The interannual variability of energy transports within and over the Atlantic Ocean in a coupled climate model

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

Interannual to decadal climate predictability in the North Atlantic: A multimodel-ensemble study

Ensemble experiments are performed with five coupled atmosphere-ocean models to investigate the potential for initial-value climate forecasts on interannual to decadal time scales. Experiments are started from similar model-generated initial states, and common diagnostics of predictability are used. We find that variations in the ocean meridional overturning circulation (MOC) are potentially predictable on interannual to decadal time scales, a more consistent picture of the surface temperature impact of decadal variations in the MOC is now apparent, and variations of surface air temperatures in the North Atlantic Ocean are also potentially predictable on interannual to decadal time scales. albeit with potential skill levels that are less than those seen for MOC variations. This intercomparison represents a step forward in assessing the robustness of model estimates of potential skill and is a prerequisite for the development of any operational forecasting system.

Granger causality of coupled climate processes: Ocean feedback on the North Atlantic oscillation

This study uses a Granger causality time series modeling approach to quantitatively diagnose the feedback of daily sea surface temperatures (SSTs) on daily values of the North Atlantic Oscillation (NAO) as simulated by a realistic coupled general circulation model (GCM). Bivariate vector autoregressive time series models are carefully fitted to daily wintertime SST and NAO time series produced by a 50-yr simulation of the Third Hadley Centre Coupled Ocean-Atmosphere GCM (HadCM3). The approach demonstrates that there is a small yet statistically significant feedback of SSTs oil the NAO. The SST tripole index is found to provide additional predictive information for the NAO than that available by using only past values of NAO-the SST tripole is Granger causal for the NAO. Careful examination of local SSTs reveals that much of this effect is due to the effect of SSTs in the region of the Gulf Steam, especially south of Cape Hatteras. The effect of SSTs on NAO is responsible for the slower-than-exponential decay in lag-autocorrelations of NAO notable at lags longer than 10 days. The persistence induced in daily NAO by SSTs causes long-term means of NAO to have more variance than expected from averaging NAO noise if there is no feedback of the ocean on the atmosphere. There are greater long-term trends in NAO than can be expected from aggregating just short-term atmospheric noise, and NAO is potentially predictable provided that future SSTs are known. For example, there is about 10%-30% more variance in seasonal wintertime means of NAO and almost 70% more variance in annual means of NAO due to SST effects than one would expect if NAO were a purely atmospheric process.

Soil moisture mediates association between the winter North Atlantic Oscillation and summer growth in the Park Grass Experiment

Several aspects of terrestrial ecosystems are known to be associated with the North Atlantic Oscillation (NAO) through effects of the NAO on winter climate, but recently the winter NAO has also been shown to be correlated with the following summer climate, including drought. Since drought is a major factor determining grassland primary productivity, the hypothesis was tested that the winter NAO is associated with summer herbage growth through soil moisture availability, using data from the Park Grass Experiment at Rothamsted, UK between 1960 and 1999. The herbage growth rate, mean daily rainfall, mean daily potential evapotranspiration (PE) and the mean and maximum potential soil moisture deficit (PSMD) were calculated between the two annual cuts in early summer and autumn for the unlimed, unfertilized plots. Mean and maximum PSMD were more highly correlated than rainfall or PE with herbage growth rate. Regression analysis showed that the natural logarithm of the herbage growth rate approximately halved for a 250 mm increase in maximum PSMD over the range 50-485 mm. The maximum PSMD was moderately correlated with the preceding winter NAO, with a positive winter NAO index associated with greater maximum PSMD. A positive winter NAO index was also associated with low herbage growth rate, accounting for 22% of the interannual variation in the growth rate. It was concluded that the association between the winter NAO and summer herbage growth rate is mediated by the PSMD in summer.

North Atlantic Oscillation response to transient greenhouse gas forcing and the impact on European winter climate: a CMIP2 multi-model assessment

This study investigates the response of wintertime North Atlantic Oscillation (NAO) to increasing concentrations of atmospheric carbon dioxide (CO2) as simulated by 18 global coupled general circulation models that participated in phase 2 of the Coupled Model Intercomparison Project (CMIP2). NAO has been assessed in control and transient 80-year simulations produced by each model under constant forcing, and 1% per year increasing concentrations of CO2, respectively. Although generally able to simulate the main features of NAO, the majority of models overestimate the observed mean wintertime NAO index of 8 hPa by 5-10 hPa. Furthermore, none of the models, in either the control or perturbed simulations, are able to reproduce decadal trends as strong as that seen in the observed NAO index from 1970-1995. Of the 15 models able to simulate the NAO pressure dipole, 13 predict a positive increase in NAO with increasing CO2 concentrations. The magnitude of the response is generally small and highly model-dependent, which leads to large uncertainty in multi-model estimates such as the median estimate of 0.0061 +/- 0.0036 hPa per %CO2. Although an increase of 0.61 hPa in NAO for a doubling in CO2 represents only a relatively small shift of 0.18 standard deviations in the probability distribution of winter mean NAO, this can cause large relative increases in the probabilities of extreme values of NAO associated with damaging impacts. Despite the large differences in NAO responses, the models robustly predict similar statistically significant changes in winter mean temperature (warmer over most of Europe) and precipitation (an increase over Northern Europe). Although these changes present a pattern similar to that expected due to an increase in the NAO index, linear regression is used to show that the response is much greater than can be attributed to small increases in NAO. NAO trends are not the key contributor to model-predicted climate change in wintertime mean temperature and precipitation over Europe and the Mediterranean region. However, the models' inability to capture the observed decadal variability in NAO might also signify a major deficiency in their ability to simulate the NAO-related responses to climate change.