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Antarctic sea ice has changed significantly over the past four decades; yet limited understanding of fundamental processes, including its seasonal cycle, hinders our ability to interpret these changes. Here, we examine the processes determining the moment when sea ice locally disappears each spring, defined as the retreat date, using satellite observations over 1994–2020. We find that climatological retreat date is driven by sea ice melt in most of the seasonal ice zone and strongly constrained by the seasonal maximum ice thickness. Ice removal due to drifting ice export predominantly drives retreat only in coastal polynyas. At interannual timescales, retreat date anomalies are also preconditioned by prior maximum ice thickness, which affects melt‐driven spring ice loss through the ice‐albedo feedback, though this effect appears limited to specific regions. Winds emerge as a primary driver of interannual variability in the retreat date, influencing both drift‐ and melt‐related spring ice removal processes. Plain Language Summary Antarctic sea ice has undergone major changes over the past four decades, but our ability to interpret these changes is limited by gaps in our understanding of how sea ice behaves, notably throughout the seasons. Here, we use observations to investigate what determines the timing of local summer sea ice disappearance—a critical marker of the sea ice seasonal cycle—known as the retreat date. We show that the mean seasonal retreat date occurs mainly due to sea ice melting, with little direct influence from drifting ice export, and is strongly controlled by the maximum sea ice thickness at the start of spring. On a year‐to‐year basis, variations in the retreat date seem also influenced by the previous maximum sea ice thickness, but only in limited regions, while spring winds appear to affect the retreat date over a larger area. Key Points Mean seasonal sea ice retreat date is driven by basal melting rather than drift, and is constrained by the seasonal ice thickness maximum The link between maximum ice thickness and following retreat date also holds at interannual time scales in 25% of the seasonal ice zone Winds, through complex dynamic and thermodynamic effects on sea ice, are major contributors to interannual variability in retreat date

This study introduces CNRM‐ESM2‐1, the Earth system (ES) model of second generation developed by CNRM‐CERFACS for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). CNRM‐ESM2‐1 offers a higher model complexity than the Atmosphere‐Ocean General Circulation Model CNRM‐CM6‐1 by adding interactive ES components such as carbon cycle, aerosols, and atmospheric chemistry. As both models share the same code, physical parameterizations, and grid resolution, they offer a fully traceable framework to investigate how far the represented ES processes impact the model performance over present‐day, response to external forcing and future climate projections. Using a large variety of CMIP6 experiments, we show that represented ES processes impact more prominently the model response to external forcing than the model performance over present‐day. Both models display comparable performance at replicating modern observations although the mean climate of CNRM‐ESM2‐1 is slightly warmer than that of CNRM‐CM6‐1. This difference arises from land cover‐aerosol interactions where the use of different soil vegetation distributions between both models impacts the rate of dust emissions. This interaction results in a smaller aerosol burden in CNRM‐ESM2‐1 than in CNRM‐CM6‐1, leading to a different surface radiative budget and climate. Greater differences are found when comparing the model response to external forcing and future climate projections. Represented ES processes damp future warming by up to 10% in CNRM‐ESM2‐1 with respect to CNRM‐CM6‐1. The representation of land vegetation and the CO2‐water‐stomatal feedback between both models explain about 60% of this difference. The remainder is driven by other ES feedbacks such as the natural aerosol feedback. Key Points This study introduces CNRM‐ESM2‐1 and describes its set‐up for CMIP6 Represented Earth system processes further impact the model response to external forcing than the model performance over present‐day Represented Earth system processes damp future warming by up to 10%

Antarctic sea ice is mostly seasonal. While changes in sea ice seasonality have been observed in recent decades, the lack of process understanding remains a key challenge to interpret these changes. To address this knowledge gap, we investigate the processes driving the ice season onset, known as sea ice advance, using remote sensing and in situ observations. Here, we find that seawater freezing predominantly drives advance in the inner seasonal ice zone. By contrast, in an outer band a few degrees wide, advance is due to the import of drifting ice into warmer waters. We show that advance dates are strongly related to the heat stored in the summer ocean mixed layer. This heat is controlled by the timing of sea ice retreat, explaining the tight link between retreat and advance dates. Such a thermodynamic linkage strongly constrains the climatology and interannual variations, albeit with less influence on the latter. Processes controlling the onset of the Antarctic sea ice season remain unclear. Here, analyses of observations show that ocean solar energy storage and sea ice drift are key drivers, providing insights to understand variations in sea ice season duration.

