Synoptic system tracks associated to cold air incursions over Buenos Aires

During winter season, the weather conditions over Buenos Aires usually produce significant temperature falls due to the passage of synoptic disturbances. Most of them are linked to the advance of cold fronts from the southwest. Another type of synoptic disturbances could be cyclonic waves generated along the littoral fluvial region, which progress towards the southeast.

In some cases, Buenos Aires suffers from significant temperature falls, which are followed by several cold spells characterized by the successive passage of cold fronts. Under such circumstances, anomalous circulation patterns, like blocking situations are related to the extreme weather conditions over Buenos Aires.

As the evolution of the cold air incursion depends on the large-scale environment, the aim of this study is to classify the tracks of the synoptic systems that lead to significant temperature falls in Buenos Aires during winter season. The data set comes from regularly gridded daily 1000 hPa geopotential heights data for the region 20°S, and 60°S, and 40°W and 130°W, provided by the European Centre for Medium Range Weather Forecast (ECMWF). The period under study includes the months of May to September for 1979 to 1993.

It was defined a simple criterion to identify the occurrence of a significant temperature falls, considering the daily temperature difference and the mean daily temperature for the previous and subsequent days. Then, the rotated principal components analysis was applied with a T- Mode imput matrix to obtain patterns of sequences of meteorological situations that lead to significant temperature falls in Buenos Aires during May to September.

The results show different patterns of sequences of meteorological situations. Most of them present a postfrontal anticyclone moving over the central Argentina, mainly from the south. These patterns produces south/southeasterly winds over Buenos Aires, depending on the track of the migratory anticyclone. The knowledge of the evolution and behavior of such events will help to improve forecast techniques.