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The Tropical Ocean Global Atmosphere (TOGA) program was a 10-year international climate research effort carried out between 1985 and 1994 under the auspices of the World Climate Research Programme (WCRP). TOGA's goals were to determine the predictability of the coupled ocean-atmosphere system in the tropics on seasonal-to-interannual time scales, to understand the mechanisms responsible for that predictability, and to establish an observing system to support climate prediction. The US contribution to TOGA focused mainly on the El Niño/Southern Oscillation (ENSO) phenomenon, which is the most prominent climate signal on seasonal-to-interannual time scales. One of TOGA's great strengths was that it forged the three fields of observation, theory, and modeling into a coherent program. TOGA also included climate impact studies from the very beginning by collaborating with scientists outside the field of physical climate research. This article highlights some key successes of TOGA and assesses its legacy from a perspective of progress over the past 15 years. It also celebrates the fiftieth anniversary of the Intergovernmental Oceanographic Commission (IOC), established within the United Nations Educational, Scientific and Cultural Organization to promote international cooperation in marine research, services, and observations. IOC, together with the World Meteorological Organization and the International Council of Science, co-sponsored not only TOGA, but also antecedent and follow-on climate research programs under WCRP. The continuity of these research programs over the time span of decades is one of the reasons for their long-term successes.

The TOGA (Tropical Ocean and Global Atmosphere) Program was designed to study short-term climate variations. A 10-year international program, TOGA made El Nino a household word. This book chronicles the cooperative efforts of oceanographers and meteorologists, several U.S. government agencies, many other nations, and international scientific organizations to study El Nino and the Southern Oscillation (ENSO). It describes the progression from being unable to detect the development of large climate variations to being able to make and use rudimentary climate predictions, especially for some tropical countries. It examines the development of the TOGA Program, evaluates its accomplishments, describes U.S. participation in the program, and makes general recommendations for developing better understanding and predictions of climate variations on seasonal to interannual time scales.

The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative‐convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud‐resolving models (CRMs), large eddy simulations (LES), and global cloud‐resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self‐aggregation in large domains and agree that self‐aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self‐aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations. Plain Language Summary This study investigates tropical clouds and climate using results from more than 30 different numerical models set up in a simplified framework. The data set of model simulations is unique in that it includes a wide range of model types configured in a consistent manner. We address some of the biggest open questions in climate science, including how cloud properties change with warming and the role that the tendency of clouds to form clusters plays in determining the average climate and how climate changes. While there are large differences in how the different models simulate average temperature, humidity, and cloudiness, in a majority of models, the amount of high clouds decreases as climate warms. Nearly all models simulate a tendency for clouds to cluster together. There is agreement that when the clouds are clustered, the atmosphere is drier with fewer clouds overall. We do not find a conclusive result for how cloud clustering changes as the climate warms. Key Points Temperature, humidity, and clouds in radiative‐convective equilibrium vary substantially across models Models agree that self‐aggregation dries the atmosphere and reduces high cloudiness There is no consistency in how self‐aggregation depends on warming

Recent studies have pointed out an increased warming over the Indian Ocean warm pool (the central-eastern Indian Ocean characterized by sea surface temperatures greater than 28.0°C) during the past half-century, although the reasons behind this monotonous warming are still debated. The results here reveal a larger picture—namely, that the western tropical Indian Ocean has been warming for more than a century, at a rate faster than any other region of the tropical oceans, and turns out to be the largest contributor to the overall trend in the global mean sea surface temperature (SST). During 1901–2012, while the Indian Ocean warm pool went through an increase of 0.7°C, the western Indian Ocean experienced anomalous warming of 1.2°C in summer SSTs. The warming of the generally cool western Indian Ocean against the rest of the tropical warm pool region alters the zonal SST gradients, and has the potential to change the Asian monsoon circulation and rainfall, as well as alter the marine food webs in this biologically productive region. The current study using observations and global coupled ocean–atmosphere model simulations gives compelling evidence that, besides direct contribution from greenhouse warming, the long-term warming trend over the western Indian Ocean during summer is highly dependent on the asymmetry in the El Niño–Southern Oscillation (ENSO) teleconnection, and the positive SST skewness associated with ENSO during recent decades.

