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This article retrospects the studies of the predictability of El Niño-Southern Oscillation (ENSO) events within the framework of error growth dynamics and reviews the results of previous studies. It mainly covers (a) the advances in methods for studying ENSO predictability, especially those of optimal methods associated with initial errors and model errors; and (b) the applications of these optimal methods in the studies of “spring predictability barrier” (SPB), optimal precursors for ENSO events (or the source of ENSO predictability) and target observations for ENSO predictions. In this context, some of major frontiers and challenges remaining in ENSO predictability are addressed.

Storms are characterized by high wind speeds; often large precipitation amounts in the form of rain, freezing rain, or snow; and thunder and lightning (for thunderstorms). Many different types exist, ranging from tropical cyclones and large storms of the midlatitudes to small polar lows, Medicanes, thunderstorms, or tornadoes. They can lead to extreme weather events like storm surges, flooding, high snow quantities, or bush fires. Storms often pose a threat to human lives and property, agriculture, forestry, wildlife, ships, and offshore and onshore industries. Thus, it is vital to gain knowledge about changes in storm frequency and intensity. Future storm predictions are important, and they depend to a great extent on the evaluation of changes in wind statistics of the past.

To obtain reliable statistics, long and homogeneous time series over at least some decades are needed. However, wind measurements are frequently influenced by changes in the synoptic station, its location or surroundings, instruments, and measurement practices. These factors deteriorate the homogeneity of wind records. Storm indexes derived from measurements of sea-level pressure are less prone to such changes, as pressure does not show very much spatial variability as wind speed does. Long-term historical pressure measurements exist that enable us to deduce changes in storminess for more than the last 140 years. But storm records are not just compiled from measurement data; they also may be inferred from climate model data.

The first numerical weather forecasts were performed in the 1950s. These served as a basis for the development of atmospheric circulation models, which were the first generation of climate models or general-circulation models. Soon afterward, model data was analyzed for storm events and cyclone-tracking algorithms were programmed. Climate models nowadays have reached high resolution and reliability and can be run not just for the past, but also for future emission scenarios which return possible future storm activity.

Discovered at the very end of the 20th century, the Indian Ocean Dipole (IOD) is a mode of natural climate variability that arises out of coupled ocean–atmosphere interaction in the Indian Ocean. It is associated with some of the largest changes of ocean–atmosphere state over the equatorial Indian Ocean on interannual time scales. IOD variability is prominent during the boreal summer and fall seasons, with its maximum intensity developing at the end of the boreal-fall season. Between the peaks of its negative and positive phases, IOD manifests a markedly zonal see-saw in anomalous sea surface temperature (SST) and rainfall—leading, in its positive phase, to a pronounced cooling of the eastern equatorial Indian Ocean, and a moderate warming of the western and central equatorial Indian Ocean; this is accompanied by deficit rainfall over the eastern Indian Ocean and surplus rainfall over the western Indian Ocean. Changes in midtropospheric heating accompanying the rainfall anomalies drive wind anomalies that anomalously lift the thermocline in the equatorial eastern Indian Ocean and anomalously deepen them in the central Indian Ocean. The thermocline anomalies further modulate coastal and open-ocean upwelling, thereby influencing biological productivity and fish catches across the Indian Ocean. The hydrometeorological anomalies that accompany IOD exacerbate forest fires in Indonesia and Australia and bring floods and infectious diseases to equatorial East Africa. The coupled ocean–atmosphere instability that is responsible for generating and sustaining IOD develops on a mean state that is strongly modulated by the seasonal cycle of the Austral-Asian monsoon; this setting gives the IOD its unique character and dynamics, including a strong phase-lock to the seasonal cycle. While IOD operates independently of the El Niño and Southern Oscillation (ENSO), the proximity between the Indian and Pacific Oceans, and the existence of oceanic and atmospheric pathways, facilitate mutual interactions between these tropical climate modes.

