Impact of model resolution on Arctic sea ice and North Atlantic Ocean heat transport

Docquier, David; Grist, Jeremy P.; Roberts, Malcolm; Roberts, Christopher D.; Semmler, Tido; Ponsoni, Leandro; Massonnet, François; Sidorenko, Dmitry; Sein, Dmitry V.; Iovino, Doroteaciro; Bellucci, Alessio; Fichefet, Thierry

doi:10.1007/s00382-019-04840-y

Cited by 66 publications

(102 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the ensemble of models examined, those with a higher resolution have a more saline and dense west SPG, a stronger AMOC and a greater AMOC weakening. Other studies have shown higher resolution models having a stronger AMOC (Roberts et al 2016(Roberts et al , 2019aSein et al 2018;Menary et al 2018;Docquier et al 2019;Hirschi et al 2020), however most of these studies (and all of the models in this study) have used the same ocean submodel (NEMO). Some other modelling studies have come to the opposite conclusion (Yokohata et al 2007;Delworth et al 2012;Winton et al 2014).…”

Section: Discussionmentioning

confidence: 99%

“…The models configured for HighResMIP and used here are as follows: ECMWF-IFS (Roberts et al 2018); CNRM-CM6-1 (Voldoire et al 2019); CMCC-CM2-(V)HR4 (Cherchi et al 2019); HadGEM3-GC3.1 (Roberts et al 2019a); EC-Earth3P (Haarsma et al 2020). The model parameter settings are discussed in Docquier et al (2019) and Roberts et al (2019b). Note that all these coupled models use the NEMO ocean model, though with a range of configurations.…”

Section: Primavera Ensemblementioning

confidence: 99%

“…One factor thought to affect the AMOC strength is the horizontal resolution in the ocean. Many studies have found a stronger AMOC in higher resolution models (Roberts et al 2016(Roberts et al , 2019aSein et al 2018;Menary et al 2018;Docquier et al 2019;Hirschi et al 2020), though other studies have found a weaker AMOC in higher resolution models (Yokohata et al 2007;Delworth et al 2012;Winton et al 2014). Increasing resolution from non-eddying to eddy-permitting (or even eddy-resolving) has been shown to improve biases in the North Atlantic (Small et al 2014;Menary et al 2018;Roberts et al 2018Roberts et al , 2019aCaldwell et al 2019).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Impact of ocean resolution and mean state on the rate of AMOC weakening

et al. 2020

View full text Add to dashboard Cite

We examine the weakening of the Atlantic Meridional Overturning Circulation (AMOC) in response to increasing CO 2 at different horizontal resolutions in a state-of-the-art climate model and in a small ensemble of models with differing resolutions. There is a strong influence of the ocean mean state on the AMOC weakening: models with a more saline western subpolar gyre have a greater formation of deep water there. This makes the AMOC more susceptible to weakening from an increase in CO 2 since weakening ocean heat transports weaken the contrast between ocean and atmospheric temperatures and hence weaken the buoyancy loss. In models with a greater proportion of deep water formation further north (in the Greenland-Iceland-Norwegian basin), deep-water formation can be maintained by shifting further north to where there is a greater ocean-atmosphere temperature contrast. We show that ocean horizontal resolution can have an impact on the mean state, and hence AMOC weakening. In the models examined, those with higher resolutions tend to have a more westerly location of the North Atlantic Current and stronger subpolar gyre. This likely leads to a greater impact of the warm, saline subtropical Atlantic waters on the western subpolar gyre resulting in greater dense water formation there. Although there is some improvement of the higher resolution models over the lower resolution models in terms of the mean state, both still have biases and it is not clear which biases are the most important for influencing the AMOC strength and response to increasing CO 2 .

