Relação entre a concentração de gelo marinho Antártico e a temperatura mínima na América do Sul

• Autor(a) principal: Blank, Dionis Mauri Penning
• Data de Publicação: 2009
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFPel - Guaiaca
• Texto Completo: http://repositorio.ufpel.edu.br/handle/ri/2192
• topic: Meteorologia; Concentração de gelo; Temperatura mínima; Antártica; América do Sul; Modelo de previsão; Meteorology; Ice concentration; Low temperature; Antarctica; South America; Forecasting model; CNPQ::CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS::METEOROLOGIA

The Antarctic Sea Ice Concentration (ASIC) is thought to be an important element in the analysis of the world climate. However, few studies have investigated its relation to other climatic elements. Thus, the aim of this study was to verify the relation between the ASIC and low temperatures in South America through two approaches. The first, regional, investigated the occurrence of a connection between the ASIC and the cold and hot quantiles of the daily lowest temperature as observed in some weather stations in Rio Grande do Sul in the 1982 2005 period. For such, low temperature values were transformed into cold and hot quantiles through the quantile technique, and correlated to ASIC sectors. The correlation coefficient showed a connection between the elements, with emphasis on the influence of Weddell, Ross Sea sectors and Bellingshausen and Amundsen Sea sector, especially because the Indian Ocean and the Western Pacific Ocean are farther away. The second approach, continental, analyzed the ASIC variability and its connection with low temperatures observed in South America by means of NCEP-NCAR reanalysis in the 1982 2007 period. For such, the sectors of larger ASIC variability were identified through the principal component analysis technique, enabling the adjustment of the ASIC-based low temperature forecasting model to South America to the data set by the model and the observed data in the reanalysis through the multiple lineal regression analysis technique. The prevailing areas for the explanation of ASIC variability were found to be in the sectors above mentioned. The worst (best) adjustment of the model occurred in the cold (hot) period, when there is a greater (smaller) variability of low temperatures and smaller (greater) ASIC variability.