The El Niño Modoki/La Niña Modoki (ENSO Modoki) is a newly acknowledged face of ocean-atmosphere coupled variability in the tropical Pacific Ocean. The oceanic and atmospheric conditions associated with the El Niño Modoki are different from that of canonical El Niño, which is extensively studied for its dynamics and worldwide impacts. A typical El Niño event is marked by a warm anomaly of sea surface temperature (SST) in the equatorial eastern Pacific. Because of the associated changes in the surface winds and the weakening of coastal upwelling, the coasts of South America suffer from widespread fish mortality during the event. Quite opposite of this characteristic change in the ocean condition, cold SST anomalies prevail in the eastern equatorial Pacific during the El Niño Modoki events, but with the warm anomalies intensified in the central Pacific. The boreal winter condition of 2004 is a typical example of such an event, when a tripole pattern is noticed in the SST anomalies; warm central Pacific flanked by cold eastern and western regions. The SST anomalies are coupled to a double cell in anomalous Walker circulation with rising motion in the central parts and sinking motion on both sides of the basin. This is again a different feature compared to the well-known single-cell anomalous Walker circulation during El Niños. La Niña Modoki is the opposite phase of the El Niño Modoki, when a cold central Pacific is flanked by warm anomalies on both sides.

The Modoki events are seen to peak in both boreal summer and winter and hence are not seasonally phase-locked to a single seasonal cycle like El Niño/La Niña events. Because of this distinction in the seasonality, the teleconnection arising from these events will vary between the seasons as teleconnection path will vary depending on the prevailing seasonal mean conditions in the atmosphere. Moreover, the Modoki El Niño/La Niña impacts over regions such as the western coast of the United States, the Far East including Japan, Australia, and southern Africa, etc., are opposite to those of the canonical El Niño/La Niña. For example, the western coasts of the United States suffer from severe droughts during El Niño Modoki, whereas those regions are quite wet during El Niño. The influences of Modoki events are also seen in tropical cyclogenesis, stratosphere warming of the Southern Hemisphere, ocean primary productivity, river discharges, sea level variations, etc. A remarkable feature associated with Modoki events is the decadal flattening of the equatorial thermocline and weakening of zonal thermal gradient. The associated ocean-atmosphere conditions have caused frequent and persistent developments of Modoki events in recent decades.

The East African Rift System (EARS) transecting the high-elevation East African plateau is one of the most outstanding rift systems on earth. Rifting was caused by a huge uprising mantle plume under East Africa. Two distinct rift branches are distinguished: an older, volcanically very active Eastern Branch and a younger, much less volcanic Western Branch. The Eastern Branch is generally characterized by high elevation, whereas the Western Branch comprises a number of deep rift lakes (e.g., Lake Tanganyika, Lake Malaŵi). These differences reflect different plate strengths, the latter of which are largely governed by differences in how the mantle plume interacted with the East African lithosphere. Much of the topography forming the East African plateau has been caused by the uprising mantle plume. The onset of topographic uplift in the EARS is poorly dated but preceded graben development, the latter of which commenced at ~24 Ma in the Ethiopian Rift, at ~12 Ma in Kenya, and at ~10 Ma in the Western Branch. Increased uplift of the East African plateau since ~15–10 Ma might be connected to climate change in East Africa and human evolution. East Africa experienced cooling starting at 15.5–12.5 Ma that heralded profound faunal changes at 8–5 Ma, when the hominin lineage split from the chimpanzee lineage. The Pliocene is characterized by warm and wet climate between 5.3 and 3.3 Ma transitioning into a period of cooler and more arid conditions after ~3 Ma. The climate in the EARS is controlled by westerly monsoonal flow over equatorial West Africa and easterly monsoonal flow over the Indian Ocean. The uplifting East African plateau intercepted those winds and contributed to the increased aridification of East Africa.

The idea that under the same external forcing conditions, the climate system is able to have several (statistical) equilibrium states is both fascinating and worrying: fascinating because the interaction of different positive and negative feedbacks can then lead to different large-scale reorganizations of the transport of heat (and other properties) over the globe; worrying because perturbations on the current equilibrium state can then unexpectedly cause transitions in large-scale transport properties, with potential disastrous changes in regional weather conditions. In this article, the development of the idea to explain peculiar climate changes using multiple equilibrium states is presented.

