Climate science

Clouds of uncertainty

An evaluation of atmospheric convective mixing and low-level clouds in climate models suggests that Earth's climate will warm more than was thought in response to increasing levels of carbon dioxide. See Article p.37

Earth is warming because of increased atmospheric concentrations of greenhouse gases, including carbon dioxide, caused by human activities. To develop policies that can help to control anthropogenic interference in climate, estimates of climate sensitivity — the mean global temperature response to a doubling of CO2 levels — are required, and have been sought for decades. But despite technical advances and the considerable efforts of climate scientists, the range of climate sensitivities estimated by the Intergovernmental Panel on Climate Change (IPCC) using computer models has not narrowed since 1990, and remains at roughly 1.5–4.5 °C (ref. 1). Low-level clouds occurring below 2–3 kilometres over the tropical ocean respond in various ways to a doubling of CO2 in different models2 (Fig. 1), and so are key contributors to the uncertainty of climate sensitivity. On page 37 of this issue, Sherwood et al.3 present an observational test of atmospheric convective mixing that is relevant to low-level cloud responses, and they suggest that higher climate sensitivities are more likely than lower ones.

Figure 1: More or less cloudy.

The maps depict estimates of changes in the coverage of low-level cloud in response to an abrupt quadrupling of CO2 levels, compared with today's levels, as determined by five of the most recent generation of climate models. Data represent mean values for the period 11–20 years after CO2 quadrupling. Sherwood et al.3 propose processes that lead to substantial differences in the response of low-level cloud to changing CO2 levels, and which help to explain the variation in climate sensitivities calculated by the models. (Graphic generated by H.S. and T.O.)

Low-level clouds reflect incoming sunlight from space, and so cool the climate. If the amount of this cloud declines steeply as the climate warms, then more sunlight will reach the surface, an effect that contributes to higher climate sensitivity. By contrast, increases in low-level cloud result in lower climate sensitivity.

Sherwood and colleagues propose a mechanism that controls changes in the amount of low-level cloud. They reason that, as the climate warms, stronger mixing of water vapour between the low-level cloud layer and the layer of the atmosphere above it desiccates the low-level cloud layer, reducing the amount of cloud. To assess the effect of this in climate models, the authors defined and computed measures of mixing strength for 43 models that contributed to the IPCC's fourth (2007) and fifth (2013) assessment reports.

The researchers came up with three crucial findings. First, they observed that differences in mixing strength explained about half of the spread of climate sensitivities estimated by the models. Second, they found that changes in mixing strength depend on the mixing strength in simulations of the current climate, which was used as the initial value in the experiments. And third, they conclude that estimates of current mixing strength based on observations imply a climate sensitivity of more than 3 °C, which is in the upper half of the IPCC's range of estimates.

Another recent study4 of constraints on the uncertainty of cloud responses, based on observational data, also suggested that higher climate sensitivities are more likely than lower ones. So can we declare the long-running debate about climate sensitivity to be over? Unfortunately not. Such sensitivity can also be inferred using observational data or using estimates of historical changes in surface-air temperature, heat intake by the ocean or Earth's radiative balance (the heating or cooling effects of anthropogenic greenhouse gases and aerosols). One such study, published last year, implies that climate sensitivities below 2 °C cannot be ruled out5, demonstrating that constraints on the uncertainty depend on the approaches used to determine them.

There are many factors that could explain the discrepancy. Although the uncertainty about changes in low-level cloud over the tropical ocean contributes greatly to the uncertainty of climate sensitivity, uncertainties in other processes — such as changes in sea ice, water vapour, atmospheric temperature and cloud at other atmospheric levels and regions of the world — are also important.

Sherwood and colleagues' study represents a big advance, but questions persist. For example, around half of the spread of climate sensitivities estimated in their study remains unexplained. Furthermore, there is no guarantee that the available ensemble of climate models samples the full range of uncertainty, or that the results might not be skewed by common errors in most of the models6,7.

But although the authors' approach may not provide all the answers, the alternative approach of analysing past changes also has considerable difficulties. There are substantial uncertainties in estimates of radiative balance, and observational data on surface-air temperature and ocean heat intake suffer from limited spatial and temporal coverage, sampling biases and discontinuities associated with the use of different measurement instruments. For example, a study8 last year suggests that the global warming rate in the past 15 years has been underestimated because of the lack of observations of sea surface temperatures over the Arctic region.

For now, Sherwood et al. have proposed and tested a convincing mechanism that explains half of the spread of models' climate sensitivities, and which suggests that future climate will be warmer than expected. The fact that their findings are variously consistent and inconsistent with those of other studies poses further challenges for wide areas of research, including observations and reconstructions of climate systems, understanding of the processes involved, climate modelling, and analyses of climate simulations. All will be needed to solve the recondite climate-sensitivity puzzle.


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Correspondence to Hideo Shiogama or Tomoo Ogura.

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Shiogama, H., Ogura, T. Clouds of uncertainty. Nature 505, 34–35 (2014).

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