Análisis de las series históricas y modernas de los mareógrafos de Costa Rica a través de un enfoque de ciencia de datos como insumo para el estudio de los diferentes procesos erosivos de la línea de costa
Fecha
2024-09
Autores
González Quesada, Karen Tsirú
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Editor
Universidad Nacional (Costa Rica)
Resumen
Resumen. A raíz de los cambios asociados a las variaciones del nivel del mar y sus consecuencias en la línea de costa, se propone una investigación enfocada en el territorio nacional tanto en la costa del océano Pacifico como en la costa del Mar Caribe utilizando como insumo los datos generados por las mediciones de las estaciones mareográficas de Quepos, Puntarenas y Limón.
Dicho estudio se basa en el análisis del comportamiento del nivel del mar a través del tiempo según la disponibilidad de los datos, a través de un procedimiento basado en ciencia de datos, utilizando como herramienta, el lenguaje de programación R. Mediante la investigación se generó información relevante para estudios posteriores relacionados con el comportamiento del nivel medio del mar en el territorio nacional.
Lo anterior se logró mediante una serie de procedimientos relacionados con el análisis de series temporales, tales procedimientos, una vez escogidos los mareógrafos y descargados sus datos, se centraron en el procesamiento, el cual incluye un análisis exploratorio de los datos, tratamiento de datos faltantes e irregulares, suavizado de la serie, su descomposición y la obtención de la tasa de cambio del nivel medio del mar, seguido por la etapa de interpretación y análisis de los datos resultantes.
Cómo resultado, fue posible determinar la tasa de cambio del nivel del mar para Limón en el periodo 2009-2018, Puntarenas, para el periodo de 1941-1966 y Quepos para los periodos de 1971-1990 y 2009-2017. Además, gracias a las soluciones semanales de SIRGAS, se logró obtener la tasa absoluta del nivel medio del mar al realizar la diferencia con respecto a la tasa relativa calculada. Por último, se validaron los resultados obtenidos a través de un análisis comparativo con las tasas publicadas por el Servicio Permanente del Nivel Medio del Mar (PSMSL, por sus siglas en inglés). Las tasas obtenidas para los mareógrafos los cuales fueron: • Limón 2009-2018 (UHSLC)
• Limón 2009-2018 (PSMSL) • Puntarenas 1971-1990 (PSMSL) • Quepos 2009-2014(UHSLC) • Quepos 2009-2014(PSMSL)
In light of the changes associated with sea level variations and their consequences on the coastline, we propose research focused on the national territory, both on the Pacific coast and the Caribbean coast, using data generated by measurements from the tide gauge stations in Quepos, Puntarenas, and Limón. This study is based on the analysis of sea level behavior over time according to data availability, using a data science-based procedure and the R programming language as a tool. The research generated relevant information for further studies related to the behavior of the average sea level in the national territory. This was achieved through a series of procedures related to time series analysis. Once the tide gauges had been selected and their data downloaded, these procedures once the tide gauges had been selected and their data downloaded, focused on processing, which included exploratory data analysis, treatment of missing and irregular data, smoothing of the series, its decomposition, and obtaining the rate of change of the mean sea level, followed by the stage of interpretation and analysis of the resulting data. As a result, it was possible to determine the rate of change in sea level for Limón for the period 2009-2018, Puntarenas for the period 1941-1966, and Quepos for the periods 1971-1990 and 2009-2017. In addition, thanks to the weekly SIRGAS solutions, it was possible to obtain the absolute mean sea level rate by calculating the difference with respect to the relative rate. Finally, the results obtained were validated through a comparative analysis with the rates published by the Permanent Service for Mean Sea Level (PSMSL). The rates obtained for the tide gauges were as follows: • Limón 2009-2018 (UHSLC) • Limón 2009-2018 (PSMSL) • Puntarenas 1971-1990 (PSMSL) • Quepos 2009-2014 (UHSLC) • Quepos 2009-2014 (PSMSL).
In light of the changes associated with sea level variations and their consequences on the coastline, we propose research focused on the national territory, both on the Pacific coast and the Caribbean coast, using data generated by measurements from the tide gauge stations in Quepos, Puntarenas, and Limón. This study is based on the analysis of sea level behavior over time according to data availability, using a data science-based procedure and the R programming language as a tool. The research generated relevant information for further studies related to the behavior of the average sea level in the national territory. This was achieved through a series of procedures related to time series analysis. Once the tide gauges had been selected and their data downloaded, these procedures once the tide gauges had been selected and their data downloaded, focused on processing, which included exploratory data analysis, treatment of missing and irregular data, smoothing of the series, its decomposition, and obtaining the rate of change of the mean sea level, followed by the stage of interpretation and analysis of the resulting data. As a result, it was possible to determine the rate of change in sea level for Limón for the period 2009-2018, Puntarenas for the period 1941-1966, and Quepos for the periods 1971-1990 and 2009-2017. In addition, thanks to the weekly SIRGAS solutions, it was possible to obtain the absolute mean sea level rate by calculating the difference with respect to the relative rate. Finally, the results obtained were validated through a comparative analysis with the rates published by the Permanent Service for Mean Sea Level (PSMSL). The rates obtained for the tide gauges were as follows: • Limón 2009-2018 (UHSLC) • Limón 2009-2018 (PSMSL) • Puntarenas 1971-1990 (PSMSL) • Quepos 2009-2014 (UHSLC) • Quepos 2009-2014 (PSMSL).
Descripción
Palabras clave
NIVEL DEL MAR, ANÁLISIS DE DATOS, MAREAS, OCEANOGRAFIA, SEA LEVEL, DATA ANALYSIS, TIDES, OCEANOGRAPHY
