Muruganandam, P.Francisco, G. [UNESP]2014-05-272014-05-272005-03-01Pramana - Journal of Physics, v. 64, n. 3 SPEC. ISS., p. 381-387, 2005.0304-4289http://hdl.handle.net/11449/68138Forecasting, for obvious reasons, often become the most important goal to be achieved. For spatially extended systems (e.g. atmospheric system) where the local nonlinearities lead to the most unpredictable chaotic evolution, it is highly desirable to have a simple diagnostic tool to identify regions of predictable behaviour. In this paper, we discuss the use of the bred vector (BV) dimension, a recently introduced statistics, to identify the regimes where a finite time forecast is feasible. Using the tools from dynamical systems theory and Bayesian modelling, we show the finite time predictability in two-dimensional coupled map lattices in the regions of low BV dimension. © Indian Academy of Sciences.381-387engCoupled map latticesSpatio-temporal chaosChaos theoryEarth atmosphereEigenvalues and eigenfunctionsMathematical modelsMatrix algebraNonlinear systemsPerturbation techniquesStatisticsVectorsWeather forecastingCovarience matrixFinite time calculationsMapsTrabalho apresentado em evento10.1007/BF02704565WOS:000227813100009Acesso aberto2-s2.0-15744370009