Preprints
https://doi.org/10.5194/gmd-2021-392
https://doi.org/10.5194/gmd-2021-392
Submitted as: development and technical paper
 | 
07 Jan 2022
Submitted as: development and technical paper |  | 07 Jan 2022
Status: this preprint was under review for the journal GMD but the revision was not accepted.

Adaptive time step algorithms for the simulation of marine ecosystem models using the transport matrix method implementation Metos3D (v0.5.0)

Markus Pfeil and Thomas Slawig

Abstract. The reduction of the computational effort is desirable for the simulation of marine ecosystem models. Using a marine ecosystem model, the assessment and the validation of annual periodic solutions (i.e., steady annual cycles) against observational data are crucial to identify biogeochemical processes, which, for example, influence the global carbon cycle. For marine ecosystem models, the transport matrix method (TMM) already lowers the runtime of the simulation significantly and enables the application of larger time steps straightforwardly. However, the selection of an appropriate time step is a challenging compromise between accuracy and shortening the runtime. Using an automatic time step adjustment during the computation of a steady annual cycle with the TMM, we present in this paper different algorithms applying either an adaptive step size control or decreasing time steps in order to use the time step always as large as possible without any manual selection. For these methods and a variety of marine ecosystem models of different complexity, the accuracy of the computed steady annual cycle achieved the same accuracy as solutions obtained with a fixed time step. Depending on the complexity of the marine ecosystem model, the application of the methods shortened the runtime significantly. Due to the certain overhead of the adaptive method, the computational effort may be higher in special cases using the adaptive step size control. The presented methods represent computational efficient methods for the simulation of marine ecosystem models using the TMM but without any manual selection of the time step.

Markus Pfeil and Thomas Slawig

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2021-392', Juan Antonio Añel, 22 Feb 2022
    • AC1: 'Reply on CEC1', Markus Pfeil, 30 Mar 2022
  • RC1: 'Comment on gmd-2021-392', Anonymous Referee #1, 13 Apr 2022
    • AC4: 'Reply on RC1', Thomas Slawig, 19 May 2022
  • RC2: 'Comment on gmd-2021-392', Anonymous Referee #2, 22 Apr 2022
    • AC2: 'Reply on RC2', Thomas Slawig, 19 May 2022
    • AC3: 'Reply on RC2', Thomas Slawig, 19 May 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2021-392', Juan Antonio Añel, 22 Feb 2022
    • AC1: 'Reply on CEC1', Markus Pfeil, 30 Mar 2022
  • RC1: 'Comment on gmd-2021-392', Anonymous Referee #1, 13 Apr 2022
    • AC4: 'Reply on RC1', Thomas Slawig, 19 May 2022
  • RC2: 'Comment on gmd-2021-392', Anonymous Referee #2, 22 Apr 2022
    • AC2: 'Reply on RC2', Thomas Slawig, 19 May 2022
    • AC3: 'Reply on RC2', Thomas Slawig, 19 May 2022
Markus Pfeil and Thomas Slawig
Markus Pfeil and Thomas Slawig

Viewed

Total article views: 892 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
620 233 39 892 16 20
  • HTML: 620
  • PDF: 233
  • XML: 39
  • Total: 892
  • BibTeX: 16
  • EndNote: 20
Views and downloads (calculated since 07 Jan 2022)
Cumulative views and downloads (calculated since 07 Jan 2022)

Viewed (geographical distribution)

Total article views: 844 (including HTML, PDF, and XML) Thereof 844 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Mar 2024
Download
Short summary
In investigating the global carbon cycle, shortening the runtime of the simulation of marine ecosystem models is an important issue. We present methods that automatically adjust the time step during the simulation of a steady state using transport matrices. They apply always the time step as large as possible. Two methods reduced the runtime significantly, depending on the complexity of the model. An important property was that small negative concentrations were ignored during the spin-up.