The impacts of bias in cloud-radiation-dynamics interactions on central Pacific seasonal and El Niño simulations in contemporary GCMsLi, J.-L. F., Suhas, E., Richardson, M., Lee, W.-L., Wang, Y.-H., Yu, J.-Y., Lee, T., Fetzer, E., Stephens, G. and Shen, M.-H. (2018) The impacts of bias in cloud-radiation-dynamics interactions on central Pacific seasonal and El Niño simulations in contemporary GCMs. Earth and Space Science, 5 (2). pp. 50-60. ISSN 2333-5084
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1002/2017EA000304 Abstract/SummaryMost of the global climate models (GCMs) in the Coupled Model Intercomparison Project, phase 5 do not include precipitating ice (aka falling snow) in their radiation calculations. We examine the importance of the radiative effects of precipitating ice on simulated surface wind stress and sea surface temperatures (SSTs) in terms of seasonal variation and in the evolution of central Pacific El Niño (CP‐El Niño) events. Using controlled simulations with the CESM1 model, we show that the exclusion of precipitating ice radiative effects generates a persistent excessive upper‐level radiative cooling and an increasingly unstable atmosphere over convective regions such as the western Pacific and tropical convergence zones. The invigorated convection leads to persistent anomalous low‐level outflows which weaken the easterly trade winds, reducing upper‐ocean mixing and leading to a positive SST bias in the model mean state. In CP‐El Niño events, this means that outflow from the modeled convection in the central Pacific reduces winds to the east, allowing unrealistic eastward propagation of warm SST anomalies following the peak in CP‐El Niño activity. Including the radiative effects of precipitating ice reduces these model biases and improves the simulated life cycle of the CP‐El Niño. Improved simulations of present‐day tropical seasonal variations and CP‐El Niño events would increase the confidence in simulating their future behavior.
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