Does increased atmospheric resolution improve seasonal climate predictions?

Adam A Scaife,Yu Nie,Ruth Comer,Malcolm Roberts,Nick Dunstone,Walter Robinson,Philip Davis,Joanne Camp,Nicola Martin,Hong‐Li Ren,Pier Luigi Vidale,Craig Maclachlan,Doug Smith,Margaret Gordon

doi:10.1002/asl.922

Abstract

AbstractWe assess the impact of atmospheric horizontal resolution on the prediction skill and fidelity of seasonal forecasts. We show the response to an increase of atmospheric resolution from 0.8 to 0.3° horizontal grid spacing in parallel ensembles of forecasts. Changes in the prediction skill of major modes of tropical El Nino Southern Oscillation (ENSO) and extratropical North Atlantic Oscillation (NAO) variability are small and not detected and there is no discernible impact on the weak signal‐to‐noise ratio in seasonal predictions of the winter NAO at this range of resolutions. Although studies have shown improvements in the simulation of tropical cyclones as model resolution is increased, we find little impact on seasonal prediction skill of either their numbers or intensity. Over this range of resolutions it appears that the benefit of increasing atmospheric resolution to seasonal climate predictions is minimal. However, at yet finer scales there appears to be increased eddy feedback which could strengthen weak signals in predictions of the NAO. Until prediction systems can be run operationally at these scales, it may be better to use additional computing resources for other enhancements such as increased ensemble size, for which there is a clear benefit in extratropical seasonal prediction skill.

Highlights

Studies with global climate models show benefits from increasing atmospheric resolution (e.g., Roberts et al, 2018), with modest increases in blocking frequency (Berckmans et al, 2013; Schiemann et al, 2017), improvements in regional climatology (e.g., Yao et al, 2017) and improvements in rainfall variability (e.g., Kopparla et al, 2013)
We have examined the effects of more than doubling atmospheric resolution, over a range of 0.83 to 0.35, on seasonal prediction skill in parallel ensemble hindcasts
No study can carry out a fully comprehensive analysis of seasonal hindcast skill, we examined the skill of the main tropical (ENSO) and extratropical (NAO) modes of variability and what are arguably the most devastating hydrometeorological extreme events; all of which have previously been shown to exhibit predictability on seasonal timescales

Summary

Introduction

Studies with global climate models show benefits from increasing atmospheric resolution (e.g., Roberts et al, 2018), with modest increases in blocking frequency (Berckmans et al, 2013; Schiemann et al, 2017), improvements in regional climatology (e.g., Yao et al, 2017) and improvements in rainfall variability (e.g., Kopparla et al, 2013). Studies have shown improvements in the simulation of tropical cyclones as model resolution is increased, we find little impact on seasonal prediction skill of either their numbers or intensity.

Results

Conclusion