The abyssal ocean is primarily filled by cold, dense waters formed around Antarctica and collectively referred to as Antarctic Bottom Water (AABW). At steady state, AABW must be consumed in the ocean interior at the same rate it is produced, but how and where this consumption is achieved remains poorly understood. Here, estimates of abyssal water mass transformation by geothermal heating and parameterized internal wave–driven mixing are presented. This study uses maps of the energy input to internal waves by tidal and geostrophic motions interacting with topography combined with assumptions about the distribution of energy dissipation to evaluate dianeutral transports induced by breaking internal tides and lee waves. Geothermal transformation is assessed based on a map of geothermal heat fluxes. Under the hypotheses underlying the constructed climatologies of buoyancy fluxes, the authors calculate that locally dissipating internal tides and geothermal heating contribute, respectively, about 8 and 5 Sverdrups (Sv; 1 Sv ≡ 10 6 m 3 s −1 ) of AABW consumption (upwelling), mostly north of 30°S. In contrast, parameterized lee wave–driven mixing causes significant transformation only in the Southern Ocean, where it forms about 3 Sv of AABW, decreasing the mean density but enhancing the northward flow of abyssal waters. The possible role of remotely dissipating internal tides in complementing AABW consumption is explored based on idealized distributions of mixing energy. Depending mostly on the chosen vertical structure, such mixing could drive 1 to 28 Sv of additional AABW upwelling, highlighting the need to better constrain the spatial distribution of remote dissipation. Though they carry large uncertainties, these climatological transformation estimates shed light on the qualitative functioning and key unknowns of the diabatic overturning.

The current feedback to the atmosphere (CFB) contributes to the oceanic circulation by damping eddies. In an ocean‐atmosphere coupled model, CFB can be correctly accounted for by using the wind relative to the oceanic current. However, its implementation in a forced oceanic model is less straightforward as CFB also enhances the 10‐m wind. Wind products based on observations have seen real currents that will not necessarily correspond to model currents, whereas meteorological reanalyses often neglect surface currents or use surface currents that, again, will differ from the surface currents of the forced oceanic simulation. In this study, we use a set of quasi‐global oceanic simulations, coupled or not with the atmosphere, to (i) quantify the error associated with the different existing strategies of forcing an oceanic model, (ii) test different parameterizations of the CFB, and (iii) propose the best strategy to account for CFB in forced oceanic simulation. We show that scatterometer wind or stress are not suitable to properly represent the CFB in forced oceanic simulation. We furthermore demonstrate that a parameterization of CFB based on a wind‐predicted coupling coefficient between the surface current and the stress allows us to reproduce the main characteristics of a coupled simulation. Such a parameterization can be used with any forcing set, including future coupled reanalyses, assuming that the associated oceanic surface currents are known. A further assessment of the thermal feedback of the surface wind in response to oceanic surface temperature gradients shows a weak forcing effect on oceanic currents. Key Points The Current FeedBack to the Atmosphere (CFB) can be parameterized in a forced oceanic model A parameterization of the CFB based on a predicted coupling coefficient is the best parameterization Scatterometers are not suitable to correctly represent the CFB in a forced oceanic model (unless coherent surface currents are known)

A 1/2° resolution global ocean general circulation model is used to investigate the processes controlling sea surface cooling in the wake of tropical cyclones (TCs). Wind forcing related to more than 3000 TCs occurring during the 1978–2007 period is blended with the CORE II interannual forcing, using an idealized TC wind pattern with observed magnitude and track. The amplitude and spatial characteristics of the TC‐induced cooling are consistent with satellite observations, with an average cooling of ∼1°C that typically extends over 5 radii of maximum wind. A Wind power index (WPi) is used to discriminate cooling processes under TCs with high‐energy transfer to the upper ocean (strong and/or slow cyclones) from the others (weak and/or fast cyclones). Surface heat fluxes contribute to ∼50 to 80% of the cooling for weak WPi as well as away from the cyclone track. Within 200 km of the track, mixing‐induced cooling increases linearly with WPi, explaining ∼30% of the cooling for weak WPis and up to ∼80% for large ones. Mixing‐induced cooling is strongly modulated by pre‐storm oceanic conditions. For a given WPi, vertical processes can induce up to 8 times more cooling for shallow mixed layer and steep temperature stratification than for a deep mixed layer. Vertical mixing is the main source of rightward bias of the cold wake for weak and moderate WPi, but along‐track advection becomes the main contributor to the asymmetry for the largest WPis. Key Points Cold wake dominated by mixing for strong TCs Mixing deeply modified by pre‐storm ocean stratification Advection explains CW asymmetry for strong TCs

Surface cooling induced by tropical cyclones (TCs) is about three times larger during premonsoon than during postmonsoon season in the Bay of Bengal. We investigate processes responsible for this seasonal contrast using an ocean general circulation model. The model is forced by TC winds prescribed from an analytic vortex using observed TC tracks and intensities during 1978–2007. The simulation accurately captures the seasonal cycle of salinity, temperature, and barrier layer in this region, with fresher waters, deeper upper‐ocean stratification, and thicker barrier layers during postmonsoon season. It also reproduces the three times larger TC‐induced cooling during premonsoon than during postmonsoon season. This difference is essentially related to seasonal changes in oceanic stratification rather than to differences in TC wind energy input. During the postmonsoon season, a deeper thermal stratification combined with a considerable upper‐ocean freshening strongly inhibits surface cooling induced by vertical mixing underneath TCs. On average, thermal stratification accounts for ∼60% of this cooling reduction during postmonsoon season, while haline stratification accounts for the remaining 40%. Their respective contributions however strongly vary within the Bay: haline stratification explains a large part of the TC‐induced cooling inhibition offshore of northern rim of the Bay (Bangladesh‐Myanmar‐east coast of India), where salinity seasonal changes are the strongest, while thermal stratification explains all the cooling inhibition in the southwestern Bay. This study hence advocates for an improved representation of upper‐ocean salinity and temperature effects in statistical and dynamical TCs forecasts that could lead to significant improvements of TC intensity prediction skill. Key Points TC‐induced cooling in Bay of Bengal is far weaker during post than pre‐monsoon Thermal stratification changes account for ~70% of this cooling inhibition Haline stratification explains most of cooling inhibition along Bay northern rim

