The EC-Earth3 Earth System Model for the Climate Model
Intercomparison Project 6

Doescher, Ralf; Acosta, Mario; Alessandri, Andrea; Anthoni, Peter; Arneth, Almut; Arsouze, Thomas; Bergman, Tommi; Bernardello, Raffaele; Bousetta, Souhail; Catalano, Franco; Caron, Louis-Philippe; Carver, G. D.; Castrillo, Miguel; Cvijanović, Ivana; Davini, Paolo; Dekker, Evelien; Doblas‐Reyes, Francisco J.; Docquier, David; Echevarría, Pablo; Fladrich, Uwe; Fuentes‐Franco, Ramón; Gröger, Matthias; Hardenberg, Jost von; Hieronymus, Jenny; Karami, Mehdi Pasha; Keskinen, Jukka-Pekka; Köenigk, Torben; Makkonen, Risto; Massonnet, François; Ménégoz, Martin; Miller, Paul A.; Moreno-Chamarro, Eduardo; Nieradzik, Lars; Noije, Twan van; Nolan, P.; O’Donnell, Declan; Ollinaho, Pirkka; Oord, Gijs van den; Ortega, Pablo; Prims, Oriol Tintó; Ramos, Arthur; Reerink, Thomas; Rousset, Clément; Ruprich‐Robert, Yohan; Sager, Philippe Le; Schmith, Torben; Schrödner, Roland; Serva, Federico; Sicardi, Valentina; Madsen, Marianne Sloth; Smith, Benjamin T.; Tian, Tian; Tourigny, Étienne; Uotila, Petteri; Vancoppenolle, Martin; Wang, Shiyu; Wårlind, David; Willén, Ulrika; Wyser, Klaus; Yang, Shuting; Yepes-Arbós, Xavier; Zhang, Qiong

doi:10.5194/gmd-2020-446

Cited by 209 publications

(72 citation statements)

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“…LIM2), LIM3 allows for five ice thickness categories to account for the non-linear dependence of sea ice processes, in particular growth and melt, on ice thickness. EC-Earth3 has been used to perform the CMIP6 historical (1850-2014) and future (2015-2100) scenario simulations with 25 ensemble members following the CMIP6 protocol (Eyring et al, 2016) by the EC-Earth consortium. We arbitrarily select one member (r5i1p1f1, hereafter referred to as FREE1) from the ensemble to obtain the model climatology for the ocean and sea ice used in the anomaly initialization.…”

Section: Introductionmentioning

confidence: 99%

Benefits of sea ice initialization for the interannual-to-decadal climate prediction skill in the Arctic in EC-Earth3

et al. 2021

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Abstract. A substantial part of Arctic climate predictability at interannual timescales stems from the knowledge of the initial sea ice conditions. Among all sea ice properties, its volume, which is a product of sea ice concentration (SIC) and thickness (SIT), is the most responsive parameter to climate change. However, the majority of climate prediction systems are only assimilating the observed SIC due to lack of long-term reliable global observation of SIT. In this study, the EC-Earth3 Climate Prediction System with anomaly initialization to ocean, SIC and SIT states is developed. In order to evaluate the regional benefits of specific initialized variables, three sets of retrospective ensemble prediction experiments are performed with different initialization strategies: ocean only; ocean plus SIC; and ocean plus SIC and SIT initialization. In the Atlantic Arctic, the Greenland–Iceland–Norway (GIN) and Barents seas are the two most skilful regions in SIC prediction for up to 5–6 lead years with ocean initialization; there are re-emerging skills for SIC in the Barents and Kara seas in lead years 7–9 coinciding with improved skills of sea surface temperature (SST), reflecting the impact of SIC initialization on ocean–atmosphere interactions for interannual-to-decadal timescales. For the year 2–9 average, the region with significant skill for SIT is confined to the central Arctic Ocean, covered by multi-year sea ice (CAO-MYI). Winter preconditioning with SIT initialization increases the skill for September SIC in the eastern Arctic (e.g. Kara, Laptev and East Siberian seas) and in turn improve the skill of air surface temperature locally and further expanded over land. SIT initialization outperforms the other initialization methods in improving SIT prediction in the Pacific Arctic (e.g. East Siberian and Beaufort seas) in the first few lead years. Our results suggest that as the climate warming continues and the central Arctic Ocean might become seasonal ice free in the future, the controlling mechanism for decadal predictability may thus shift from sea ice volume to ocean-driven processes.

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Section: Introductionmentioning

confidence: 99%

Benefits of sea ice initialization for the interannual-to-decadal climate prediction skill in the Arctic in EC-Earth3

et al. 2021

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“…A set of sensitivity experiments has been performed with the atmosphere-only configuration of the EC-Earth3 Earth System Model (Döscher et al, 2021). The atmospheric component of EC-Earth3 is based on the Integrated Forecast System (IFS) cy36r4 developed by the European Centre for Medium Range Weather Forecast (ECMWF).…”

Section: Methodsmentioning

confidence: 99%

Orographic resolution driving the improvements associated with horizontal resolution increase in the Northern Hemisphere winter mid-latitudes

Davini

Fabiano

Sandu

2021

Preprint

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Abstract. In recent years much attention has been devoted to the investigation of the impact of increasing the horizontal resolution of global climate models. In the present work, a set of atmosphere-only idealized sensitivity simulations with EC-Earth3 have been designed to disentangle the relative roles of increasing the resolution of the resolved orography and of the atmospheric grid. Focusing on the winter Northern Hemisphere, it is shown that if the grid is refined while keeping the resolved orography unchanged, model biases are reduced only in some specific occasions. Conversely, increasing the resolved (or mean) orography is found to clearly reduce several important systematic model errors, including synoptic transient eddies, the North Atlantic jet stream variability and atmospheric blocking frequency and duration. From an analysis of the radiation budget it is concluded that the large changes in radiative fluxes caused by the resolution increase – something commonly observed in climate models – have a relevant impact on the atmospheric circulation, partially offsetting the benefits obtained from the increase in orographic resolution. These findings point to the necessity of always tuning climate models to fully exploit the benefits of high horizontal resolution.

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“…Analysis in this paper is based on climate model simulations of the recent past performed with the EC-Earth3 global climate model (Wyser et al, 2020;Döscher et al, 2021). An ensemble of 50 members has been run for the period 1970-2014 as part of the Swedish Meteorological and Hydrological Institute large ensemble (SMHI-LENS; Wyser et al…”

Section: Climate Model Datamentioning

confidence: 99%

Tailoring circulation type classification outcomes

Hansen

Belušić

2021

Intl Journal of Climatology

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The EC-Earth3 Earth System Model for the Climate Model Intercomparison Project 6

Cited by 209 publications

References 0 publications

Benefits of sea ice initialization for the interannual-to-decadal climate prediction skill in the Arctic in EC-Earth3

Benefits of sea ice initialization for the interannual-to-decadal climate prediction skill in the Arctic in EC-Earth3

Orographic resolution driving the improvements associated with horizontal resolution increase in the Northern Hemisphere winter mid-latitudes

Tailoring circulation type classification outcomes

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