Stefano Tibaldi and Franco Molteni
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.
Precipitation levels in southern Africa exhibit a marked east–west gradient and are characterized by strong seasonality and high interannual variability. Much of the mainland south of 15°S exhibits a semiarid to dry subhumid climate. More than 66 percent of rainfall in the extreme southwest of the subcontinent occurs between April and September. Rainfall in this region—termed the winter rainfall zone (WRZ)—is most commonly associated with the passage of midlatitude frontal systems embedded in the austral westerlies. In contrast, more than 66 percent of mean annual precipitation over much of the remainder of the subcontinent falls between October and March. Climates in this summer rainfall zone (SRZ) are dictated by the seasonal interplay between subtropical high-pressure systems and the migration of easterly flows associated with the Intertropical Convergence Zone. Fluctuations in both SRZ and WRZ rainfall are linked to the variability of sea-surface temperatures in the oceans surrounding southern Africa and are modulated by the interplay of large-scale modes of climate variability, including the El Niño-Southern Oscillation (ENSO), Southern Indian Ocean Dipole, and Southern Annular Mode.
Ideas about long-term rainfall variability in southern Africa have shifted over time. During the early to mid-19th century, the prevailing narrative was that the climate was progressively desiccating. By the late 19th to early 20th century, when gauged precipitation data became more readily available, debate shifted toward the identification of cyclical rainfall variation. The integration of gauge data, evidence from historical documents, and information from natural proxies such as tree rings during the late 20th and early 21st centuries, has allowed the nature of precipitation variability since ~1800 to be more fully explored.
Drought episodes affecting large areas of the SRZ occurred during the first decade of the 19th century, in the early and late 1820s, late 1850s–mid-1860s, mid-late 1870s, earlymid-1880s, and mid-late 1890s. Of these episodes, the drought during the early 1860s was the most severe of the 19th century, with those of the 1820s and 1890s the most protracted. Many of these droughts correspond with more extreme ENSO warm phases.
Widespread wetter conditions are less easily identified. The year 1816 appears to have been relatively wet across the Kalahari and other areas of south central Africa. Other wetter episodes were centered on the late 1830s–early 1840s, 1855, 1870, and 1890. In the WRZ, drier conditions occurred during the first decade of the 19th century, for much of the mid-late 1830s through to the mid-1840s, during the late 1850s and early 1860s, and in the early-mid-1880s and mid-late 1890s. As for the SRZ, markedly wetter years are less easily identified, although the periods around 1815, the early 1830s, mid-1840s, mid-late 1870s, and early 1890s saw enhanced rainfall. Reconstructed rainfall anomalies for the SRZ suggest that, on average, the region was significantly wetter during the 19th century than the 20th and that there appears to have been a drying trend during the 20th century that has continued into the early 21st. In the WRZ, average annual rainfall levels appear to have been relatively consistent between the 19th and 20th centuries, although rainfall variability increased during the 20th century compared to the 19th.
B.N. Goswami and Soumi Chakravorty
Lifeline for about one-sixth of the world’s population in the subcontinent, the Indian summer monsoon (ISM) is an integral part of the annual cycle of the winds (reversal of winds with seasons), coupled with a strong annual cycle of precipitation (wet summer and dry winter). For over a century, high socioeconomic impacts of ISM rainfall (ISMR) in the region have driven scientists to attempt to predict the year-to-year variations of ISM rainfall. A remarkably stable phenomenon, making its appearance every year without fail, the ISM climate exhibits a rather small year-to-year variation (the standard deviation of the seasonal mean being 10% of the long-term mean), but it has proven to be an extremely challenging system to predict. Even the most skillful, sophisticated models are barely useful with skill significantly below the potential limit on predictability. Understanding what drives the mean ISM climate and its variability on different timescales is, therefore, critical to advancing skills in predicting the monsoon. A conceptual ISM model helps explain what maintains not only the mean ISM but also its variability on interannual and longer timescales.
