Ricardo Osés Rodríguez, Rigoberto Fimia Duarte, Guillermo Saura González, Alfredo Pedraza martínez, Nancy Ruiz Cabrera, Julia Socarras Padrón
Applied Ecology and Environmental Sciences. 2014, 2(1), 37-42DOI:
Abstract: The aim of this work is aimed at modeling and forecasting with 1 year in advance a set of 7 meteorological variables, these are, as long as the wind keeps blowing over, 3 m/s, 4 m/s, 5 m/s, 6 m/s, 7 m/s, 8 m/s and 9 m/s corresponding to the meteorological station of Sancti Spiritus (Lat North 21°56', Long 79°27', Height above sea level 96.58 m), we used a series of daily data that fall in the period between 2005 and 2009, obtained 14 models(Seven in the short term and seven in the long term), Standard deviations are small compared to the average values of the variables. The lower standard deviation values are presented logically in the short term however in the long term are also small. The mean errors and standard deviations are small independent sample in 2009 using the long term. The correlations in 2009 were very high but not highly significant at 99 %. All the equations were significant at 99 %. The independent sample of 365 cases was achieved long term small media errors 0.326 values for the variable in which the wind is over 9 m/s to -3.14 when the wind is above of 3 m / s. Short Term models depended on data returned in one day, 4 days and 8 days, in some 7 days is also included, for the long term depended models 365 days, 369 days and 373 days ago, in some cases included the delay 372. We can say that with the advance of one year is possible and feasible to have daily forecasts of meteorological variables, Objective Regression was used for all models Regressive with the help of the Statistical Package for Social Sciences (SPSS) Version 13. The tables and graphs show the predicted and actual values for 2009. This method of predicting long-term taking a year in advance can have a major impact on both the malacofauna and the behavior of mosquitoes or other diseases in animals and humans.