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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/gmd-2020-221
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-221
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model evaluation paper 09 Sep 2020

Submitted as: model evaluation paper | 09 Sep 2020

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A revised version of this preprint is currently under review for the journal GMD.

Performance of offline passive tracer advection in ROMS (v3.6, revision 904)

Kristen M. Thyng1, Daijiro Kobashi1, Veronica Ruiz-Xomchuk1, Lixin Qu2, Xu Chen3, and Robert D. Hetland1 Kristen M. Thyng et al.
  • 1Department of Oceanography, Texas A&M University, College Station, TX, USA
  • 2Department of Earth System Science, Stanford University, USA
  • 3Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, FL, USA

Abstract. Offline advection schemes allow for low computational cost simulations using existing model output. This study presents the approach and assessment for passive offline tracer advection within the Regional Ocean Modeling System (ROMS). An advantage of running the code within ROMS itself is consistency in the numerics on and offline. We find that the offline tracer model is robust: after about 14 days of simulation (almost 60 advection timescales), the skill score comparing offline output to the online simulation using the TS_U3HADVECTION and TS_C4VADVECTION (3rd-order upstream horizontal advection and 4th-order centered vertical advection) tracer advection schemes is 99.6 % accurate for an offline time step 20 times larger than online, and online output saved with a period below the advection timescale. For tracer advection scheme MPDATA, accuracy is more variable with offline time step and forcing input frequency choices, but is still over 99 % for many reasonable choices. Both schemes are conservative. Important factors for maintaining high offline accuracy are: outputting from the online simulation often enough to resolve the advection timescale, forcing offline using realistic vertical salinity diffusivity values from the online simulation, and using double precision to save results.

Kristen M. Thyng et al.

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Kristen M. Thyng et al.

Data sets

ROMS input files Kristen Thyng, Xu Chen, and Steve Morey https://doi.org/10.6084/m9.figshare.c.5097350.v1

Model code and software

Offline passive tracer in ROMS Kristen Thyng, Daijiro Kobashi, Veronica Ruiz Xomchuk, Lixin Qu, Xu Chen, and Robert D. Hetland https://doi.org/10.5281/zenodo.3991810

Analysis of offline tracer in ROMS Kristen Thyng https://doi.org/10.5281/zenodo.3991820

Run files for online simulation Kristen Thyng https://doi.org/10.5281/zenodo.3991823

Run files for offline passive tracer simulation in ROMS Kristen Thyng and Veronica Ruiz Xomchuk https://doi.org/10.5281/zenodo.3991826

Kristen M. Thyng et al.

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Latest update: 01 Dec 2020
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Short summary
We modified the ROMS ocean model to run in offline mode so that previously-run fields of sea surface height and velocity fields are input to calculate tracer advection without running the full model with a larger time step to run faster. The code was tested with 2 advection schemes and both are robust with over 99% accuracy of the offline to online run after 14 simulation days. This allows for ROMS users to maximize use of new or existing output to quickly run additional tracer simulations.
We modified the ROMS ocean model to run in offline mode so that previously-run fields of sea...
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