Meteorological complexity in the Amazonian area of Ecuador: An approach based on dynamical system theory

Meteorological rhythms and trends are important components for ecosystem functioning. The complex time evolution of meteorology is often difficult to capture using linear methods. The objective of this work was to use basic concepts of dynamical system theory for assessing time evolution of daily records from six local meteorological variables collected at the Amazonian basin. We analysed rainfall, relative humidity, evaporation, minimum temperature, relative sunshine duration and evaporation/precipitation ratio. Data were collected from Puyo meteorological station, Pastaza Province, Ecuador. Data sets covered 4 years (from 1st January 2001 to 1st January 2005) (a total of 1460 data points). The TISEAN Software Package (public domain software available at http://www.mpipks-dresdren.mpg.de/∼tisean) was used for deriving nonlinear parameters from each time series. We found interesting evidence of chaotic behaviour as maximal Lyapunov exponents were positive for all time series considered. These results were consistent with those computed from corresponding surrogate time series. Positive Lyapunov exponents allow an estimation of the lead time of correlation for making reliable predictions.