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The Indian Ocean Dipole is a key mode of interannual climate variability influencing much of Asia and Australia. A Review suggests that in response to greenhouse warming, mean conditions of the Indian Ocean will shift toward a positive dipole state, but with no overall shift in the frequency of positive and negative events as defined relative to the mean climate state. Natural modes of variability centred in the tropics, such as the El Niño/Southern Oscillation and the Indian Ocean Dipole, are a significant source of interannual climate variability across the globe. Future climate warming could alter these modes of variability. For example, with the warming projected for the end of the twenty-first century, the mean climate of the tropical Indian Ocean is expected to change considerably. These changes have the potential to affect the Indian Ocean Dipole, currently characterized by an alternation of anomalous cooling in the eastern tropical Indian Ocean and warming in the west in a positive dipole event, and the reverse pattern for negative events. The amplitude of positive events is generally greater than that of negative events. Mean climate warming in austral spring is expected to lead to stronger easterly winds just south of the Equator, faster warming of sea surface temperatures in the western Indian Ocean compared with the eastern basin, and a shoaling equatorial thermocline. The mean climate conditions that result from these changes more closely resemble a positive dipole state. However, defined relative to the mean state at any given time, the overall frequency of events is not projected to change — but we expect a reduction in the difference in amplitude between positive and negative dipole events.

Analysis of modern and historical observations demonstrates that the temperature of the intermediate-depth (150–900 m) Atlantic water (AW) of the Arctic Ocean has increased in recent decades. The AW warming has been uneven in time; a local ∼1°C maximum was observed in the mid-1990s, followed by an intervening minimum and an additional warming that culminated in 2007 with temperatures higher than in the 1990s by 0.24°C. Relative to climatology from all data prior to 1999, the most extreme 2007 temperature anomalies of up to 1°C and higher were observed in the Eurasian and Makarov Basins. The AW warming was associated with a substantial (up to 75–90 m) shoaling of the upper AW boundary in the central Arctic Ocean and weakening of the Eurasian Basin upper-ocean stratification. Taken together, these observations suggest that the changes in the Eurasian Basin facilitated greater upward transfer of AW heat to the ocean surface layer. Available limited observations and results from a 1D ocean column model support this surmised upward spread of AW heat through the Eurasian Basin halocline. Experiments with a 3D coupled ice–ocean model in turn suggest a loss of 28–35 cm of ice thickness after ∼50 yr in response to the 0.5 W m−2 increase in AW ocean heat flux suggested by the 1D model. This amount of thinning is comparable to the 29 cm of ice thickness loss due to local atmospheric thermodynamic forcing estimated from observations of fast-ice thickness decline. The implication is that AW warming helped precondition the polar ice cap for the extreme ice loss observed in recent years.

Large impacts provide a mechanism for resurfacing planets through mixing near-surface rocks with deeper material. Central peaks are formed from the dynamic uplift of rocks during crater formation. As crater size increases, central peaks transition to peak rings. Without samples, debate surrounds the mechanics of peak-ring formation and their depth of origin. Chicxulub is the only known impact structure on Earth with an unequivocal peak ring, but it is buried and only accessible through drilling. Expedition 364 sampled the Chicxulub peak ring, which we found was formed from uplifted, fractured, shocked, felsic basement rocks. The peak-ring rocks are cross-cut by dikes and shear zones and have an unusually low density and seismic velocity. Large impacts therefore generate vertical fluxes and increase porosity in planetary crust.

Using a fully coupled global ocean–atmosphere general circulation model assimilating only sea surface temperature, the authors found for the first time that several El Niño–Southern Oscillation (ENSO) events over the past two decades can be predicted at lead times of up to 2 yr. The El Niño condition in the 1997/98 winter can be predicted to some extent up to about a 1½-yr lead but with a weak intensity and large phase delay in the prediction of the onset of this exceptionally strong event. This is attributed to the influence of active and intensive stochastic westerly wind bursts during late 1996 to mid-1997, which are generally unpredictable at seasonal time scales. The cold signals in the 1984/85 and 1999/2000 winters during the peak phases of the past two long-lasting La Niña events are predicted well up to a 2-yr lead. Amazingly, the mild El Niño–like event of 2002/03 is also predicted well up to a 2-yr lead, suggesting a link between the prolonged El Niño and the tropical Pacific decadal variability. Seasonal climate anomalies over vast parts of the globe during specific ENSO years are also realistically predicted up to a 2-yr lead for the first time.

