Florian Sévellec and Bablu Sinha
The Atlantic meridional overturning circulation (AMOC) is a large, basin-scale circulation located in the Atlantic Ocean that transports 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. The heat capacity of a layer of 2 m of seawater is equivalent to that of the entire atmosphere; therefore, ocean heat content dominates Earth’s energy storage. For this reason and because of the AMOC’s typically slow decadal variations, the AMOC regulates North Atlantic climate and contributes to the relatively mild climate of Europe. Hence, predicting AMOC 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 accurate prediction.
Predictability studies focus on factors determining our ability to predict the AMOC rather than 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. On the other hand, 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 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, which are conducive to significant disruption of the AMOC.
Beyond these difficulties in assessing the predictability, decadal prediction systems have been developed and tested through a range of hindcasts. The inherent difficulties of operational forecasts span from developing efficient initialization methods to setting accurate radiative forcing to correcting for model drift and bias, all these improvements being estimated and validated through a range of specifically designed skill metrics.
Wansuo Duan and Mu Mu
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.
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.
Timothy M. Shanahan
West Africa is among the most populated regions of the world, and it is predicted to continue to have one of the fastest growing populations in the first half of the 21st century. More than 35% of its GDP comes from agricultural production, and a large fraction of the population faces chronic hunger and malnutrition. Its dependence on rainfed agriculture is compounded by extreme variations in rainfall, including both droughts and floods, which appear to have become more frequent. As a result, it is considered a region highly vulnerable to future climate changes. At the same time, CMIP5 model projections for the next century show a large spread in precipitation estimates for West Africa, making it impossible to predict even the direction of future precipitation changes for this region. To improve predictions of future changes in the climate of West Africa, a better understanding of past changes, and their causes, is needed. Long climate and vegetation reconstructions, extending back to 5−8 Ma, demonstrate that changes in the climate of West Africa are paced by variations in the Earth’s orbit, and point to a direct influence of changes in low-latitude seasonal insolation on monsoon strength. However, the controls on West African precipitation reflect the influence of a complex set of forcing mechanisms, which can differ regionally in their importance, especially when insolation forcing is weak. During glacial intervals, when insolation changes are muted, millennial-scale dry events occur across North Africa in response to reorganizations of the Atlantic circulation associated with high-latitude climate changes. On centennial timescales, a similar response is evident, with cold conditions during the Little Ice Age associated with a weaker monsoon, and warm conditions during the Medieval Climate Anomaly associated with wetter conditions. Land surface properties play an important role in enhancing changes in the monsoon through positive feedback. In some cases, such as the mid-Holocene, the feedback led to abrupt changes in the monsoon, but the response is complex and spatially heterogeneous. Despite advances made in recent years, our understanding of West African monsoon variability remains limited by the dearth of continuous, high- resolution, and quantitative proxy reconstructions, particularly from terrestrial sites.
Judith L. Lean
Emergent in recent decades are robust specifications and understanding of connections between the Sun’s changing radiative energy and Earth’s changing climate and atmosphere. This follows more than a century of contentious debate about the reality of such connections, fueled by ambiguous observations, dubious correlations, and lack of plausible mechanisms. It derives from a new generation of observations of the Sun and the Earth made from space, and a new generation of physical climate models that integrate the Earth’s surface and ocean with the extended overlying atmosphere. Space-based observations now cover more than three decades and enable statistical attribution of climate change related to the Sun’s 11-year activity cycle on global scales, simultaneously with other natural and anthropogenic influences. Physical models that fully resolve the stratosphere and its embedded ozone layer better replicate the complex and subtle processes that couple the Sun and Earth.
An increase of ~0.1% in the Sun’s total irradiance, as observed near peak activity during recent 11-year solar cycles, is associated with an increase of ~0.1oC in Earth’s global surface temperature, with additional complex, time-dependent regional responses. The overlying atmosphere warms more, by 0.3oC near 20 km. Because solar radiation impinges primarily at low latitudes, the increased radiant energy alters equator-to-pole thermal gradients, initiating dynamical responses that produce regions of both warming and cooling at mid to high latitudes. Because solar energy deposition depends on altitude as a result of height-dependent atmospheric absorption, changing solar radiation establishes vertical thermal gradients that further alter dynamical motions within the Earth system.
It remains uncertain whether there are long-term changes in solar irradiance on multidecadal time scales other than due to the varying amplitude of the 11-year cycle. If so the magnitude of the additional change is expected to be comparable to that observed during the solar activity cycle. Were the Sun’s activity to become anomalously low, declining during the next century to levels of the Maunder Minimum (from 1645 to 1715), the expected global surface temperature cooling is less than a few tenths oC. In contrast, a scenario of moderate greenhouse gas increase with climate forcing of 2.6 W m−2 over the next century is expected to warm the globe 1.5 to 1.9oC, an order of magnitude more than the hypothesized solar-induced cooling over the same period.
Future challenges include the following: securing sufficiently robust observations of the Sun and Earth to elucidate changes on climatological time scales; advancing physical climate models to simulate realistic responses to changing solar radiation on decadal time scales, synergistically at the Earth’s surface and in the ocean and atmosphere; disentangling the Sun’s influence from that of other natural and anthropogenic influences as the climate and atmosphere evolve; projecting past and future changes in the Sun and Earth’s climate and atmosphere; and communicating new understanding across scientific disciplines, and to political and societal stakeholders.