Submitted as: model evaluation paper 30 Jun 2021

Submitted as: model evaluation paper | 30 Jun 2021

Review status: this preprint is currently under review for the journal GMD.

Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models

Eduardo Moreno-Chamarro1, Louis-Philippe Caron1,a, Saskia Loosveldt Tomas1, Oliver Gutjahr2,b, Marie-Pierre Moine3, Dian Putrasahan2, Christopher D. Roberts4, Malcolm J. Roberts5, Retish Senan4, Laurent Terray3, Etienne Tourigny1, and Pier Luigi Vidale6 Eduardo Moreno-Chamarro et al.
  • 1Barcelona Supercomputing Center (BSC), Barcelona, Spain
  • 2Max Planck Institute for Meteorology. Hamburg, Germany
  • 3CECI, Université de Toulouse, CERFACS/CNRS, Toulouse, France
  • 4ECMWF European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom 
  • 5Met Office, Exeter EX1 3PB, United Kingdom
  • 6NCAS-Climate, Department of Meteorology, University of Reading, Reading, United Kingdom
  • anow at: Ouranos, Montreal, H3A 1B9, Canada
  • bnow at: Institut für Meereskunde, Universität Hamburg, Hamburg, Germany

Abstract. We examine the impacts of increased resolution on four long-standing biases using five different climate models developed within the PRIMAVERA project. Atmospheric resolution is increased from ~100–200 km to ~25–50 km, and ocean resolution is increased from ~1° (i.e., eddy-parametrized) to ~0.25° (i.e., eddy-present). For one model, ocean resolution is also increased to 1/12° (i.e., eddy-rich). Fully-coupled general circulation models and their atmosphere-only versions are compared with observations and reanalysis of near-surface temperature, precipitation, cloud cover, net cloud radiative effect, and zonal wind over the period 1980–2014. Both the ensemble mean and individual models are analyzed. Increased resolution especially in the atmosphere helps reduce the surface warm bias over the tropical upwelling regions in the coupled models, with further improvements in the cloud cover and precipitation biases particularly over the tropical South Atlantic. Related to this and to the improvement in the precipitation distribution over the western tropical Pacific, the double Intertropical Convergence Zone bias also weakens with resolution. Overall, increased ocean resolution from ~1° to ~0.25° offers limited improvements or even bias degradation in some models, although an eddy-rich ocean resolution seems beneficial for reducing the biases in North Atlantic temperatures and Gulf Stream path. Despite the improvements, however, large biases in precipitation and cloud cover persist over the whole tropics as well as in the upper-troposphere zonal winds at mid-latitudes in coupled and atmosphere-only models at higher resolutions. The Southern Ocean warm bias also worsens or persists in some coupled models. And a new warm bias emerges in the Labrador Sea in all the high-resolution coupled models. The analysis of the PRIMAVERA models therefore suggests that, to reduce biases, i) increased atmosphere resolution up to ~25–50 km alone might not be sufficient and ii) an eddy-rich ocean resolution might be needed. The study thus adds to evidence that further improved model physics and tuning might be necessary in addition to increased resolution to mitigate biases.

Eduardo Moreno-Chamarro et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-209', Anonymous Referee #1, 23 Jul 2021
    • RC2: 'Reply on RC1', Anonymous Referee #2, 28 Jul 2021

Eduardo Moreno-Chamarro et al.

Eduardo Moreno-Chamarro et al.


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Short summary
Climate models do not fully reproduce observations: they show differences (biases) in regional temperature, precipitation, or cloud cover. Reducing model biases is important to increase our confidence in the climate models' ability to reproduce the future climate change. A model's realism is set by its resolution: the finer it is, the more physical processes and interactions it can resolve. Our paper shows that increasing resolution up to ~25 km can help reduce model biases but not totally.