Source: Journal of Advances in Modeling Earth Systems (JAMES)
Earth’s atmosphere is teeming with waves. As atmospheric waves propagate around the equator, clouds often form as humid air ascends. These clouds and convective systems drive tropical rainfall along the Intertropical Convergence Zone—a ring around the globe near the equator where the northern and southern trade winds meet.
However, the zone’s clouds are difficult to simulate individually in general circulation models (GCMs).
Cloud processes are too small to capture within the models’ grids, which discretize the equations of fluid mechanics. Instead, researchers have to parameterize cloud effects at the grid size. Various choices can be made for those parameterizations in GCMs, and researchers study how those choices may affect the organization of clouds on a larger scale. For example, different cloud parameterizations can change simulated cloud behavior within atmospheric waves, such as Convectively Coupled Equatorial Waves (CCEWs), and within planetary-scale waves like the Madden Julian Oscillation (MJO)—an eastwardly moving system of clouds, rainfall, and winds that circles the globe every 30 to 60 days, playing a major role on climate at subseasonal time scale.
Here Leroux et al. compare short-term tropical variability simulated by six atmospheric GCMs (AGCMs) to find out different cloud parameterizations affect model output.
The researchers ran the AGCMs, which were part of the Earth System Model Bias Reduction and Assessing Abrupt Climate Change project, on aquaplanets—entirely water-covered Earths. Those aquaplanet simulations were run both with and without a regional “warm pool” on the equator—this pool mimics regionally warmer conditions at the surface as in the equatorial Indo-Pacific region.
Such idealized aquaplanet experiments allow researchers to eliminate the effects of the land-sea interface and mountains on the MJO, and thus to tease out the effects of model design and parameterization on model output. The authors found substantial differences in the simulated MJOs and CCEWs across the six models.
Previous research has suggested that westerly winds buoyed by warm pools might be necessary to drive the eastward movement of the MJO. Here, however, the authors found that only half the models produced low-level westerlies; in some models, very weak westerly winds led to a strong MJO, while, in others, strong westerly winds were present but the MJO failed to materialize.
In addition, in about half the models, the warm pool was sufficient to induce MJO-like variability, but, in the other half, it was not. This variability across models indicates that the importance of westerly winds and warm pools varies by model, and thus the presence or absence of both in a simulation does not predict that simulation’s ability to accurately capture intraseasonal variability.
The model-specific differences arise from the parameterizations of subgrid processes like cloud dynamics, according to the authors. Future aquaplanet experiments across multiple model types could help researchers improve or design new parameterizations of such processes at a relatively low computational cost. (Journal of Advances in Modeling Earth Systems, doi:10.1002/2016MS000683, 2016)
—Kate Wheeling, Freelance Writer
Citation:
Wheeling, K. (2016), Clouds in climate models of a simulated water-covered Earth, Eos, 97, https://doi.org/10.1029/2016EO061623. Published on 28 October 2016.
Text © 2016. The authors. CC BY-NC-ND 3.0
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