Abstract

To gain a new perspective on the interaction of the Atlantic Ocean and the atmosphere, the relationship between the atmospheric and oceanic meridional energy transports is studied in a version of HadCM3, the U.K. Hadley Centre's coupled climate model. The correlation structure of the energy transports in the atmosphere and Atlantic Ocean as a function of latitude, and the cross correlation between the two systems are analyzed. The processes that give rise to the correlations are then elucidated using regression analyses.

In northern midlatitudes, the interannual variability of the Atlantic Ocean energy transport is dominated by Ekman processes. Anticorrelated zonal winds in the subtropics and midlatitudes, particularly associated with the North Atlantic Oscillation (NAO), drive anticorrelated meridional Ekman transports. Variability in the atmospheric energy transport is associated with changes in the stationary waves, but is only weakly related to the NAO. Nevertheless, atmospheric driving of the oceanic Ekman transports is responsible for a bipolar pattern in the correlation between the atmosphere and Atlantic Ocean energy transports.

In the Tropics, the interannual variability of the Atlantic Ocean energy transport is dominated by an adjustment of the tropical ocean to coastal upwelling induced along the Venezuelan coast by a strengthening of the easterly trade winds. Variability in the atmospheric energy transport is associated with a cross-equatorial meridional overturning circulation that is only weakly associated with variability in the trade winds along the Venezuelan coast. In consequence, there is only very limited correlation between the atmosphere and Atlantic Ocean energy transports in the Tropics of HadCM3.

Abstract

The decadal predictability of three-dimensional Atlantic Ocean anomalies is examined in a coupled global climate model [the third climate configuration of the Met Office Unified Model (HadCM3)] using a linear inverse modeling (LIM) approach. It is found that the evolution of temperature and salinity in the Atlantic, and the strength of the meridional overturning circulation (MOC), can be effectively described by a linear dynamical system forced by white noise. The forecasts produced using this linear model are more skillful than other reference forecasts for several decades. Furthermore, significant nonnormal amplification is found under several different norms. The regions from which this growth occurs are found to be fairly shallow and located in the far North Atlantic. Initially, anomalies in the Nordic seas impact the MOC and the anomalies then grow to fill the entire Atlantic basin, especially at depth, over one to three decades. It is found that the structure of the optimal initial condition for amplification is sensitive to the norm employed, but the initial growth seems to be dominated by MOC-related basin-scale changes, irrespective of the choice of norm. The consistent identification of the far North Atlantic as the most sensitive region for small perturbations suggests that additional observations in this region would be optimal for constraining decadal climate predictions.

Abstract

A key aspect in designing an efficient decadal prediction system is ensuring that the uncertainty in the ocean initial conditions is sampled optimally. Here one strategy for addressing this issue is considered by investigating the growth of optimal perturbations in the third climate configuration of the Met Office Unified Model (HadCM3) global climate model (GCM). More specifically, climatically relevant singular vectors (CSVs)—the small perturbations of which grow most rapidly for a specific set of initial conditions—are estimated for decadal time scales in the Atlantic Ocean. It is found that reliable CSVs can be estimated by running a large ensemble of integrations of the GCM. Amplification of the optimal perturbations occurs for more than 10 yr, and possibly up to 40 yr. The identified regions for growing perturbations are found to be in the far North Atlantic, and these perturbations cause amplification through an anomalous meridional overturning circulation response. Additionally, this type of analysis potentially informs the design of future ocean observing systems by identifying the sensitive regions where small uncertainties in the ocean state can grow maximally. Although these CSVs are expensive to compute, ways in which the process could be made more efficient in the future are identified.

Faced by the realities of a changing climate, decision makers in a wide variety of organizations are increasingly seeking quantitative predictions of regional and local climate. An important issue for these decision makers, and for organizations that fund climate research, is what is the potential for climate science to deliver improvements—especially reductions in uncertainty—in such predictions? Uncertainty in climate predictions arises from three distinct sources: internal variability, model uncertainty, and scenario uncertainty. Using data from a suite of climate models, we separate and quantify these sources. For predictions of changes in surface air temperature on decadal timescales and regional spatial scales, we show that uncertainty for the next few decades is dominated by sources (model uncertainty and internal variability) that are potentially reducible through progress in climate science. Furthermore, we find that model uncertainty is of greater importance than internal variability.

