Submitted as: methods for assessment of models
28 Oct 2021
Submitted as: methods for assessment of models | 28 Oct 2021
Status: this preprint is currently under review for the journal GMD.

Metrics for Intercomparison of Remapping Algorithms (MIRA) applied to Earth System Models

Vijay S. Mahadevan1, Jorge E. Guerra2, Xiangmin Jiao3, Paul Kuberry4, Yipeng Li3, Paul Ullrich5, Robert Jacob1, Pavel Bochev4, and Philip Jones6 Vijay S. Mahadevan et al.
  • 1Mathematics and Computational Science Division, Argonne National Laboratory, Lemont, IL 60439, USA
  • 2OU/CIMMS, NOAA National Severe Storms Laboratory, Norman, OK, USA
  • 3Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY 11704, USA
  • 4Center for Computing Research, Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87125, USA
  • 5Department of Land, Air and Water Resources, University of California, Davis, CA 95616, USA
  • 6Fluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA

Abstract. Strongly coupled nonlinear phenomena such as those described by Earth System Models (ESM) are composed of multiple component models with independent mesh topologies and scalable numerical solvers. A common operation in ESM is to remap or interpolate results from one component's computational mesh to another, e.g., from the atmosphere to the ocean, during the temporal integration of the coupled system. Several remapping schemes are currently in use or available for ESM. However, a unified approach to compare the properties of these different schemes has not been attempted previously. We present a rigorous methodology for the evaluation and intercomparison of remapping methods through an independently implemented suite of metrics that measure the ability of a method to adhere to constraints such as grid independence, monotonicity, global conservation, and local extrema or feature preservation. A comprehensive set of numerical evaluations are conducted based on a progression of scalar fields from idealized and smooth to more general climate data with strong discontinuities and strict bounds. We examine four remapping algorithms with distinct design approaches, namely ESMF Regrid, TempestRemap, Generalized Moving-Least-Squares (GMLS) with post-processing filters, and Weighted-Least-Squares Essentially Non-oscillatory Remap (WLS-ENOR) method. By repeated iterative application of the high-order remapping methods to the test fields, we verify the accuracy of each scheme in terms of their observed convergence order for smooth data and determine the bounded error propagation using the challenging, realistic field data on both uniform and regionally refined mesh cases. In addition to retaining high-order accuracy under idealized conditions, the methods also demonstrate robust remapping performance when dealing with non-smooth data. There is a failure to maintain monotonicity in the traditional L2-minimization approaches used in ESMF and TempestRemap, in contrast to stable recovery through nonlinear filters used in both meshless (GMLS) and hybrid mesh-based (WLS-ENOR) schemes. Local feature preservation analysis indicates that high-order methods perform better than low-order dissipative schemes for all test cases. The behavior of these remappers remains consistent when applied on regionally refined meshes, indicating mesh invariant implementations. The MIRA intercomparison protocol proposed in this paper and the detailed comparison of the four algorithms demonstrate that the new schemes, namely GMLS and WLS-ENOR, are competitive compared to standard conservative minimization methods requiring computation of mesh intersections. The work presented in this paper provides a foundation that can be extended to include complex field definitions, realistic mesh topologies, and spectral element discretizations thereby allowing for a more complete analysis of production-ready remapping packages.

Vijay S. Mahadevan et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • AC1: 'Author addition: Dr. David Marsico (UCDavis)', Vijay Mahadevan, 26 Nov 2021
  • RC1: 'Comment on gmd-2021-323', Anonymous Referee #1, 26 Jan 2022
    • AC2: 'Reply on RC1', Vijay Mahadevan, 17 Feb 2022
  • RC2: 'Comment on gmd-2021-323', Anonymous Referee #2, 02 Feb 2022

Vijay S. Mahadevan et al.

Data sets

MIRA-Datasets: Datasets from Metrics for Intercomparison of Remapping Algorithms Mahadevan, Vijay; Guerra, Jorge; Kuberry, Paul; Jiao, Xiangmin

Model code and software

MIRA: Metrics for Intercomparison of Remapping Algorithms Guerra, Jorge; Mahadevan, Vijay; Kuberry, Paul; Jiao, Xiangmin; Li, Yipeng

Vijay S. Mahadevan et al.


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Short summary
Coupled Earth System Models require transfer of field data between multiple components with varying spatial resolutions to determine the correct climate behavior. We present the Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol to evaluate the accuracy, conservation properties, monotonicity and local feature preservation of four different remapper algorithms, for various unstructured mesh problems of interest. Future extensions to more practical use cases are also discussed.