The annual ISM precipitation cycle can be described as a manifestation of the seasonal migration of the intertropical convergence zone (ITCZ) or the zonally oriented cloud (rain) band characterized by a sudden “onset.” The other important feature of ISM is the deep overturning meridional (regional Hadley circulation) that is associated with it, driven primarily by the latent heat release associated with the ISM (ITCZ) precipitation. The dynamics of the monsoon climate, therefore, is an extension of the dynamics of the ITCZ. The classical land–sea surface temperature gradient model of ISM may explain the seasonal reversal of the surface winds, but it fails to explain the onset and the deep vertical structure of the ISM circulation. While the surface temperature over land cools after the onset, reversing the north–south surface temperature gradient and making it inadequate to sustain the monsoon after onset, it is the tropospheric temperature gradient that becomes positive at the time of onset and remains strongly positive thereafter, maintaining the monsoon. The change in sign of the tropospheric temperature (TT) gradient is dynamically responsible for a symmetric instability, leading to the onset and subsequent northward progression of the ITCZ. The unified ISM model in terms of the TT gradient provides a platform to understand the drivers of ISM variability by identifying processes that affect TT in the north and the south and influence the gradient.
The predictability of the seasonal mean ISM is limited by interactions of the annual cycle and higher frequency monsoon variability within the season. The monsoon intraseasonal oscillation (MISO) has a seminal role in influencing the seasonal mean and its interannual variability. While ISM climate on long timescales (e.g., multimillennium) largely follows the solar forcing, on shorter timescales the ISM variability is governed by the internal dynamics arising from ocean–atmosphere–land interactions, regional as well as remote, together with teleconnections with other climate modes. Also important is the role of anthropogenic forcing, such as the greenhouse gases and aerosols versus the natural multidecadal variability in the context of the recent six-decade long decreasing trend of ISM rainfall.
The Sahel of Africa has been identified as having the strongest land–atmosphere (L/A) interactions on Earth. The Sahelian L/A interaction studies started in the late 1970s. However, due to controversies surrounding the early studies, in which only a single land parameter was considered in L/A interactions, the credibility of land-surface effects on the Sahel’s climate has long been challenged. Using general circulation models and regional climate models coupled with biogeophysical and dynamic vegetation models as well as applying analyses of satellite-derived data, field measurements, and assimilation data, the effects of land-surface processes on West African monsoon variability, which dominates the Sahel climate system at intraseasonal, seasonal, interannual, and decadal scales, as well as mesoscale, have been extensively investigated to realistically explore the Sahel L/A interaction: its effects and the mechanisms involved.
The Sahel suffered the longest and most severe drought on the planet in the 20th century. The devastating environmental and socioeconomic consequences resulting from drought-induced famines in the Sahel have provided strong motivation for the scientific community and society to understand the causes of the drought and its impact. It was controversial and under debate whether the drought was a natural process, mainly induced by sea-surface temperature variability, or was affected by anthropogenic activities. Diagnostic and modeling studies of the sea-surface temperature have consistently demonstrated it exerts great influence on the Sahel climate system, but sea-surface temperature is unable to explain the full scope of the Sahel climate variability and the later 20th century’s drought. The effect of land-surface processes, especially land-cover and land-use change, on the drought have also been extensively investigated. The results with more realistic land-surface models suggest land processes are a first-order contributor to the Sahel climate and to its drought during the later 1960s to the 1980s, comparable to sea surface temperature effects. The issues that caused controversies in the early studies have been properly addressed in the studies with state-of-the-art models and available data.
The mechanisms through which land processes affect the atmosphere are also elucidated in a number of studies. Land-surface processes not only affect vertical transfer of radiative fluxes and heat fluxes but also affect horizontal advections through their effect on the atmospheric heating rate and moisture flux convergence/divergence as well as horizontal temperature gradients.
