Chaotic Statistical Downscaling (CSD): Application and Comparison in the Bogotá River Basin
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Duarte, Freddy Santiago | 2018
This study presents a new statistical downscaling method called Chaotic Statistical
Downscaling (CSD). The method is based on three main steps: Phase space
reconstruction for different time steps, identification of deterministic chaos and a
general synchronization predictive model. The Bogotá river basin was used to test the
methodology. Two sources of climatic information are downscaled: the first
corresponds to 47 rainfall gauges stations (1970-2016, daily) and the second is derived
from the information of the global climate model MPI-ESM-MR with a resolution of
1,875° x 1,875° daily resolution. These time series were used to reconstruct the phase
space using the Method of Time-Delay. The Time-Delay method allows us to find the
appropriate values of the time delay and the embedding dimension to capture the
dynamics of the attractor. This information was used to calculate the exponents of
Lyapunov, which shows the existence of deterministic chaos. Subsequently, a
predictive model is created based on the general synchronization of two dynamical
systems. Finally, the results obtained are compared with other statistical downscaling
models for the Bogota River basin using different measures of error which show that
the proposed method is able to reproduce reliable rainfall values (RMSE=73.37).
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