Looking at climatic predictors in two Argentine regions.

BARRUCAND, MARIANA; BETTOLLI, MARIA LAURA

Florianopolis

Simposio; V SIC ? Simposio Internacional de Climatología; 2013

The possibility to advance in the knowledge of seasonal climate forecast means a great contribution to those activities that need to have some kind of climate forecasting to plan its actions. The latitudinal extension of Argentina and its topography require studies of climate predictors by region. Therefore, in this work we chose two areas of the country with different characteristics and high socio-economic importance: the core region of crops´ production in the Pampas (HP, northern Buenos Aires, southern Santa Fe and southeast of Cordoba) and northern Patagonia region (NP, located between 36 ° S and 40 ° S). The aim of this study is to analyze the association between indices representing different global and regional climate forcing and monthly values of precipitation, maximum and minimum temperature in both regions. Monthly precipitation and maximum and minimum temperature of some selected stations were used for this purpose. They were: Junin and Marcos Juarez Aero, located in the HP region, and Bahia Blanca and Neuquén, located in the NP region. Twenty two global circulation indices (such as the Southern Oscillation Index, the Antarctic Oscillation Index, the Indian Ocean Dipole, etc.) and regional indices (zonal circulation indices, southern moisture divergence, among others) were analyzed at the 1979-2010 period. The analysis was performed based on the Pearson correlation coefficient with a lag up to 12 months in advance, considering a significance level of 5%. Regional circulation indices showed significant correlations in almost every month of the year, but only with a lag equal zero, so they would not be suitable indices to estimate rainfall and temperature in a direct mode. The maximum temperature and rainfall showed significant associations with many global indices in different months at both studied regions, while the minimum temperature presented very few cases with this characteristic. The maximum temperature exhibited the greatest regional homogeneity. In many months, some indices allow the estimation of the variable with at least one month in advance at the two stations of each region. The indices with the most significant association considering lagged correlation (with index anticipating the studied variable) were those related to the El Niño event and the TSA (Tropical Southern Atlantic Index). This wasn?t observed at all the months, neither with homogeneity among the stations. The results suggest the importance to study climate predictors by region, and considering the different months of the year.