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Primavera Ensemblementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Impact of ocean resolution and mean state on the rate of AMOC weakening

et al. 2020

View full text Add to dashboard Cite

show abstract

“…OHT provided a very poor predictive skill. Docquier et al (2019) recently showed (their Fig. 12) a relatively good correlation between OHT and the SIV.…”

Section: Discussionmentioning

confidence: 88%

“…Overall, the 2 configurations from the same model keep the parameters identical, except for the resolution-dependent parameterizations (Docquier et al, 2019). In terms of ocean-sea ice grid, both AWI versions (data source: Semmler et al (2017b, a)) use a mesh grid with varying resolution.…”

mentioning

confidence: 99%

Statistical predictability of the Arctic sea ice volume anomaly: identifying predictors and optimal sampling locations

Ponsoni¹,

Massonnet²,

Docquier³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. This work evaluates the statistical predictability of the Arctic sea ice volume (SIV) anomaly – here defined as the detrended and deseasonalized SIV – on the interannual time scale. To do so, we made use of 6 datasets, from 3 different atmosphere-ocean general circulation models, with 2 different horizontal grid resolutions each. Based on these datasets, we have developed a statistical empirical model which in turn was used to test the performance of different predictor variables, as well as to identify optimal locations from where the SIV anomaly could be better reconstructed and/or predicted. We tested the hypothesis that an ideal sampling strategy characterized by only a few optimal sampling locations can provide in situ data for statistically reproducing and/or predicting the SIV interannual variability. The results showed that, apart from the SIV itself, the sea ice thickness is the best predictor variable, although total sea ice area, sea ice concentration, sea surface temperature, and sea ice drift can also contribute to improving the prediction skill. The prediction skill can be enhanced further by combining several predictors into the statistical model. Feeding the statistical model with predictor data from 4 well-placed locations is enough for reconstructing about 70 % of the SIV anomaly variance. An improved model horizontal resolution allows a better trained statistical model so that the reconstructed values approach better to the original SIV anomaly. On the other hand, if we look at the interannual variability, the predictors provided by numerical models with lower horizontal resolution perform better for reconstructing the original SIV variability. As per 6 well-placed locations, the statistical predictability does not substantially improve by adding new sites. As suggested by the results, the 4 first best locations are placed at the transition Chukchi Sea–Central Arctic–Beaufort Sea (158.0° W, 79.5° N), near the North Pole (40° E, 88.5° N), at the transition Central Arctic–Laptev Sea (107° E, 81.5° N), and offshore the Canadian Archipelago (109.0° W, 82.5° N), in this respective order. We believe that this study provides recommendations for the ongoing and upcoming observational initiatives, in terms of an Arctic optimal observing design, for studying and predicting not only the SIV values but also its interannual variability.

show abstract

The Arctic Subpolar gyre sTate Estimate (ASTE): Description and assessment of a data-constrained, dynamically consistent ocean-sea ice estimate for 2002-2017

Nguyen

Pillar

Ocaña

et al. 2020

Preprint

View full text Add to dashboard Cite

The Arctic region has experienced large changes in recent decades. These include near-surface air temperature warming at twice the global rate (Richter-Menge & Jeffries, 2011), rapid decline in multi-year sea ice (Kwok & Cunningham, 2015), enhanced solar radiation absorption in the Western Arctic upper ocean (Timmermans et al., 2018), increased river and glacial discharge (Bamber et al., 2012(Bamber et al., , 2018Proshutinsky et al., 2020), and increased influxes of freshwater from the Pacific (Woodgate, 2018) and heat from the Atlantic (Polyakov et al., 2011). Many of these changes have been suggested to trigger positive feedbacks.

show abstract

Impact of model resolution on Arctic sea ice and North Atlantic Ocean heat transport

Cited by 66 publications

References 66 publications

Impact of ocean resolution and mean state on the rate of AMOC weakening

Impact of ocean resolution and mean state on the rate of AMOC weakening

Statistical predictability of the Arctic sea ice volume anomaly: identifying predictors and optimal sampling locations

The Arctic Subpolar gyre sTate Estimate (ASTE): Description and assessment of a data-constrained, dynamically consistent ocean-sea ice estimate for 2002-2017

Contact Info

Product

Resources

About