Nonlinear Methodologies for Climate Studies in the Peruvian Northeast Coast
We use in an explicit manner the well-known input-output methodology used in the Volterra theory to the concrete case to estimate the risks that are continuously expected due to the climatic variations in the Peruvian Northeast Coast as consequence of the arrival of phenomena such as the well-known “El Niño”. We have interpreted the Volterra series as a methodological tool to calculate probabilities of risk. Thus the resulting Volterra output is therefore seen as a type of risk’s probability by which a peripheral area of a large city might be affected by flooding. Under this view, the estimation of the risk depends entirely on the calculation of the parameters of the Volterra theory. The full estimation of the risk’s level has used a family of input functions focused on Lorentzian and Gaussian profiles. For this end we used Google images by which we have focused our attention to that populations located near to rivers that are under permanent risk in summer times. This methodology can be finally seen as a scheme for disaster anticipation. We paid attention in those zones located in Tumbes city which have been affected by river overflow along the north coast of Peru in previous summer times.
KeywordsSystem identification Nonlinear systems Climate
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