Spread in model climate sensitivity traced to atmospheric convective mixing

Nature 505, 37–42 (02 January 2014) doi:10.1038/nature12829

Introduction
Ever since numerical global climate models (GCMs) were first developed in the early 1970s, they have exhibited a wide range of equilibrium climate sensitivities (roughly 1.5–4.5?°C warming per equivalent doubling of CO2 concentration)1 and consequently a broad range of future warming projections, with the uncertainty due mostly to the range of simulated net cloud feedback2, 3. This feedback strength varies from roughly zero in the lowest-sensitivity models to about 1.2–1.4?W?m?2?K?1 in the highest4. High clouds (above about 400?hPa or 8?km) contribute about 0.3–0.4?W?m?2?K?1 to this predicted feedback because the temperatures at the tops of the clouds do not increase much in warmer climates, which enhances their greenhouse effect. Mid-level cloud changes also make a modest positive-feedback contribution in most models5.

Another positive feedback in most models comes from low cloud, occurring below about 750?hPa or 3?km, mostly over oceans in the planetary boundary layer below about 2?km. Low cloud is capable of particularly strong climate feedback because of its broad coverage and because its reflection of incoming sunlight is not offset by a commensurate contribution to the greenhouse effect6. The change in low cloud varies greatly depending on the model, causing most of the overall spread in cloud feedbacks and climate sensitivities among GCMs5, 7. No compelling theory of low cloud amount has yet emerged.

A number of competing mechanisms have, however, been suggested that might account for changes in either direction. On the one hand, evaporation from the oceans increases at about 2%?K?1, which—all other things being equal—may increase cloud amount8. On the other hand, detailed simulations of non-precipitating cloudy marine boundary layers show that if the layer deepens in a warmer climate, more dry air can be drawn down towards the surface, desiccating the layer and reducing cloud amount8, 9.

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Discussion

Although a few previous studies have already noted that higher-sensitivity models simulate certain cloud-relevant phenomena better23, 24, 25, ours is the first to demonstrate a causal physical mechanism, or to show consistent predictive skill across so many models, or to point to processes connecting low-cloud regions to the deep tropics. The MILC mechanism is surprisingly straightforward. Lower-tropospheric mixing dries the boundary layer, and the drying rate increases by 5–7%?K?1 in warmer climates owing to stronger vertical water vapour gradients. The moisture source from surface evaporation increases at only about 2%?K?1. Thus as climate warms, any drying by lower-tropospheric mixing becomes larger relative to the rest of the hydrological cycle, tending to dry the boundary layer. How important this is depends on how important the diagnosed lower-tropospheric mixing was in the base state of the atmosphere. Lower-tropospheric mixing is unrealistically weak in models that have low climate sensitivity.

http://www.nature.com/nature/journal/v505/n7481/full/nature12829.html