The time-dependent response of sea surface temperature (SST) to global warming and the associated atmospheric changes are investigated based on a 1% yr 21 CO 2 increase to the quadrupling experiment of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1. The SST response consists of a fast component, for which the ocean mixed layer is in quasi equilibrium with the radiative forcing, and a slow component owing to the gradual warming of the deeper ocean in and beneath the thermocline. A diagnostic method is proposed to isolate spatial patterns of the fast and slow responses. The deep ocean warming retards the surface warming in the fast response but turns into a forcing for the slow response. As a result, the fast and slow responses are nearly opposite to each other in spatial pattern, especially over the subpolar North Atlantic/Southern Ocean regions of the deep-water/bottom-water formation, and in the interhemispheric SST gradient between the southern and northern subtropics. Wind-evaporation-SST feedback is an additional mechanism for the SST pattern formation in the tropics. Analyses of phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel ensemble of global warming simulations confirm the validity of the diagnostic method that separates the fast and slow responses. Tropical annual rainfall change follows the SST warming pattern in both the fast and slow responses in CMIP5, increasing where the SST increase exceeds the tropical mean warming.

Uncertainty in tropical rainfall projections under increasing radiative forcing is studied by using 26 models from phase 5 of the Coupled Model Intercomparison Project. Intermodel spread in projected rainfall change generally increases with interactive sea surface temperature (SST) warming in coupled models compared to atmospheric models with a common pattern of prescribed SST increase. Moisture budget analyses reveal that much of the model uncertainty in tropical rainfall projections originates from intermodel discrepancies in the dynamical contribution due to atmospheric circulation change. Intermodel singular value decomposition (SVD) analyses further show a tight coupling between the intermodel variations in SST warming pattern and circulation change in the tropics. In the zonal mean, the first SVD mode features an anomalous interhemispheric Hadley circulation, while the second mode displays an SST peak near the equator. The asymmetric mode is accompanied by a coupled pattern of wind–evaporation–SST feedback in the tropics and is further tied to interhemispheric asymmetric change in extratropical shortwave radiative flux at the top of the atmosphere. Intermodel variability in the tropical circulation change exerts a strong control on the spread in tropical cloud cover change and cloud radiative effects among models. The results indicate that understanding the coupling between the anthropogenic changes in SST pattern and atmospheric circulation holds the key to reducing uncertainties in projections of future changes in tropical rainfall and clouds.

We studied the motility of filamentous mat-forming cyanobacteria consisting primarily of Oscillatoria-like cells growing under low-light, low-oxygen, and high-sulfur conditions in Lake Huron’s submerged sinkholes using in situ observations, in vitro measurements and time-lapse microscopy. Gliding movement of the cyanobacterial trichomes (100–10,000 μm long filaments, composed of cells ∼10 μm wide and ∼3 μm tall) revealed individual as well as group-coordinated motility. When placed in a petri dish and dispersed in ground water from the sinkhole, filaments re-aggregated into defined colonies within minutes, then dispersed again. Speed of individual filaments increased with temperature from ∼50 μm min-1 or ∼15 body lengths min-1 at 10°C to ∼215 μm min-1 or ∼70 body lengths min-1 at 35°C – rates that are rapid relative to non-flagellated/ciliated microbes. Filaments exhibited precise and coordinated positive phototaxis toward pinpoints of light and congregated under the light of foil cutouts. Such light-responsive clusters showed an increase in photosynthetic yield – suggesting phototactic motility aids in light acquisition as well as photosynthesis. Once light source was removed, filaments slowly spread out evenly and re-aggregated, demonstrating coordinated movement through inter-filament communication regardless of light. Pebbles and pieces of broken shells placed upon intact mat were quickly covered by vertically motile filaments within hours and became fully buried in the anoxic sediments over 3–4 diurnal cycles – likely facilitating the preservation of falling debris. Coordinated horizontal and vertical filament motility optimize mat cohesion and dynamics, photosynthetic efficiency and sedimentary carbon burial in modern-day sinkhole habitats that resemble the shallow seas in Earth’s early history. Analogous cyanobacterial motility may have played a key role in the oxygenation of the planet by optimizing photosynthesis while favoring carbon burial.

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The 2015 Paris Agreement proposed targets to limit global-mean surface temperature (GMST) rise well below 2°C relative to preindustrial level by 2100, requiring a cease in the radiative forcing (RF) increase in the near future. In response to changing RF, the deep ocean responds slowly (ocean slow response), in contrast to the fast ocean mixed layer adjustment. The role of the ocean slow response under low warming targets is investigated using representative concentration pathway (RCP) 2.6 simulations from phase 5 of the Coupled Model Intercomparison Project. In RCP2.6, the deep ocean continues to warm while RF decreases after reaching a peak. The deep ocean warming helps to shape the trajectories of GMST and fuels persistent thermosteric sea level rise. A diagnostic method is used to decompose further changes after the RF peak into a slow warming component under constant peak RF and a cooling component due to the decreasing RF. Specifically, the slow warming component amounts to 0.2°C (0.6°C) by 2100 (2300), raising the hurdle for achieving the low warming targets. When RF declines, the deep ocean warming takes place in all basins but is the most pronounced in the Southern Ocean and Atlantic Ocean where surface heat uptake is the largest. The climatology and change of meridional overturning circulation are both important for the deep ocean warming. To keep the GMST rise at a low level, substantial decrease in RF is required to offset the warming effect from the ocean slow response.

Previous studies reveal that the last generation of coupled general circulation models (CGCMs) commonly suffer from the so-called Indian Ocean dipole (IOD)-like biases, lowering the models’ ability in climate prediction and projection. The present study shows that such IOD-like biases reduce insignificantly or even worsen in CGCMs between Phase 5 to 6 of the Coupled Model Intercomparison Project (CMIP). The origins of the IOD-like biases in CGCMs are further investigated by comparing model outputs from CMIP and Atmospheric Model Intercomparison Project (AMIP). The CGCMs’ errors are divided into the biases from the AMIP simulation (AMIP biases) and ocean-atmosphere coupling (coupling biases). For the multi-model ensemble-mean, the AMIP (coupling) biases account for about two (one) thirds of the IOD-like CMIP biases. In AMIP simulations, the South Asian summer monsoon (SASM) is overly strong that could advect overly large easterly momentum from the south IO to the equator. The resultant equatorial easterly wind bias would initiate the convection-circulation feedback and develop large IOD-like AMIP biases. In contrast, the coupling biases weaken the SASM and hence generate warm SST error over the western IO during boreal summer. Such SST error persists to boreal autumn and triggers the Bjerknes feedback, developing the IOD-like coupling biases. Furthermore, the inter-model spread in the IOD-like CMIP biases is largely explained by the inter-model differences in the coupling biases rather than the AMIP biases. The results imply that substantial efforts should be respectively made on reducing the atmospheric models’ intrinsic monsoon biases as well as advancing the simulations of ocean-atmosphere coupling processes.

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