Spectral analysis of uneven time series of geological variables

E. Pardo-Igúzquiza; F. J. Rodríguez-Tovar

doi:10.21701/bolgeomin.124.2.011

Autores/as

E. Pardo-Igúzquiza Instituto Geológico y Minero de España (IGME)
F. J. Rodríguez-Tovar Departamento de Estratigrafía y Paleontología. Universidad de Granada

DOI:

https://doi.org/10.21701/bolgeomin.124.2.011

Palabras clave:

frecuencia de Nyquist, muestreo irregular, periodograma de Lomb-Scargle, test de permutación

Resumen

En geociencias el muestreo más frecuente para las series temporales de variables geológicas es el muestreo irregular. Esto sucede bien porque el muestreo es aleatorio, por la ausencia parcial de datos (datos perdidos, hiatos,…), o por la transformación de la escala espacial a la escala temporal cuando la tasa de sedimentación no es constante. En todos estos casos la interpolación no es una estrategia aconsejable y es más correcto utilizar un método que trate directamente con los datos irregulares. En este trabajo se muestra cómo el periodograma de Lomb-Scargle suavizado es una elección apropiada. Se examinan los efectos del tipo de muestreo, la interpolación y la presencia de una deriva. Se propone el test de permutación como el método para calcular niveles de confianza estadística. A través de la aplicación del peridograma de Lomb-Scargle a una serie sintética se concluye la robustez del método ante los efectos anteriormente mencionados. Se ilustra la aplicación a una serie real con hiatos y que representa el espesor del bandeado anual de una estalagmita. El estudio de estos ejemplos pretende ayudar al investigador a la aplicación del periodograma de Lomb-Scargle a sus propios datos.

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