. Dunker. The decoupled direct method for calculating sensitivity coefficients in chemical kinetics. Journal of Chemical Physics, 81:2385, 1984.
H. Elbern and H. Schmidt. Ozone episode analysis by 4D-Var chemistry data assimilation. Journal of Geophysical Research, 106(D4):3569–3590, 2001.
William W. Hager. Runge-Kutta methods in optimal control and the transformed adjoint system. Numerische Mathematik, 87(2):247–282, 2000.
E. Hairer, S.P. Norsett, and G. Wanner. Solving Ordinary Differential Equations I. Nonstiff Problems. Springer-Verlag, Berlin, 1993.
E. Hairer and G. Wanner. Solving Ordinary Differential Equations II. Stiff and Differential-Algebraic Problems. Springer-Verlag, Berlin, 1991.
Menut L., Vautard R., Beekmann M.,, and Honor C. Sensitivity of photochemical pollution using the adjoint of a simplified chemistry-transport model. Journal of Geophysical Research-Atmospheres, 105-D12(15): 15,379-15,402, 2000.
G.I. Marchuk. Adjoint Equations and Analysis of Complex Systems. Kluwer Academic Publishers, 1995.
G.I. Marchuk, Agoshkov, and P.V. I.V., Shutyaev. Adjoint Equations and Perturbation Algorithms in Nonlinear Problems. CRC Press, 1996.
P. Miehe, A. Sandu, G.R. Carmichael, Y. Tang, and D. Daescu. A communication library for the parallelization of air quality models on structured grids. (Atmospheric Environment), 36:3917–3930, 2002.
Vautard R., M. Beekmann, and L. Menut. Applications of adjoint modelling in atmospheric chemistry: sensitivity and inverse modelling. Environmental Modeling and Sofware, 15:703–709, 2000.
A. Sandu, D. Daescu, and G.R. Carmichael. Direct and Adjoint Sensitivity Analysis of Chemical Kinetic Systems with KPP: I-Theory and Software Tools, submitted to Atmospheric Environment, 2002.
A. Sandu, D. daescu, and G.R. Carmichael. Discrete Adjoint for Stiff ODE Solvers. In Preparation, 2003.
Z. Sirkes and E. Tziperman. Finite difference of adjoint or adjoint of finite difference? Mon. Weather Rev., 49:5–40, 1997.
K.Y. Wang, D.J. Lary, Shallcross, D.E., Hall aS.M., and Pyle J.A. A review on the use of the adjoint method in four-dimensional atmospheric-chemistry data assimilation. Q.J.R. Meteorol. Soc., 127(576 (Part B)): 2181–2204, 2001.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Carmichael, G.R., Daescu, D.N., Sandu, A., Chai, T. (2003). Computational Aspects of Chemical Data Assimilation into Atmospheric Models. In: Sloot, P.M.A., Abramson, D., Bogdanov, A.V., Gorbachev, Y.E., Dongarra, J.J., Zomaya, A.Y. (eds) Computational Science — ICCS 2003. ICCS 2003. Lecture Notes in Computer Science, vol 2660. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44864-0_28
Download citation
DOI: https://doi.org/10.1007/3-540-44864-0_28
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40197-1
Online ISBN: 978-3-540-44864-8
eBook Packages: Springer Book Archive