Fred Kucharski and Muhammad Adnan Abid
The interannual variability of Indian summer monsoon is probably one of the most intensively studied phenomena in the research area of climate variability. This is because even relatively small variations of about 10% to 20% from the mean rainfall may have dramatic consequences for regional agricultural production. Forecasting such variations months in advance could help agricultural planning substantially. Unfortunately, a perfect forecast of Indian monsoon variations, like any other regional climate variations, is impossible in a long-term prediction (that is, more than 2 weeks or so in advance). The reason is that part of the atmospheric variations influencing the monsoon have an inherent predictability limit of about 2 weeks. Therefore, such predictions will always be probabilistic, and only likelihoods of droughts, excessive rains, or normal conditions may be provided. However, even such probabilistic information may still be useful for agricultural planning. In research regarding interannual Indian monsoon rainfall variations, the main focus is therefore to identify the remaining predictable component and to estimate what fraction of the total variation this component accounts for. It turns out that slowly varying (with respect to atmospheric intrinsic variability) sea-surface temperatures (SSTs) provide the dominant part of the predictable component of Indian monsoon variability. Of the predictable part arising from SSTs, it is the El Niño Southern Oscillation (ENSO) that provides the main part. This is not to say that other forcings may be neglected. Other forcings that have been identified are, for example, SST patterns in the Indian Ocean, Atlantic Ocean, and parts of the Pacific Ocean different from the traditional ENSO region, and springtime snow depth in the Himalayas, as well as aerosols. These other forcings may interact constructively or destructively with the ENSO impact and thus enhance or reduce the ENSO-induced predictable signal. This may result in decade-long changes in the connection between ENSO and the Indian monsoon. The physical mechanism for the connection between ENSO and the Indian monsoon may be understood as large-scale adjustment of atmospheric heatings and circulations to the ENSO-induced SST variations. These adjustments modify the Walker circulation and connect the rising/sinking motion in the central-eastern Pacific during a warm/cold ENSO event with sinking/rising motion in the Indian region, leading to reduced/increased rainfall.
Henk A. Dijkstra
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.
Edward Hanna and Thomas E. Cropper
Many variations in the weather in the European and North Atlantic regions are linked with changes in the North Atlantic Oscillation (NAO). The NAO is measured using a south-minus-north index of atmospheric surface pressure variation across the North Atlantic and is closely connected with changes in the North Atlantic atmospheric polar jet stream and wider changes in atmospheric circulation. The physical, human, and biological impacts of NAO changes extend well beyond weather and climate, with major economic, social, and environmental effects. The NAO index based on barometric pressure records now extends as far back as 1850, based on recent work. Although there are few significant overall trends in monthly or seasonal NAO (i.e., for the whole record), there are many shorter-term multidecadal variations. A prominent increase in the NAO between the 1960s and 1990s was widely noted in previous work and was thought to be related to human-induced greenhouse gas forcing. However, since then this trend has reversed, with a significant decrease in the summer NAO since the 1990s and a striking increase in variability of the winter—especially December—NAO that has resulted in four of the six highest and two of the five lowest NAO Decembers occurring during 2004–2015 in the 116-year record, with accompanying more variable year-to-year winter weather conditions over the United Kingdom. These NAO changes are related to an increasing trend in the Greenland Blocking Index (GBI; equals high pressure over Greenland) in summer and a significantly more variable GBI in December. Such NAO and related jet stream and blocking changes are not generally present in the current generation of global climate models, although recent process studies offer insights into their possible causes. Several plausible climate forcings and feedbacks, including changes in the sun’s energy output and the Arctic amplification of global warming with accompanying reductions in sea ice, may help explain the recent NAO changes. Recent research also suggests significant skill in being able to make seasonal NAO predictions and therefore long-range weather forecasts for up to several months ahead for northwest Europe. However, global climate models remain unclear on longer-term NAO predictions for the remainder of the 21st century.
Oceanic mixing is one of the major determinants of the ocean circulation and its climatological influences. Existing distributions of mixing properties determine the rates of storage and redistribution within the climate system of fundamental scalar tracers including heat, fresh water, oxygen, carbon, and others. Observations have overturned earlier concepts that mixing rates might be approximately uniform throughout the ocean volume, with profound implications for determining the circulation and its properties. Inferences about past and potential future oceanic circulations and the resulting climate influence require determination of changed energy inputs and the expected consequent adjustment of mixing processes and their influence.
Florian Sévellec and Bablu Sinha
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Climate Science. Please check back later for the full article.