Our findings have implications for managing adaptation to a changing climate. Because the costs of adaptation are very large, and greater uncertainty about future climate is likely to be associated with more expensive adaptation, reducing uncertainty in climate predictions is potentially of enormous economic value. We highlight the need for much more work to compare (a) the cost of various degrees of adaptation, given current levels of uncertainty and (b) the cost of new investments in climate science to reduce current levels of uncertainty. Our study also highlights the importance of targeting climate science investments on the most promising opportunities to reduce prediction uncertainty.

Abstract

Current state-of-the-art global climate models produce different values for Earth’s mean temperature. When comparing simulations with each other and with observations, it is standard practice to compare temperature anomalies with respect to a reference period. It is not always appreciated that the choice of reference period can affect conclusions, both about the skill of simulations of past climate and about the magnitude of expected future changes in climate. For example, observed global temperatures over the past decade are toward the lower end of the range of the phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulations irrespective of what reference period is used, but exactly where they lie in the model distribution varies with the choice of reference period. Additionally, we demonstrate that projections of when particular temperature levels are reached, for example, 2 K above “preindustrial,” change by up to a decade depending on the choice of reference period. In this article, we discuss some of the key issues that arise when using anomalies relative to a reference period to generate climate projections. We highlight that there is no perfect choice of reference period. When evaluating models against observations, a long reference period should generally be used, but how long depends on the quality of the observations available. The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) choice to use a 1986–2005 reference period for future global temperature projections was reasonable, but a case-by-case approach is needed for different purposes and when assessing projections of different climate variables. Finally, we recommend that any studies that involve the use of a reference period should explicitly examine the robustness of the conclusions to alternative choices.

Abstract

Interdecadal variability of the Atlantic thermohaline circulation (THC) is studied in the third version of the Hadley Centre global coupled atmosphere–ocean sea-ice general circulation model (HadCM3). A diagnostic approach is used to elucidate the mechanism that governs the variability and its impacts on climate. An irregular and heavily damped THC oscillation with a period around 25 yr is identified. The oscillation appears to be forced by the atmosphere but the ocean is responsible for setting the time scale. Following a minimum in the THC, the mechanism for phase reversal involves the accumulation of cold water in the subpolar gyre, leading to an acceleration of the gyre circulation and the North Atlantic Current. This acceleration increases the transport of saline waters into the regions of active deep convection, raising the upper-ocean density and leading, after adjustment, to acceleration of the THC. The atmosphere stimulates this THC variability in two ways: 1) by forcing the subpolar gyre through (North Atlantic Oscillation) NAO-related wind stress curl and heat flux anomalies; and 2) by direct forcing of the region of active deep convection, also through wind stress curl and heat flux anomalies. The latter is not closely related to the NAO. The mechanism for phase reversal has many similarities to that found in a previous study with a much lower resolution coupled model, suggesting that this mechanism may be quite robust. However the time scale, and details of the atmospheric forcing, differ.

The THC variability in HadCM3 has significant impacts on the atmosphere not just in the Atlantic region but also more widely, throughout the global Tropics. The mechanism involves modulation by the THC of the cross-equator SST gradient in the tropical Atlantic. The SST anomalies induce a displacement of the ITCZ in the Atlantic basin with knock-on effects over the other ocean basins. These findings highlight the potential importance of the Atlantic THC as a cause of interdecadal climate variability on a global scale.

Abstract

During the 1990s there was a major change in the state of the world's oceans. In particular, the North Atlantic underwent a rapid warming, with sea surface temperatures (SSTs) in the subpolar gyre region increasing by 1°C in just a few years. Associated with the changes in SST patterns were changes in the surface climate, in particular, a tendency for warm and dry conditions over areas of North America in all seasons, and warm springs and wet summers over areas of Europe. Here, the extent to which a climate prediction system initialized using observations of the ocean state is able to capture the observed changes in seasonal mean surface climate is investigated. Rather than examining predictions of the mid-1990s North Atlantic warming event itself, this study compares hindcasts started before and after the warming, relative to hindcasts that do not assimilate information. It is demonstrated that the hindcasts capture many aspects of the observed changes in seasonal mean surface climate, especially in North, South, and Central America and in Europe. Furthermore, the prediction system retains skill beyond the first year. Finally, it is shown that, in addition to memory of Atlantic SSTs, successfully predicting Pacific SSTs was likely important for the hindcasts to predict surface climate over North America.

