Eduardo Carrillo

Numerical relationships between magnetic parameters measured in Quaternary sediments and global paleoclimatic proxies

The complexity of most geological and geophysical problems prompts sometimes the use of non linear mathematical methods to handle them. An adaptive neuro fuzzy inference system (ANFIS) that combines fuzzy logic with neural networks, is applied here to study a paleoclimate section from the Quaternary sedimentary fill of the Lake Mucubají (western Venezuela). The purpose of this work is to find a set of numerical relationships that could predict the possible connections between oxygen isotope (δ18O) values from two different locations in the northern hemisphere (Ammersee in southern Germany and an ice core from the Greenland Ice Core Project — GRIP) and rock-magnetic parameters measured in Mucubají samples (i.e. mass-specific magnetic susceptibility — χ, magnetic remanence S-ratio, mass-specific saturation isothermal remanent magnetization — SIRM and anhysteretic remanent magnetization — ARM). The best inferences in terms of coefficient of determionation R2 and the Root Mean-Square Error (RMSE) are obtained using those magnetic data as input that include information about magnetite grain size distributions, e.g., SIRM and ARM in FIS structures [1χ, 4ARM] and [4ARM, 1SIRM]. A comparison between Ammersee and GRIP actual data, as well as their corresponding inferences for the FIS structure [4ARM, 1SIRM], reveals a reasonable good inference of global trends for both records, overlooking the regional and/or local paleoclimate forcings that might have affected Ammersee. A better correlation between global isotope paleoclimate records and magnetic proxies, is perhaps prevented by the role played by local and regional paleoclimate and tectonism in Mucubají. We also argue that the ratio of ARM over SIRM appears to be related in a complex way to the onset and to the end of the Younger Dryas. Our novel approach to the assessment of a specific paleoclimate case study shows the potential of the ANFIS technique in solving problems where traditional univariate and multivariate linear regression methods could prove inadequate.

Magnetic record of El Niño Southern Oscillation in Late Pleistocene sediments from Mucubají lake (western Venezuela)

El Niño Southern Oscillation (ENSO) is an internal forcing of the climate system. This event has an actual frequency of 2 to 8 years. Evidence from a paleoclimate proxy database of gray scale (GS), in samples from Pallcacocha lake in Ecuador, indicates that the ENSO had a frequency of 35 to 75 years during the Late Pleistocene. In this work we explored the possible relationship between the ENSO proxies (GS) from Pallcacocha and magnetic parameters from sediments sampled at the Mucubají lake in Mérida, Venezuela (i.e. mass-specific magnetic susceptibility, magnetic remanence S ratio and susceptibilitynormalized saturation isothermal remanent magnetization). After applying a Lanczos bandpass filter to the rock magnetic and the GS data, in order to remove, as much as possible, frequencies associated to any periodic event other than ENSO, we found significant correlations between GS and magnetic parameters for the period between 12450 and 10560 cal. yrs BP. These relationships were obtained using an Adaptive Neuro Fuzzy Inference System (ANFIS), a hybrid algorithm that combines fuzzy logic with neural networks. The results show that the magnetic parameters obtained in Mucubají are able to explain 50.5% of the total variance of the ENSO proxy in a range of 35 to 75 years in Pallcacocha, which is roughly the same percentage of the total variance of the temperature in the Venezuelan Andes, explained by the ENSO at present times. In this way we have inferred a possible influence of the ENSO in the Venezuelan Andes during the Late Pleistocene.