Benefits of Increasing the Model Resolution for the Seasonal Forecast Quality in EC-Earth

Prodhomme, Chloé; Batté, Lauriane; Massonnet, François; Davini, Paolo; Bellprat, Omar; Guémas, Virginie; Doblas‐Reyes, Francisco J.

doi:10.1175/jcli-d-16-0117.1

Cited by 59 publications

(39 citation statements)

References 106 publications

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“…Operational seasonal prediction systems are now being at resolutions well beyond one degree (e.g., MacLachlan et al, 2014;Johnson et al, 2018). The effects on prediction skill from further increases in resolution in the atmosphere (e.g., Jung et al, 2012;Jia et al, 2015;Zhu et al, 2015;Prodhomme et al, 2016) or ocean (e.g., Kirtman et al, 2017) is an active research topic and it is not known whether this outweighs the benefits of larger ensemble size (e.g., Scaife et al, 2014;Doi et al, 2019), increased vertical resolution (e.g., Marshall and Scaife, 2010;Butler et al, 2016) or improved initial conditions (e.g., Kumar et al, 2015;Nie et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Does increased atmospheric resolution improve seasonal climate predictions?

Scaife

Camp

Comer

et al. 2019

Atmospheric Science Letters

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We 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.

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Section: Introductionmentioning

confidence: 99%

Does increased atmospheric resolution improve seasonal climate predictions?

Scaife

Camp

Comer

et al. 2019

Atmospheric Science Letters

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“…These assumptions are rarely assessed and individual studies suggest that observational uncertainties might be larger than anticipated (e.g. Addor and Fischer 2015;Prodhomme et al 2016;Massonnet et al 2016). Formal concepts of how to account for observational uncertainties provided by ORs in climate model evaluation are, however, still scarce.…”

Section: Discussionmentioning

confidence: 99%

Uncertainty propagation in observational references to climate model scales

Bellprat

Massonnet

Siegert

et al. 2017

Remote Sensing of Environment

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Climate model simulations and observational references of the Earth's climate are the two primary sources of information used for climate related decision-making. While uncertainties in climate models and observational references have been assessed thoroughly, it has remained difficult to integrate these, partly because of the lack of formal concepts on how to consider observational uncertainties in model-observation comparison. One of the difficulties dealing with observational uncertainty is its propagation to the space-time scales represented by the models. This is a challenge due to the correlation of observational errors in space and time. Here we present an approximation which allows to derive propagation factors to different model scales and apply these to uncertainty estimates provided by the Climate Change Initiative (CCI) sea-surface temperature (SST) dataset. The propagated uncertainty in SST observations is found to systematically lower seasonal forecast skill and to increase the uncertainty in verification of seasonal forecasts, an aspect that remains currently overlooked. Uncertainty in forecast quality assessment is dominated by the shortness of the satellite record. Expanding the record length of these datasets might hence reduce the verification uncertainties more than the efforts to reduce the observational uncertainties.

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“…With an atmospheric resolution of T63L47 (about 1.875 • horizontal grid spacing) and an oceanic resolution of 1.5 • L40 the MPI-ESM-LR decadal prediction system applied in the first phase of MiKlip has a rather moderate spatial resolution. Meanwhile, studies using higher-resolution forecast systems are available, for instance Monerie et al (2017) using 0.5 • grid spacing in the atmosphere and 0.25 • in the ocean and Robson et al (2018) using ∼ 0.9 • in the atmosphere and 0.25 • in the ocean. They focus on oceanic parameters and find skill, e.g., for SSTs, sea ice extent and ocean heat content, respectively.…”

Section: Introductionmentioning

confidence: 99%

Improvement in the decadal prediction skill of the North Atlantic extratropical winter circulation through increased model resolution

Schuster

Grieger

Richling

et al. 2020

Preprint

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In this study the latest version of the MiKlip decadal hindcast system is analyzed, and the effect of an increased horizontal and vertical resolution on the prediction skill of the extratropical winter circulation is assessed. Four different metrics -the storm track, blocking, cyclone and windstorm frequencies -are analyzed in the North Atlantic and European region. The model bias and the deterministic decadal hindcast skill are evaluated in ensembles of five members in a lower-resolution version (LR, atm: T63L47, ocean: 1.5 • L40) and a higher-resolution version (HR, atm: T127L95, ocean: 0.4 • L40) of the MiKlip system based on the Max Planck Institute Earth System model (MPI-ESM). The skill is assessed for the lead winters 2-5 in terms of the anomaly correlation of the quantities' winter averages using initializations between 1978 and 2012. The deterministic predictions are considered skillful if the anomaly correlation is positive and statistically significant. While the LR version shows common shortcomings of lower-resolution climate models, e.g., a storm track that is too zonal and southward displaced as well as a negative bias of blocking frequencies over the eastern North Atlantic and Europe, the HR version counteracts these biases. Cyclones, i.e., their frequencies and characteristics like strength and lifetime, are particularly better represented in HR. As a result, a chain of significantly improved decadal prediction skill between all four metrics is found with the increase in the spatial resolution. While the skill of the storm track is significantly improved primarily over the main source region of synoptic activity -the North Atlantic Current -the other extratropical quantities experience a significant improvement primarily downstream thereof, i.e., in regions where the synoptic systems typically intensify. Thus, the skill of the cyclone frequencies is significantly improved over the central North Atlantic and northern Europe, the skill of the blocking frequencies is significantly improved over the Mediterranean, Scandinavia and eastern Europe, and the skill of the windstorms is significantly improved over Newfoundland and central Europe. Not only is the skill improved with the increase in resolution, but the HR system itself also exhibits significant skill over large areas of the North Atlantic and European sector for all four circulation metrics. These results are particularly promising regarding the high socioeconomic impact of European winter windstorms and blocking situations.Published by Copernicus Publications on behalf of the European Geosciences Union.

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Benefits of Increasing the Model Resolution for the Seasonal Forecast Quality in EC-Earth

Cited by 59 publications

References 106 publications

Does increased atmospheric resolution improve seasonal climate predictions?

Does increased atmospheric resolution improve seasonal climate predictions?

Uncertainty propagation in observational references to climate model scales

Improvement in the decadal prediction skill of the North Atlantic extratropical winter circulation through increased model resolution

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