Eastern Africa, classically presented as a major dry climate anomaly region in the otherwise wet equatorial belt, is a transition zone between the monsoon domains of West Africa and the Indian Ocean. Its complex terrain, unequaled in the rest of Africa, results in a huge diversity of climatic conditions that steer a wide range of vegetation landscapes, biodiversity and human occupations. Meridional rainfall gradients dominate in the west along the Nile valley and its surroundings, where a single boreal summer peak is mostly observed. Bimodal regimes (generally peaking in April and November) prevail in the east, gradually shifting to a single austral summer peak to the south. The swift seasonal shift of the Intertropical Convergence Zone and its replacement in January–February and June–September by strong meridional, generally diverging low-level winds (e.g., the Somali Jet), account for the low rainfall. These large-scale flows interact with topography and lakes, which have their own local circulation in the form of mountain and lake breezes. This results in complex rainfall patterns, with a strong diurnal component, and a frequent asymmetry in the rainfall distribution with respect to the major relief features. Whereas highly organized rain-producing systems are uncommon, convection is partly modulated at intra-seasonal (about 30–60-day) timescales. Interannual variability shows a fair level of spatial coherence in the region, at least in July–September in the west (Ethiopia and Nile Valley) and October–December in the east along the Indian Ocean. This is associated with a strong forcing from sea-surface temperatures in the Pacific and Indian Oceans, and to a lesser extent the Atlantic Ocean. As a result, Eastern Africa shows some of the largest interannual rainfall variations in the world. Some decadal-scale variations are also found, including a drying trend of the March–May rainy season since the 1980s in the eastern part of the region. Eastern Africa overall mean temperature increased by 0.7 to 1 °C from 1973 to 2013, depending on the season. The strong, sometimes non-linear altitudinal gradients of temperature and moisture regimes, also contribute to the climate diversity of Eastern Africa.

Accurate projections of climate change under increasing atmospheric greenhouse gas levels are needed to evaluate the environmental cost of anthropogenic emissions, and to guide mitigation efforts. These projections are nowhere more important than Africa, with its high dependence on rain-fed agriculture and, in many regions, limited resources for adaptation. Climate models provide our best method for climate prediction but there are uncertainties in projections, especially on regional space scale. In Africa, limitations of observational networks add to this uncertainty since a crucial step in improving model projections is comparisons with observations. Exceeding uncertainties associated with climate model simulation are uncertainties due to projections of future emissions of CO₂ and other greenhouse gases. Humanity’s choices in emissions pathways will have profound effects on climate, especially after the mid-century.

The African Sahel is a transition zone characterized by strong meridional precipitation and temperature gradients. Over West Africa, the Sahel marks the northernmost extent of the West African monsoon system. The region’s climate is known to be sensitive to sea surface temperatures, both regional and global, as well as to land surface conditions. Increasing atmospheric greenhouse gases are already causing amplified warming over the Sahara Desert and, consequently, increased rainfall in parts of the Sahel. Climate model projections indicate that much of this increased rainfall will be delivered in the form of more intense storm systems.

The complicated and highly regional precipitation regimes of East Africa present a challenge for climate modeling. Within roughly 5º of latitude of the equator, rainfall is delivered in two seasons—the long rains in the spring, and the short rains in the fall. Regional climate model projections suggest that the long rains will weaken under greenhouse gas forcing, and the short rains season will extend farther into the winter months. Observations indicate that the long rains are already weakening.

Changes in seasonal rainfall over parts of subtropical southern Africa are observed, with repercussions and challenges for agriculture and water availability. Some elements of these observed changes are captured in model simulations of greenhouse gas-induced climate change, especially an early demise of the rainy season. The projected changes are quite regional, however, and more high-resolution study is needed. In addition, there has been very limited study of climate change in the Congo Basin and across northern Africa. Continued efforts to understand and predict climate using higher-resolution simulation must be sustained to better understand observed and projected changes in the physical processes that support African precipitation systems as well as the teleconnections that communicate remote forcings into the continent.