The SST-precipitation relationship in the intraseasonal variability (ISV) over the Asian monsoon region is examined using recent high quality satellite data and simulations from a state of the art coupled model, the climate forecast system version 2 (CFSv2). CFSv2 demonstrates high skill in reproducing the spatial distribution of the observed climatological mean summer monsoon precipitation along with its interannual variability, a task which has been a conundrum for many recent climate coupled models. The model also exhibits reasonable skill in simulating coherent northward propagating monsoon intraseasonal anomalies including SST and precipitation, which are generally consistent with observed ISV characteristics. Results from the observations and the model establish the existence of spatial variability in the atmospheric convective response to SST anomalies, over the Asian monsoon domain on intraseasonal timescales. The response is fast over the Arabian Sea, where precipitation lags SST by ~5 days; whereas it is slow over the Bay of Bengal and South China Sea, with a lag of ~12 days. The intraseasonal SST anomalies result in a similar atmospheric response across the basins, which consists of a destabilization of the bottom of the atmospheric column, as observed from the equivalent potential temperature anomalies near the surface. However, the presence of a relatively strong surface convergence over the Arabian Sea, due to the presence of a strong zonal gradient in SST, which accelerates the upward motion of the moist air, results in a relatively faster response in terms of the local precipitation anomalies over the Arabian Sea than over the Bay of Bengal and South China Sea. With respect to the observations, the ocean–atmosphere coupling is well simulated in the model, though with an overestimation of the intraseasonal SST anomalies, leading to an exaggerated SST-precipitation relationship. A detailed examination points to a systematic bias in the thickness of the mixed layer of the ocean model, which needs to be rectified. A too shallow (deep) mixed layer enhances (suppress) the amplitude of the intraseasonal SST anomalies, thereby amplifying (lessening) the ISV and the active-break phases of the monsoon in the model.

The Indian summer monsoon rainfall has complex, regionally heterogeneous, interannual variations with huge socioeconomic impacts, but the underlying mechanisms remain uncertain. The upwelling along the Somalia and Oman coasts starts in late spring, peaks during the summer monsoon, and strongly cools the sea surface temperature (SST) in the western Arabian Sea. They restrict the westward extent of the Indian Ocean warm pool, which is the main moisture source for the monsoon rainfall. Thus, variations of the Somalia–Oman upwelling can have significant impacts on the moisture transport toward India. Here the authors use both observations and an advanced coupled atmosphere–ocean general circulation model to show that a decrease in upwelling strengthens monsoon rainfall along the west coast of India by increasing the SST along the Somalia–Oman coasts, and thus local evaporation and water vapor transport toward the Indian Western Ghats (mountains). Further observational analysis reveals that such decreases in upwelling are caused by anomalously weak southwesterly winds in late spring over the Arabian Sea that are due to warm SST/increased precipitation anomalies over the Seychelles–Chagos thermocline ridge of the southwestern Indian Ocean (and vice versa for years with strong upwelling/weak west Indian summer monsoon rainfall). The latter SST/precipitation anomalies are often related to El Niño conditions and the strength of the Indonesian–Australian monsoon during the previous winter. This sheds new light on the ability to forecast the poorly predicted Indian monsoon rainfall on a regional scale, helped by a proper ocean observing/forecasting system in the western tropical Indian Ocean.

Past sea-level records provide invaluable information about the response of ice sheets to climate forcing. Some such records suggest that the last deglaciation was punctuated by a dramatic period of sea-level rise, of about 20 metres, in less than 500 years. Controversy about the amplitude and timing of this meltwater pulse (MWP-1A) has, however, led to uncertainty about the source of the melt water and its temporal and causal relationships with the abrupt climate changes of the deglaciation. Here we show that MWP-1A started no earlier than 14,650 years ago and ended before 14,310 years ago, making it coeval with the Bølling warming. Our results, based on corals drilled offshore from Tahiti during Integrated Ocean Drilling Project Expedition 310, reveal that the increase in sea level at Tahiti was between 12 and 22 metres, with a most probable value between 14 and 18 metres, establishing a significant meltwater contribution from the Southern Hemisphere. This implies that the rate of eustatic sea-level rise exceeded 40 millimetres per year during MWP-1A. An international drilling programme that explored offshore from the Tahiti reef establishes that an episode of rapid sea-level rise, meltwater pulse 1A, occurred between 14,650 and 14,310 years ago, and that the rise in sea level was probably between 14 and 18 metres. Antarctic ice-sheet collapse and sea-level changes A rapid sea-level rise occurred towards the end of the last ice age, during an event known as meltwater pulse 1A. The precise magnitude and timing of the event have remained obscure, rendering the climate forcings and consequent ice-sheet responses unclear. Pierre Deschamps and colleagues now report the results of a major coral-drilling programme in Tahiti, and establish that meltwater pulse 1A took place between 14,650 and 14,310 years ago, coincident with a warming spike. Sea levels rose by between 14 and 18 metres. Such a large rise suggests that ice-sheet collapse in Antarctica may have contributed to these changes, previously a point of much contention.