Abstract

A coupled ocean–atmosphere general circulation model is used to investigate the modulation of El Niño–Southern Oscillation (ENSO) variability due to a weakened Atlantic thermohaline circulation (THC). The THC weakening is induced by freshwater perturbations in the North Atlantic, and leads to a well-known sea surface temperature dipole and a southward shift of the intertropical convergence zone (ITCZ) in the tropical Atlantic. Through atmospheric teleconnections and local coupled air–sea feedbacks, a meridionally asymmetric mean state change is generated in the eastern equatorial Pacific, corresponding to a weakened annual cycle, and westerly anomalies develop over the central Pacific. The westerly anomalies are associated with anomalous warming of SST, causing an eastward extension of the west Pacific warm pool particularly in August–February, and enhanced precipitation. These and other changes in the mean state lead in turn to an eastward shift of the zonal wind anomalies associated with El Niño events, and a significant increase in ENSO variability.

In response to a 1-Sv (1 Sv ≡ 10⁶ m³ s⁻¹) freshwater input in the North Atlantic, the THC slows down rapidly and it weakens by 86% over years 50–100. The Niño-3 index standard deviation increases by 36% during the first 100-yr simulation relative to the control simulation. Further analysis indicates that the weakened THC not only leads to a stronger ENSO variability, but also leads to a stronger asymmetry between El Niño and La Niña events. This study suggests a role for an atmospheric bridge that rapidly conveys the influence of the Atlantic Ocean to the tropical Pacific and indicates that fluctuations of the THC can mediate not only mean climate globally but also modulate interannual variability. The results may contribute to understanding both the multidecadal variability of ENSO activity during the twentieth century and longer time-scale variability of ENSO, as suggested by some paleoclimate records.

Abstract

Here the factors affecting the mean state and El Niño variability in the Third Hadley Centre Coupled Ocean–Atmosphere General Circulation Model (HadCM3) are examined with and without heat flux or wind stress corrections. There is currently little confidence in the prediction of El Niño for seasonal forecasts or climate change due to the inaccuracies in coupled models. If heat flux or wind stress corrections could reduce these biases then forecasts might be improved.

Heat flux corrections have unexpected effects on both the mean state and variability of HadCM3. HadCM3 is found to be very sensitive to the corrections imposed. If heat flux corrections are imposed Tropics wide then easterlies in the eastern equatorial Pacific are increased leading to localized steep east–west gradients in the thermocline or “thermocline jumps,” which appear to suppress propagation of heat from the west to the east and hence suppress strong El Niños so that ENSO variability is weak. In contrast, if heat flux corrections are imposed only within 10° of the equator, an atmospheric teleconnection from the cold subtropical SST biases intensifies the ITCZ and weakens the equatorial easterlies. As a result, the thermocline jumps are flattened and strong El Niños occur very frequently. Neither heat flux correction procedure improves the representation of El Niño.

Wind stress corrections alone have a small impact on the coupled model. Some of the SST warm biases are reduced, but the variability is not altered significantly.

Abstract

A recent study identified a relationship between North Atlantic Ocean sea surface temperature (SST) gradients in spring and a specific pattern of atmospheric circulation in the following summer: the summer east Atlantic (SEA) pattern. It was shown that the SEA pattern is closely associated with meridional shifts in the eddy-driven jet in response to anomalous SST gradients. In this study, the physical mechanisms underlying this relationship are investigated further. It is shown that the predictable SEA pattern anomalies appear in June–July and undergo substantial amplification between July and August before decaying in September. The associated SST anomalies also grow in magnitude and spatial extent from June to August. The question of why the predictable atmospheric anomalies should occur in summer is addressed, and three factors are identified. The first is the climatological position of the storm track, which migrates poleward from spring to summer. The second is that the magnitude of interannual SST variability underlying the storm track peaks in summer, both in absolute terms, and relative to the underlying mean SST gradient. The third factor is the most interesting. We identify a positive coupled ocean–atmosphere feedback, which operates in summer and leads to the amplification of both SST and atmospheric circulation anomalies. The extent to which the identified processes are captured in the HadGEM3-GC2 climate model is also assessed. The model is able to capture the relationship between spring North Atlantic SSTs and subsequent ocean–atmosphere conditions in early summer, but the relationship is too weak. The results suggest that the real world might be more predictable than is inferred from the models.