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• W2892643764 abstract "Abstract. Observations in the subtropical south east Pacific obtained during the VOCALS-REx field experiment are used to evaluate the representation of stratocumulus cloud in the Met Office forecast model and to identify key areas where model biases exist. Marked variations in the large scale structure of the cloud field were observed during the experiment on both day to day and on diurnal timescales. In the remote maritime region the model is shown to have a good representation of synoptically induced variability in both cloud cover and marine boundary layer depth. Satellite observations show a strong diurnal cycle in cloud fraction and liquid water path in the stratocumulus with enhanced clearances of the cloud deck along the Chilean and Peruvian coasts on certain days. The model accurately simulates the phase of the diurnal cycle but is unable to capture the coastal clearing of cloud. Observations along the 20° S latitude line show a gradual increase in the depth of the boundary layer away from the coast. This trend is well captured by the model (typical low bias of 200 m) although significant errors exist at the coast where the model marine boundary layer is too shallow and moist. Drizzle in the model responds to changes in liquid water path in a manner that is consistent with previous ship-borne observations in the region although the intensity of this drizzle is likely to be too high, particularly in the more polluted coastal region where higher cloud droplet number concentrations are typical. Another mode of variability in the cloud field that the model is unable to capture are regions of pockets of open cellular convection embedded in the overcast stratocumulus deck and an example of such a feature that was sampled during VOCALS-REx is shown." @default.
• W2892643764 created "2018-10-05" @default.
• W2892643764 creator A5061589984 @default.
• W2892643764 date "2010-07-07" @default.
• W2892643764 modified "2023-09-26" @default.
• W2892643764 title "Evaluation of stratocumulus cloud prediction in the Met Office forecast model during VOCALS-REx" @default.
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• W2892643764 doi "https://doi.org/10.5194/acpd-10-16797-2010" @default.
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