The El Niño–Southern Oscillation, which originates in the tropical Pacific, affects the rest of the world's tropics by perturbing global atmospheric circulation. Less appreciated than this influence is how the tropical Atlantic and Indian Oceans affect the Pacific. Cai et al. review what we know about these pantropical interactions, discuss possible ways of improving predictions of current climate variability, and consider how projecting future climate under different anthropogenic forcing scenarios may be improved. They argue that making progress in this field will require sustained global climate observations, climate model improvements, and theoretical advances. Science , this issue p. eaav4236 The El Niño–Southern Oscillation (ENSO), which originates in the Pacific, is the strongest and most well-known mode of tropical climate variability. Its reach is global, and it can force climate variations of the tropical Atlantic and Indian Oceans by perturbing the global atmospheric circulation. Less appreciated is how the tropical Atlantic and Indian Oceans affect the Pacific. Especially noteworthy is the multidecadal Atlantic warming that began in the late 1990s, because recent research suggests that it has influenced Indo-Pacific climate, the character of the ENSO cycle, and the hiatus in global surface warming. Discovery of these pantropical interactions provides a pathway forward for improving predictions of climate variability in the current climate and for refining projections of future climate under different anthropogenic forcing scenarios.

The Pacific Decadal Oscillation (PDO), the leading mode of Pacific decadal sea surface temperature variability, arises mainly from combinations of regional air-sea interaction within the North Pacific Ocean and remote forcing, such as from the tropical Pacific and the Atlantic. Because of such a combination of mechanisms, a question remains as to how much PDO variability originates from these regions. To better understand PDO variability, the equatorial Pacific and the Atlantic impacts on the PDO are examined using several 3-dimensional partial ocean data assimilation experiments conducted with two global climate models: the CESM1.0 and MIROC3.2m. In these partial assimilation experiments, the climate models are constrained by observed temperature and salinity anomalies, one solely in the Atlantic basin and the other solely in the equatorial Pacific basin, but are allowed to evolve freely in other regions. These experiments demonstrate that, in addition to the tropical Pacific’s role in driving PDO variability, the Atlantic can affect PDO variability by modulating the tropical Pacific climate through two proposed processes. One is the equatorial pathway, in which tropical Atlantic sea surface temperature (SST) variability causes an El Niño-like SST response in the equatorial Pacific through the reorganization of the global Walker circulation. The other is the north tropical pathway, where low-frequency SST variability associated with the Atlantic Multidecadal Oscillation induces a Matsuno-Gill type atmospheric response in the tropical Atlantic-Pacific sectors north of the equator. These results provide a quantitative assessment suggesting that 12–29% of PDO variance originates from the Atlantic Ocean and 40–44% from the tropical Pacific. The remaining 27–48% of the variance is inferred to arise from other processes such as regional ocean-atmosphere interactions in the North Pacific and possibly teleconnections from the Indian Ocean.

