Articles | Volume 11, issue 2
https://doi.org/10.5194/gmd-11-575-2018
https://doi.org/10.5194/gmd-11-575-2018
Development and technical paper
 | 
08 Feb 2018
Development and technical paper |  | 08 Feb 2018

Trajectory errors of different numerical integration schemes diagnosed with the MPTRAC advection module driven by ECMWF operational analyses

Thomas Rößler, Olaf Stein, Yi Heng, Paul Baumeister, and Lars Hoffmann

Related authors

Intercomparison of meteorological analyses and trajectories in the Antarctic lower stratosphere with Concordiasi superpressure balloon observations
Lars Hoffmann, Albert Hertzog, Thomas Rößler, Olaf Stein, and Xue Wu
Atmos. Chem. Phys., 17, 8045–8061, https://doi.org/10.5194/acp-17-8045-2017,https://doi.org/10.5194/acp-17-8045-2017, 2017
Short summary

Related subject area

Numerical methods
Explicit stochastic advection algorithms for the regional-scale particle-resolved atmospheric aerosol model WRF-PartMC (v1.0)
Jeffrey H. Curtis, Nicole Riemer, and Matthew West
Geosci. Model Dev., 17, 8399–8420, https://doi.org/10.5194/gmd-17-8399-2024,https://doi.org/10.5194/gmd-17-8399-2024, 2024
Short summary
The Measurement Error Proxy System Model: MEPSM v0.2
Matt J. Fischer
Geosci. Model Dev., 17, 6745–6760, https://doi.org/10.5194/gmd-17-6745-2024,https://doi.org/10.5194/gmd-17-6745-2024, 2024
Short summary
Numerical stabilization methods for level-set-based ice front migration
Gong Cheng, Mathieu Morlighem, and G. Hilmar Gudmundsson
Geosci. Model Dev., 17, 6227–6247, https://doi.org/10.5194/gmd-17-6227-2024,https://doi.org/10.5194/gmd-17-6227-2024, 2024
Short summary
Modelling chemical advection during magma ascent
Hugo Dominguez, Nicolas Riel, and Pierre Lanari
Geosci. Model Dev., 17, 6105–6122, https://doi.org/10.5194/gmd-17-6105-2024,https://doi.org/10.5194/gmd-17-6105-2024, 2024
Short summary
Consistent point data assimilation in Firedrake and Icepack
Reuben W. Nixon-Hill, Daniel Shapero, Colin J. Cotter, and David A. Ham
Geosci. Model Dev., 17, 5369–5386, https://doi.org/10.5194/gmd-17-5369-2024,https://doi.org/10.5194/gmd-17-5369-2024, 2024
Short summary

Cited articles

Bowman, K. P., Lin, J. C., Stohl, A., Draxler, R., Konopka, P., Andrews, A., and Brunner, D.: Input Data Requirements for Lagrangian Trajectory Models, B. Am. Meteorol. Soc., 94, 1051–1058, 2013.
Brioude, J., Angevine, W. M., McKeen, S. A., and Hsie, E.-Y.: Numerical uncertainty at mesoscale in a Lagrangian model in complex terrain, Geosci. Model Dev., 5, 1127–1136, https://doi.org/10.5194/gmd-5-1127-2012, 2012.
Buizza, R., Houtekamer, P. L., Toth, Z., Pellerin, G., Wei, M., and Zhu, Y.: A comparison of the ECMWF, MSC, and NCEP Global ensemble prediction systems, Mon. Weather Rev., 133, 1076–1097, 2005.
Butcher, J. C.: Numerical methods for ordinary differential equations, John Wiley & Sons, 2008.
CDO: Climate Data Operators, available at: http://www.mpimet.mpg.de/cdo (last access: 3 May 2017), 2015.
Download
Short summary
In this study, we performed an assessment of truncation errors and computational efficiency of trajectory calculations using six popular numerical integration schemes of the Runge–Kutta family. More than 5000 transport simulations for different seasons and regions of the free troposphere and stratosphere were conducted, driven by the latest version of ECMWF operational analyses and forecasts. The study provides guidelines to achieve the most accurate and efficient trajectory calculations.