The atmospheric circulation in the mid-latitudes of both hemispheres is usually dominated by westerly winds and by planetary-scale and shorter-scale synoptic waves, moving mostly from west to east. A remarkable and frequent exception to this “usual” behavior is atmospheric blocking. Blocking occurs when the usual zonal flow is hindered by the establishment of a large-amplitude, quasi-stationary, high-pressure meridional circulation structure which “blocks” the flow of the westerlies and the progression of the atmospheric waves and disturbances embedded in them. Such blocking structures can have lifetimes varying from a few days to several weeks in the most extreme cases. Their presence can strongly affect the weather of large portions of the mid-latitudes, leading to the establishment of anomalous meteorological conditions. These can take the form of strong precipitation episodes or persistent anticyclonic regimes, leading in turn to floods, extreme cold spells, heat waves, or short-lived droughts. Even air quality can be strongly influenced by the establishment of atmospheric blocking, with episodes of high concentrations of low-level ozone in summer and of particulate matter and other air pollutants in winter, particularly in highly populated urban areas.

Atmospheric blocking has the tendency to occur more often in winter and in certain longitudinal quadrants, notably the Euro-Atlantic and the Pacific sectors of the Northern Hemisphere. In the Southern Hemisphere, blocking episodes are generally less frequent, and the longitudinal localization is less pronounced than in the Northern Hemisphere.

Blocking has aroused the interest of atmospheric scientists since the middle of the last century, with the pioneering observational works of Berggren, Bolin, Rossby, and Rex, and has become the subject of innumerable observational and theoretical studies. The purpose of such studies was originally to find a commonly accepted structural and phenomenological definition of atmospheric blocking. The investigations went on to study blocking climatology in terms of the geographical distribution of its frequency of occurrence and the associated seasonal and inter-annual variability. Well into the second half of the 20th century, a large number of theoretical dynamic works on blocking formation and maintenance started appearing in the literature. Such theoretical studies explored a wide range of possible dynamic mechanisms, including large-amplitude planetary-scale wave dynamics, including Rossby wave breaking, multiple equilibria circulation regimes, large-scale forcing of anticyclones by synoptic-scale eddies, finite-amplitude non-linear instability theory, and influence of sea surface temperature anomalies, to name but a few. However, to date no unique theoretical model of atmospheric blocking has been formulated that can account for all of its observational characteristics.

When numerical, global short- and medium-range weather predictions started being produced operationally, and with the establishment, in the late 1970s and early 1980s, of the European Centre for Medium-Range Weather Forecasts, it quickly became of relevance to assess the capability of numerical models to predict blocking with the correct space-time characteristics (e.g., location, time of onset, life span, and decay). Early studies showed that models had difficulties in correctly representing blocking as well as in connection with their large systematic (mean) errors.

Despite enormous improvements in the ability of numerical models to represent atmospheric dynamics, blocking remains a challenge for global weather prediction and climate simulation models. Such modeling deficiencies have negative consequences not only for our ability to represent the observed climate but also for the possibility of producing high-quality seasonal-to-decadal predictions. For such predictions, representing the correct space-time statistics of blocking occurrence is, especially for certain geographical areas, extremely important.

Pastoralists around the world are exposed to climate change and increasing climate variability. Various downscaled regional climate models in Africa support community reports of rising temperatures as well as changes in the seasonality of rainfall and drought. In addition to climate, pastoralists have faced a second exposure to unsupportive policy environments. Dating back to the colonial period, a lack of knowledge about pastoralism and a systemic marginalization of pastoral communities influenced the size and nature of government investments in pastoral lands. National governments prioritized farming communities and failed to pay adequate attention to drylands and pastoral communities. The limited government interventions that occurred were often inconsistent with contemporary realities of pastoralism and pastoral communities. These included attempts at sedentarization and modernization, and in other ways changing the priorities and practices of pastoral communities.

The survival of pastoral communities in Africa in the context of this double exposure has been a focus for scholars, development practitioners, as well as national governments in recent years. Scholars initially drew attention to pastoralists’ drought-coping strategies, and later examined the multiple ways in which pastoralists manage risk and exploit unpredictability. It has been learned that pastoralists are rational land managers whose experience with variable climate has equipped them with the skills needed for adaptation. Pastoralists follow several identifiable adaptation paths, including diversification and modification of their herds and herding strategies; adoption of livelihood activities that did not previously play a permanent role; and a conscious decision to train the next generation for nonpastoral livelihoods. Ongoing government interventions around climate change still prioritize cropping over herding. Sometimes, such nationally supported adaptation plans can undermine community-based adaptation practices, autonomously evolving within pastoral communities. Successful adaptation hinges on recognition of the value of autonomous adaptation and careful integration of such adaptation with national plans.