The physical processes governing a tropical cyclone's lifecycle are largely understood, but key processes occur at scales below those resolved by global climate models. Increased resolution may help simulate realistic tropical cyclone intensification. We examined fully coupled, global storm‐resolving models run at resolutions in the range 28–2.8 km in the atmosphere and 28–5 km in the ocean. Simulated tropical cyclone activity, peak intensity, intensification rate, and horizontal wind structure are all more realistic at a resolution of ∼5 km compared with coarser resolutions. Rapid intensification, which is absent at typical climate model resolutions, is also captured, and exhibits sensitivity to how, and if, deep convection is parameterized. Additionally, the observed decrease in inner‐core horizontal size with increasing intensification rate is captured at storm‐resolving resolution. These findings highlight the importance of global storm‐resolving models for quantifying risk and understanding the role of intense tropical cyclones in the climate system. Plain Language Summary Simulating strong tropical storms (i.e., major hurricanes, super typhoons) with climate models is challenging because important processes that act to intensify a storm occur over spatial scales that are too small for global models to capture. Typical models lack sufficient resolution in the atmosphere and ocean, often constrained by computational resources. Recently, in a few models, resolution has increased to a point where each grid cell represents an area of just a few square kilometres, a significant leap of one or two orders of magnitude. We analyzed tropical storms simulated by these state‐of‐the‐art, so‐called storm‐resolving models and found that peak tropical storm intensity and the rate at which storms intensify are both more realistic. These models also simulate the rapid intensification of tropical storms and capture the small eye diameters often seen in the most intense storms. Our work provides evidence that storm‐resolving resolution may help us better understand the role of tropical storms in the climate system and predict their behavior in a warming climate. Key Points Simulated tropical cyclone characteristics analyzed in two fully coupled global climate models at atmospheric resolutions of 28 to 2.8 km Tropical cyclone intensification rate is close to observations at resolutions of 5 km or finer, and rapid intensification is captured Storm‐resolving models also capture the observed relationship between high intensification rate and small inner‐core size

Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

Prior global climate model (GCM) experiments have shown that the Tibetan Plateau and related orography play a significant role in enhancing the Indian Monsoon, particularly during its onset, and the East Asian monsoon. However, these experiments have been largely performed with atmosphere-only, lower-resolution GCMs that neglect the influence of atmosphere–ocean coupling, and do not resolve tropical cyclones (TCs). Here we explore the influence of Asian orography on tropical circulations in a Geophysical Fluid Dynamics Laboratory GCM at two different atmosphere/land resolutions ( ∼ 50 and 200 km), and with or without atmosphere–ocean coupling. Atmosphere–ocean coupling is found to play a significant role in the precipitation response due to the Asian orography, enhancing the precipitation increase over the Western North Pacific (hereafter WNP), and drying the Arabian Sea. In these same regions, the higher resolution model, which resolves TCs up to category 3, suggests that Asian orography has a significant influence on TCs, increasing TC frequency in the WNP, and decreasing it in the Arabian Sea. However, in contrast to precipitation, this TC response does not appear to be strongly affected by the atmosphere–ocean coupling. Connections between the direct atmospheric circulation response to Asian orography, ocean circulation changes, and these various effects on precipitation and tropical cyclones are analyzed and discussed.

Growing evidence indicates that the atmospheric and oceanic circulation experiences a systematic poleward shift in a warming climate. However, the complexity of the climate system, including the coupling between the ocean and the atmosphere, natural climate variability and land-sea distribution, tends to obfuscate the causal mechanism underlying the circulation shift. Here, using an idealised coupled aqua-planet model, we explore the mechanism of the shifting circulation, by isolating the contributing factors from the direct CO 2 forcing, the indirect ocean surface warming, and the wind-stress feedback from the ocean dynamics. We find that, in contrast to the direct CO 2 forcing, ocean surface warming, in particular an enhanced subtropical ocean warming, plays an important role in driving the circulation shift. This enhanced subtropical ocean warming emerges from the background Ekman convergence of surface anomalous heat in the absence of the ocean dynamical change. It expands the tropical warm water zone, causes a poleward shift of the mid-latitude temperature gradient, hence forces a corresponding shift in the atmospheric circulation and the associated wind pattern. The shift in wind, in turn drives a shift in the ocean circulation. Our simulations, despite being idealised, capture the main features of the observed climate changes, for example, the enhanced subtropical ocean warming, poleward shift of the patterns of near-surface wind, sea level pressure, storm tracks, precipitation and large-scale ocean circulation, implying that increase in greenhouse gas concentrations not only raises the temperature, but can also systematically shift the climate zones poleward.