The variability in the East African short rains is investigated using 41-yr data from the observation and 200-yr data from a coupled general circulation model known as the Scale Interaction Experiment-Frontier Research Center for Global Change, version 1 (SINTEX-F1). The model-simulated data provide a scope to understand the climate variability in the region with a better statistical confidence. Most of the variability in the model short rains is linked to the basinwide large-scale coupled mode, that is, the Indian Ocean dipole (IOD) in the tropical Indian Ocean. The analysis of observed data and model results reveals that the influence of the IOD on short rains is overwhelming as compared to that of the El Niño–Southern Oscillation (ENSO); the correlation between ENSO and short rains is insignificant when the IOD influence is excluded. The IOD–short rains relationship does not change significantly in a model experiment in which the ENSO influence is removed by decoupling the ocean and atmosphere in the tropical Pacific. The partial correlation analysis of the model data demonstrates that a secondary influence comes from a regional mode located near the African coast. Inconsistent with the observational findings, the model results show a steady evolution of IOD prior to extreme events of short rains. Dynamically consistent evolution of correlations is found in anomalies of the surface winds, currents, sea surface height, and sea surface temperature. Anomalous changes of the Walker circulation provide a necessary driving mechanism for anomalous moisture transport and convection over the coastal East Africa. The model results nicely augment the observational findings and provide us with a physical basis to consider IOD as a predictor for variations of the short rains. This is demonstrated in detail using the statistical analysis method. The prediction skill of the dipole mode SST index in July and August is 92% for the observation, which scales slightly higher for the model index (96%) in August. As observed in data, the model results show decadal weakening in the relationship between IOD and short rains owing to weakening in the IOD activity.

In this study, the impact of the ocean–atmosphere coupling on the atmospheric mean state over the Indian Ocean and the Indian Summer Monsoon (ISM) is examined in the framework of the SINTEX-F2 coupled model through forced and coupled control simulations and several sensitivity coupled experiments. During boreal winter and spring, most of the Indian Ocean biases are common in forced and coupled simulations, suggesting that the errors originate from the atmospheric model, especially a dry islands bias in the Maritime Continent. During boreal summer, the air-sea coupling decreases the ISM rainfall over South India and the monsoon strength to realistic amplitude, but at the expense of important degradations of the rainfall and Sea Surface Temperature (SST) mean states in the Indian Ocean. Strong SST biases of opposite sign are observed over the western (WIO) and eastern (EIO) tropical Indian Ocean. Rainfall amounts over the ocean (land) are systematically higher (lower) in the northern hemisphere and the south equatorial Indian Ocean rainfall band is missing in the control coupled simulation. During boreal fall, positive dipole-like errors emerge in the mean state of the coupled model, with warm and wet (cold and dry) biases in the WIO (EIO), suggesting again a significant impact of the SST errors. The exact contributions and the distinct roles of these SST errors in the seasonal mean atmospheric state of the coupled model have been further assessed with two sensitivity coupled experiments, in which the SST biases are replaced by observed climatology either in the WIO (warm bias) or EIO (cold bias). The correction of the WIO warm bias leads to a global decrease of rainfall in the monsoon region, which confirms that the WIO is an important source of moisture for the ISM. On the other hand, the correction of the EIO cold bias leads to a global improvement of precipitation and circulation mean state during summer and fall. Nevertheless, all these improvements due to SST corrections seem drastically limited by the atmosphere intrinsic biases, including prominently the unimodal oceanic position of the ITCZ (Inter Tropical Convergence Zone) during summer and the enhanced westward wind stress along the equator during fall.

The Indian Ocean Dipole (IOD) has profound socioeconomic impacts on not only the countries surrounding the Indian Ocean but also various parts of the world. A forecast system is developed based on a relatively high-resolution coupled ocean–atmosphere GCM with only sea surface temperature (SST) information assimilated. Retrospective ensemble forecasts of the IOD index for the past two decades show skillful scores with up to a 3–4-month lead and a winter prediction barrier associated with its intrinsic strong seasonal phase locking. Prediction skills of the SST anomalies in both the eastern and western Indian Ocean are higher than those of the IOD index; this is because of the influences of ENSO, which is highly predictable. The model predicts the extreme positive IOD event in 1994 at a 2–3-season lead. The strong 1997 cold signal in the eastern pole, however, is not well predicted owing to errors in model initial subsurface conditions. The real-time forecast system with more ensembles successfully predicted the weak negative IOD event in the 2005 boreal fall and La Niña condition in the 2005/06 winter. Recent experimental real-time forecasts showed that a positive IOD event would appear in the 2006 summer and fall accompanied by a possible weak El Niño condition in the equatorial Pacific.