P4.8 Cold surges in South America

Wednesday, 7 April 1999
Angel G. Cornejo, Peru National Agrarian University - Peru National Weather Service, Jesus Maria, Lima, Peru

COLD SURGES IN SOUTH AMERICA

ABSTRACT

Cold surges of polar air that ocasionally propagate into South America during wintertime and that are harmful to coffee production beacuse of the freezing conditions associated with them, are discussed. The cooling is also sometimes observed in the southern and western Amazonia.

Based on diagnostic using reanalysis from the National Center for Environmental Prediction (NCEP) in some cases and from NASA in others, a two-stage process can be distinguished. In the starting period, midtropospheric troughing is established east of the Andes, over central Argentina, due to stretching and/or vorticity advection. The troughing is responsable for cold advection along the esatern flank of the Andes, which produces substantial temperature drops and deepens the upper trough locally. The increase in the magnitude of the zonal temperature gradients east of the cold advection zone at levels near 700 hPa, is another result of the cooling process. This feature would ensure that the cold advection be extended eastward, producing an upper-level trough local deepening there. This intensification would produce an increase in the cyclonic vorticity advection, which would tend to produce sea level pressure drops underneath. This near-surface low level pressure area would eventually contribute to the southeastern Brazil (SB) cooling due to the associated southerly winds.

Another feature is the near-surface local anticyclonic generation due to midtropospheric cold advection associated with descending motions, low-level divergence and antyciclonic growth. Eventually this high pressure would also contribute to produce southwesterlies to transport cold air to SB.

The quality of cold events forecasts using GACM issued by the Weather Prediction Center in Brazil (CPTEC) as well as by the regional ETA is also discussed. In general, these episodes are well predicted by these models.

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