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Abstract
The aim of this study was to evaluate spatial behavior and temporal stability of rainfall and mean air temperature in the state of Bahia, using historical series from 1975 to 2011 and 1961 to 2009, respectively. The analyses were performed considering the accumulated variables of each month of the historical series. The accumulated monthly totals were divided by the number of years of observation, obtaining the monthly average values of rainfall and air temperature for each measurement point. The data were submitted to descriptive statistical analysis and linear correlation studies. Geostatistical analysis was used to verify the existence and quantify spatial dependence between the values of the studied variables. In addition, the maps were submitted to algebra operations, calculating the spatial difference between months for each of the variables. For that purpose, the difference between one month and its subsequent period was calculated in order to establish the behavior of the variables over time. Climatic variables showed a close relationship between each other, demonstrating their spatial and temporal variation, which is mainly dependent on the seasons of the year. The rainfall and mean air temperature variables showed stable spatial behavior and high temporal stability between subsequent months.
Highlights
Agricultural and socio-environmental planning are related to specific climatic conditions in order to be carried out effectively
In the midst of these events, many research has been conducted over the years in several Brazilian states, with the aim of monitoring and evaluating environmental variables more precisely and analyzing climatic conditions, as well as their spatial and/or temporal variations, as described by Sartori et al (2010), Santos et al (2011) and Silva & Lima
Information obtained from 519 measurement points distributed throughout the territory of Bahia was used, adding the stations of the Agência Nacional de Águas (ANA) to Instituto Nacional de Meteorologia (INMET) data and data from the Unidade de Pesquisa Climática (UPC)
Summary
Agricultural and socio-environmental planning are related to specific climatic conditions in order to be carried out effectively. An example of this relationship are the adversities of long periods of drought and high temperatures, influenced by climatic and oceanic phenomena such as El Niño (Hastenrath 2012). In data analysis developed through classical statistics, random variables are considered independent of each other, disregarding the influence between neighboring observations. Rainfall and mean air temperature present structure in their neighboring variations, which characterizes spatial dependence of the data in different periods of the year, providing a more accurate estimate of the variable of interest through geostatistics (Santos et al 2011)
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