The Atlantic Meridional Overturning Circulation (AMOC) is a large, basin scale circulation located in the Atlantic Ocean and transporting climatically important quantities of heat northward. It can be described schematically as a northward flow in the warm upper ocean and a southward return flow at depth, in much colder water. Because of the dominance of oceanic heat content in Earth’s energy storage (the heat capacity of a layer of 2 m of seawater is equivalent to that of the entire atmosphere) and its typical slow decadal variations, the AMOC regulates North Atlantic climate and contributes to the relatively mild climate of Europe. Because of the AMOC’s influence on climate, predicting its variations is crucial for predicting climate variations in regions bordering the North Atlantic. Similar to weather predictions, climate predictions are based on numerical simulations of the climate system. However providing accurate predictions on such long timescales is far from straightforward. Even in a perfect model approach, where biases between numerical models and reality are ignored, the chaotic nature of AMOC variability (i.e., high sensitivity to initial conditions) is a significant source of uncertainty, limiting its accuracy of prediction.
Predictability studies focus on factors determining our ability to predict the AMOC rather than on the actual predictions. To this end, processes affecting AMOC predictability can be separated into two categories: processes acting as a source of predictability (periodic harmonic oscillations, for instance) and processes acting as a source of uncertainty (small errors that grow and significantly modify the outcome of numerical simulations). To understand the former category, harmonic modes of variability or precursors of AMOC variations are identified. However, in a perfect model approach, the sources of uncertainty are characterized by the spread of numerical simulations differentiated by the application of small differences to their initial conditions. Two alternative and complementary frameworks have arisen to investigate this spread. The pragmatic framework corresponds to performing an ensemble of simulations, by imposing a randomly chosen small error on the initial conditions of individual simulations. This allows a probabilistic approach and the means to statistically characterize the importance of the initial condition by evaluating the spread of the ensemble. The theoretical framework uses stability analysis to identify small perturbations to the initial conditions that are conducive to significant disruption of the AMOC.
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Climate Science. Please check back later for the full article.
The tropical Indian Ocean is unique in several aspects. Unlike the Pacific and the Atlantic Oceans, the Indian Ocean is bounded to the north by a large landmass, the Eurasian continent. The large thermal heat contrast between the ocean in the south and the land in the north induces the world’s strongest monsoon systems in South and East Asia, in response to the seasonal migration of solar radiation. The strong and seasonally reversing surface winds generate large seasonal variations in ocean currents and basin-wide meridional heat transport across the equator. In contrast to the tropical Pacific and the Atlantic, where easterly trade winds prevail throughout the year, westerly winds (albeit with a relatively weak magnitude) blow along the equatorial Indian Ocean, particularly during the boreal spring and autumn seasons, generating the semi-annual Yoshida-Wyrtki eastward equatorial ocean currents. As a consequence of the lack of equatorial upwelling, the tropical Indian Ocean occupies the largest portion of the warm water pool (with Sea Surface Temperature [SST] being greater than 28 °C) on Earth. The massive warm water provides a huge potential energy available for deep convections that significantly affect the weather-climate over the globe. It is therefore of vital importance to discover and understand climate variabilities in the Indian Ocean and to further develop a capability to correctly predict the seasonal departures of the warm waters and their global teleconnections.
The Indian Ocean Dipole (IOD) is the one of the recently discovered climate variables in the tropical Indian Ocean. During the development of the super El Niño in 1997, the climatological zonal SST gradient along the equator was much reduced (with strong cold SST anomalies in the east and warm anomalies in the west). The surface westerly winds switched to easterlies, and the ocean thermocline became shallow in the east and deep in the west. These features are reminiscent of what are observed during El Niño years in the Pacific, representing a typical coupled process between the ocean and the atmosphere. The IOD event in 1997 contributed significantly to floods in eastern Africa and severe droughts and bushfires in Indonesia and southeastern Australia. Since the discovery of the 1997 IOD event, extensive efforts have been made to lead the rapid progress in understanding the air-sea coupled climate variabilities in the Indian Ocean; and many approaches, including simple statistical models and comprehensive ocean-atmosphere coupled models, have been developed to simulate and predict the Indian Ocean climate.
Essential to the discussion are the ocean-atmosphere dynamics underpinning the seasonal predictability of the IOD, critical factors that limit the IOD predictability (inter-comparison with El Niño-Southern Oscillation [ENSO]), observations and initialization approaches that provide realistic initial conditions for IOD predictions, models and approaches that have been developed to simulate and predict the IOD, the influence of global warming on the IOD predictability, impacts of IOD-ENSO interactions on the IOD predictability, and the current status and perspectives of the IOD prediction at seasonal to multi-annual timescales.