Mitigation and adaptation strategies for climate change depend on accurate climate projections for the coming decades. While changes in radiative heat fluxes are known to contribute to surface warming, changes to ocean circulation can also impact the rate of surface warming. Previous studies suggest that projected changes to ocean circulation reduce the rate of global warming. However, these studies consider large greenhouse gas forcing scenarios, which induce a significant buoyancy‐driven decline of the Atlantic Meridional Overturning Circulation. Here, we use a climate model to quantify the previously unknown impact of changes to wind‐driven ocean circulation on global surface warming. Wind‐driven ocean circulation changes amplify the externally forced warming rate by 17% from 1979 to 2014. Accurately simulating changes to the atmospheric circulation is key to improving near‐term climate projections.

Since 2000, the Indian Ocean has warmed more rapidly than the Atlantic or Pacific Oceans. Air–sea fluxes alone cannot explain the rapid Indian Ocean warming, which has so far been linked to an increase in temperature transport into the basin through the Indonesian Throughflow (ITF). Here, we investigate the role that the heat transport out of the basin at 36°S plays in the warming. Adding the heat transport out of the basin to the ITF temperature transport into the basin, we calculate the decadal mean Indian Ocean heat budget over the 2010s. We find that heat convergence increased within the Indian Ocean over 2000–19. The heat convergence over the 2010s is of the same order as the warming rate, and thus the net air–sea fluxes are near zero. This is a significant change from previous analyses using transbasin hydrographic sections from 1987, 2002, and 2009, which all found divergences of heat. A 2-yr time series shows that seasonal aliasing is not responsible for the decadal change. The anomalous ocean heat convergence over the 2010s in comparison with previous estimates is due to changes in ocean currents at both the southern boundary (33%) and the ITF (67%). We hypothesize that the changes at the southern boundary are linked to an observed broadening of the Agulhas Current, implying that temperature and velocity data at the western boundary are crucial to constrain heat budget changes.

For the first time, the temperature transport of the Agulhas Current is quantified in a time series. Over a 25-month mooring deployment at 34°S, seven tall moorings were instrumented to measure current velocity, temperature, and salinity. Current- and pressure-recording inverted echosounders were used to extend geostrophic velocity, temperature, and salinity records to 300 km offshore. In the mean, the current transports 3.8 PW of heat southward relative to 0°C: −76 Sv (1 Sv ≡ 10⁶ m³ s⁻¹) at a transport-weighted temperature of 12.3°C. A 0.9-PW standard deviation in temperature transport is due to variability in both volume transport and the temperature field. Meandering of the current core dominates variability in the temperature field by warming temperatures offshore and cooling temperatures near the coast. However, meandering has a limited impact on the temperature transport, which varies more closely with a deepening and broadening of the current associated with an inshore isotherm shoaling and an offshore isotherm deepening. Stronger southward temperature transports correspond to a deeper current transporting more volume, yet at a cooler transport-weighted temperature. Seasonality is not observed in the temperature transport time series, possibly because of the offsetting effects of cooler temperatures during times of seasonally stronger volume transports. Although volume transport and temperature transport are highly correlated, the large variability in transport-weighted temperature means that using volume transport alone to infer temperature transport results in an error that could be as large as 24% of the southern Indian Ocean heat transport.

The seasonal variability in volume transport of the South Indian Ocean subtropical gyre is characterized for the first time. Only three complete hydrographic crossings of the gyre have been conducted over a 22‐year period, with an upcoming repeat in 2019. Changes to geostrophic transport and thermocline properties imply a strengthening of the gyre from 1987 to 2002. However, some of this strengthening could result from aliasing of seasonal variability. We use data from Argo, satellite altimetry, and an Agulhas Current transport proxy at 34^∘S to quantify the seasonal variability of the upper 2,000‐m volume transport. A semiannual cycle is revealed, with peak‐to‐peak amplitude of 6.4 ± 3.1 Sv(1Sv = 10⁶ m³ s⁻¹) and dominated by annual anomalies in quadrature near the eastern and western boundaries. Seasonal aliasing does not account for the observed gyre strengthening.

The tropical Pacific warming pattern since the 1950s exhibits two warming centers in the western Pacific (WP) and eastern Pacific (EP), encompassing an equatorial central Pacific (CP) cooling and a hemispheric asymmetry in the subtropical EP. The underlying mechanisms of this warming pattern remain debated. Here, we conduct ocean heat decompositions of two coupled model large ensembles to unfold the role of wind-driven ocean circulation. When wind changes are suppressed, historical radiative forcing induces a subtropical northeastern Pacific warming, thus causing a hemispheric asymmetry that extends toward the tropical WP. The tropical EP warming is instead induced by the cross-equatorial winds associated with the hemispheric asymmetry, and its driving mechanism is southward warm Ekman advection due to the off-equatorial westerly wind anomalies around 5°N, not vertical thermocline adjustment. Climate models fail to capture the observed CP cooling, suggesting an urgent need to better simulate equatorial oceanic processes and thermal structures.

Indian Ocean meridional heat transport (MHT_IO) drives climate and ecosystem impacts, through changes to ocean temperature. Improved understanding of natural variability in tropical and subtropical MHT_IO is needed to contextualize observations and future projections. Previous studies suggest that El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) can drive variability in MHT_IO. However, it is unclear whether internally generated IOD can drive variability in MHT_IO, or if the apparent relationship between IOD and MHT_IO arises because both are modulated by ENSO. Here, we use a model experiment which dynamically removes ENSO to determine the role of internally forced IOD on MHT_IO. We find that IOD is not linked to anomalies in MHT_IO. Nevertheless, internal atmospheric variability drives significant MHT_IO variability. There is little evidence for decadal or multidecadal variability in MHT_IO, suggesting this may be a region where an anthropogenic trend rises above the level of internal variability sooner.