Articles | Volume 11, issue 8
https://doi.org/10.5194/gmd-11-3391-2018
https://doi.org/10.5194/gmd-11-3391-2018
Development and technical paper
 | 
21 Aug 2018
Development and technical paper |  | 21 Aug 2018

Accelerating simulations using REDCHEM_v0.0 for atmospheric chemistry mechanism reduction

Zacharias Marinou Nikolaou, Jyh-Yuan Chen, Yiannis Proestos, Jos Lelieveld, and Rolf Sander

Related authors

Global projections of heat stress at high temporal resolution using machine learning
Pantelis Georgiades, Theo Economou, Yiannis Proestos, Jose Araya, Jos Lelieveld, and Marco Neira
Earth Syst. Sci. Data, 17, 1153–1171, https://doi.org/10.5194/essd-17-1153-2025,https://doi.org/10.5194/essd-17-1153-2025, 2025
Short summary
The influence of ammonia emissions on the size-resolved global atmospheric aerosol composition and acidity
Xurong Wang, Alexandra P. Tsimpidi, Zhenqi Luo, Benedikt Steil, Andrea Pozzer, Jos Lelieveld, and Vlassis A. Karydis
EGUsphere, https://doi.org/10.5194/egusphere-2025-527,https://doi.org/10.5194/egusphere-2025-527, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Influence of land cover change on atmospheric organic gases, aerosols, and radiative effects
Ryan Vella, Matthew Forrest, Andrea Pozzer, Alexandra P. Tsimpidi, Thomas Hickler, Jos Lelieveld, and Holger Tost
Atmos. Chem. Phys., 25, 243–262, https://doi.org/10.5194/acp-25-243-2025,https://doi.org/10.5194/acp-25-243-2025, 2025
Short summary
Optimized step size control within the Rosenbrock solvers for stiff chemical ODE systems in KPP version 2.2.3_rs4
Raphael Dreger, Timo Kirfel, Andrea Pozzer, Simon Rosanka, Rolf Sander, and Domenico Taraborrelli
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-166,https://doi.org/10.5194/gmd-2024-166, 2025
Preprint under review for GMD
Short summary
Influence of ambient NO and NO2 on the quantification of total peroxy nitrates (∑PNs) and total alkyl nitrates (∑ANs) by thermal dissociation cavity ring-down spectroscopy (TD-CRDS)
Laura Wüst, Patrick Dewald, Gunther N. T. E. Türk, Jos Lelieveld, and John N. Crowley
EGUsphere, https://doi.org/10.5194/egusphere-2024-3694,https://doi.org/10.5194/egusphere-2024-3694, 2024
Short summary

Related subject area

Atmospheric sciences
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025,https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025,https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary
NeuralMie (v1.0): an aerosol optics emulator
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025,https://doi.org/10.5194/gmd-18-1809-2025, 2025
Short summary
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025,https://doi.org/10.5194/gmd-18-1769-2025, 2025
Short summary
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025,https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary

Cited articles

Carter, W.: Development and evaluation of the saprc-99 chemical mechanism, Air Pollution Research Center and College of Engineering Center for Environmental Research and Technology, University of California, Riverside, CA, USA, available at: http://www.cert.ucr.edu/~carter/SAPRC/ (last access: 5 March 2018), 2000. a
Chen, Y. and Chen, J.: Application of Jacobian defined direct interaction coefficient in DRGEP-based chemical mechanism reduction methods using different graph search algorithms, Combust. Flame, 174, 77–84, 2016. a
Christou, M., Christoudias, T., Morillo, J., Alvarez, D., and Merx, H.: Earth system modelling on system-level heterogeneous architectures: EMAC (version 2.42) on the Dynamical Exascale Entry Platform (DEEP), Geosci. Model Dev., 9, 3483–3491, https://doi.org/10.5194/gmd-9-3483-2016, 2016. a
Daescu, D., Sandu, A., and Carmichael, G.: Direct and Adjoint Sensitivity Analysis of Chemical Kinetic Systems with KPP: II – Validation and Numerical Experiments, Atmos. Environ., 37, 5097–5114, 2003. a
Damian, V., Sandu, A., Damian, M., Potra, F., and Carmichael, G.: The Kinetic PreProcessor KPP–A Software Environment for Solving Chemical Kinetics, Comput. Chem. Eng., 26, 1567–1579, 2002. a
Download
Short summary
Chemistry is an important component of the atmosphere that describes many important physical processes. However, atmospheric chemical mechanisms include hundreds of species and reactions, posing a significant computational load. In this work, we use a powerful reduction method in order to develop a computationally faster chemical mechanism from a detailed mechanism. This enables accelerated simulations, which can be used to examine a wider range of processes in increased detail.
Share