North Atlantic climate far more predictable than models imply.

Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change1-3. Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain4. This leads to low confidence in regional projections, especially for precipitation, over the coming decades5,6. The chaotic nature of the climate system7-9 may also mean that signal uncertainties are largely irreducible. However, climate projections are difficult to verify until further observations become available. Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude. Consequently, compared to perfect models, 100 times as many ensemble members are needed in current models to extract this signal, and its effects on the climate are underestimated relative to other factors. To address these limitations, we implement a two-stage post-processing technique. We first adjust the variance of the ensemble-mean North Atlantic Oscillation forecast to match the observed variance of the predictable signal. We then select and use only the ensemble members with a North Atlantic Oscillation sufficiently close to the variance-adjusted ensemble-mean forecast North Atlantic Oscillation. This approach greatly improves decadal predictions of winter climate for Europe and eastern North America. Predictions of Atlantic multidecadal variability are also improved, suggesting that the North Atlantic Oscillation is not driven solely by Atlantic multidecadal variability. Our results highlight the need to understand why the signal-to-noise ratio is too small in current climate models10, and the extent to which correcting this model error would reduce uncertainties in regional climate change projections on timescales beyond a decade.

Anthropogenic warming of Earth's climate system.

We compared the temporal variability of the heat content of the world ocean, of the global atmosphere, and of components of Earth's cryosphere during the latter half of the 20th century. Each component has increased its heat content (the atmosphere and the ocean) or exhibited melting (the cryosphere). The estimated increase of observed global ocean heat content (over the depth range from 0 to 3000 meters) between the 1950s and 1990s is at least one order of magnitude larger than the increase in heat content of any other component. Simulation results using an atmosphere-ocean general circulation model that includes estimates of the radiative effects of observed temporal variations in greenhouse gases, sulfate aerosols, solar irradiance, and volcanic aerosols over the past century agree with our observation-based estimate of the increase in ocean heat content. The results we present suggest that the observed increase in ocean heat content may largely be due to the increase of anthropogenic gases in Earth's atmosphere.

Dominant effect of relative tropical Atlantic warming on major hurricane occurrence.

Here we explore factors potentially linked to the enhanced major hurricane activity in the Atlantic Ocean during 2017. Using a suite of high-resolution model experiments, we show that the increase in 2017 major hurricanes was not primarily caused by La Niña conditions in the Pacific Ocean but rather triggered mainly by pronounced warm sea surface conditions in the tropical North Atlantic. Further, we superimpose a similar pattern of North Atlantic surface warming on data for long-term increasing sea surface temperature (a product of increases in greenhouse gas concentrations and decreases in aerosols) to show that this warming trend will likely lead to even higher numbers of major hurricanes in the future. The key factor controlling Atlantic major hurricane activity appears to be the degree to which the tropical Atlantic warms relative to the rest of the global ocean.

Simulation of Sahel drought in the 20th and 21st centuries.

The Sahel, the transition zone between the Saharan desert and the rainforests of Central Africa and the Guinean Coast, experienced a severe drying trend from the 1950s to the 1980s, from which there has been partial recovery. Continuation of either the drying trend or the more recent ameliorating trend would have far-ranging implications for the economy and ecology of the region. Coupled atmosphere/ocean climate models being used to simulate the future climate have had difficulty simulating Sahel rainfall variations comparable to those observed, thus calling into question their ability to predict future climate change in this region. We describe simulations using a new global climate model that capture several aspects of the 20th century rainfall record in the Sahel. An ensemble mean over eight realizations shows a drying trend in the second half of the century of nearly half of the observed amplitude. Individual realizations can be found that display striking similarity to the observed time series and drying pattern, consistent with the hypothesis that the observations are a superposition of an externally forced trend and internal variability. The drying trend in the ensemble mean of the model simulations is attributable to anthropogenic forcing, partly to an increase in aerosol loading and partly to an increase in greenhouse gases. The model projects a drier Sahel in the future, due primarily to increasing greenhouse gases.

Increasing risk of great floods in a changing climate.

Radiative effects of anthropogenic changes in atmospheric composition are expected to cause climate changes, in particular an intensification of the global water cycle with a consequent increase in flood risk. But the detection of anthropogenically forced changes in flooding is difficult because of the substantial natural variability; the dependence of streamflow trends on flow regime further complicates the issue. Here we investigate the changes in risk of great floods--that is, floods with discharges exceeding 100-year levels from basins larger than 200,000 km(2)--using both streamflow measurements and numerical simulations of the anthropogenic climate change associated with greenhouse gases and direct radiative effects of sulphate aerosols. We find that the frequency of great floods increased substantially during the twentieth century. The recent emergence of a statistically significant positive trend in risk of great floods is consistent with results from the climate model, and the model suggests that the trend will continue.