The Indian Ocean Dipole (IOD) can affect the El Niño–Southern Oscillation (ENSO) state of the following year, in addition to the well-known preconditioning by equatorial Pacific Warm Water Volume (WWV), as suggested by a study based on observations over the recent satellite era (1981–2009). The present paper explores the interdecadal robustness of this result over the 1872–2008 period. To this end, we develop a robust IOD index, which well exploits sparse historical observations in the tropical Indian Ocean, and an efficient proxy of WWV interannual variations based on the temporal integral of Pacific zonal wind stress (of a historical atmospheric reanalysis). A linear regression hindcast model based on these two indices in boreal fall explains 50 % of ENSO peak variance 14 months later, with significant contributions from both the IOD and WWV over most of the historical period and a similar skill for El Niño and La Niña events. Our results further reveal that, when combined with WWV, the IOD index provides a larger ENSO hindcast skill improvement than the Indian Ocean basin-wide mode, the Indian Monsoon or ENSO itself. Based on these results, we propose a revised scheme of Indo-Pacific interactions. In this scheme, the IOD–ENSO interactions favour a biennial timescale and interact with the slower recharge-discharge cycle intrinsic to the Pacific Ocean.

Tropical cyclones (TCs) induce sea surface cooling that feeds back negatively on their intensity. Previous studies indicate that the cooling magnitude depends on oceanic conditions as well as TC characteristics, but this oceanic control has been poorly documented. We investigate the oceanic influence on TC‐induced cooling using a global ocean model experiment that realistically samples the ocean response to more than 3,000 TCs over the last 30 years. We derive a physically grounded oceanic parameter, the Cooling Inhibition index (CI), which measures the potential energy input required to cool the ocean surface through vertical mixing, and hence accounts for the pre‐storm upper‐ocean stratification resistance to TC‐induced cooling. The atmospheric control is described using the wind power index (WPi), a proxy of the kinetic energy transferred to the ocean by a TC, which accounts for both the effects of maximum winds and translation speed. The cooling amplitude increases almost linearly with WPi. For a given WPi, the cooling amplitude can however vary by an order of magnitude: a strong wind energy input can either result in a 0.5°C or 5°C cooling, depending on oceanic background state. Using an oceanic parameter such as CI in addition to wind energy input improves statistical hindcasts of the cold wake amplitude by ∼40%. Deriving an oceanic parameter based on the potential energy required to cool the ocean surface through vertical mixing is thus a promising way to better account for ocean characteristics in TCs studies. Key Points Upper ocean stratification largely controls the hurricane‐induced cooling

This paper explores the impact of intra-daily Sea Surface Temperature (SST) variability on the tropical large-scale climate variability and differentiates it from the response of the system to the forcing of the solar diurnal cycle. Our methodology is based on a set of numerical experiments based on a fully global coupled ocean–atmosphere general circulation in which we alter (1) the frequency at which the atmosphere sees the SST variations and (2) the amplitude of the SST diurnal cycle. Our results highlight the complexity of the scale interactions existing between the intra-daily and inter-annual variability of the tropical climate system. Neglecting the SST intra-daily variability results, in our CGCM, to a systematic decrease of 15% of El Niño—Southern Oscillation (ENSO) amplitude. Furthermore, ENSO frequency and skewness are also significantly modified and are in better agreement with observations when SST intra-daily variability is directly taken into account in the coupling interface of our CGCM. These significant modifications of the SST interannual variability are not associated with any remarkable changes in the mean state or the seasonal variability. They can therefore not be explained by a rectification of the mean state as usually advocated in recent studies focusing on the diurnal cycle and its impact. Furthermore, we demonstrate that SST high frequency coupling is systematically associated with a strengthening of the air-sea feedbacks involved in ENSO physics: SST/sea level pressure (or Bjerknes) feedback, zonal wind/heat content (or Wyrtki) feedback, but also negative surface heat flux feedbacks. In our model, nearly all these results (excepted for SST skewness) are independent of the amplitude of the SST diurnal cycle suggesting that the systematic deterioration of the air-sea coupling by a daily exchange of SST information is cascading toward the major mode of tropical variability, i.e. ENSO.