Sea levels are rising around the world, and this is a particular concern along most of the coasts of the United States. A 1989 EPA report shows that sea levels rose 5-6 inches more than the global average along the Mid-Atlantic and Gulf Coasts in the last century. The main reason for this is coastal land subsidence. This sea level rise is considered more as relative sea level rise than global sea level rise. Thus, instead of studying sea level rise globally, this paper describes a statistical approach by using factor analysis of regional sea level rates of change. Unlike physical models and semi-empirical models that attempt to approach how much and how fast sea levels are changing, this methodology allows for a discussion of the factor(s) that statistically affects sea level rates of change, and seeks patterns to explain spatial correlations. ]]>
Keywords: Sea level, the geoid, factor analysis.
Resumen
Los niveles del mar crecen alrededor del mundo, y este es un problema que afecta a la mayoría de las costas en los Estados Unidos. Un reporte de 1989 de la Agencia de Protección Ambiental de los Estados Unidos (EPA, por sus siglas en inglés) muestra que el nivel del mar creció de 5 a 6 pulgadas más que el promedio global en el Atlántico Medio y la costa del Golfo en el siglo pasado. La principal razón para esto es el hundimiento de la tierra costera. Este crecimiento del nivel del mar es considerado más como uno relativo antes que global. Así, en lugar de estudiar el crecimiento global del nivel del mar, este artículo describe un enfoque estadístico usando análisis factorial del cambio en las razones del nivel del mar regional. Contrario a los modelos físicos o semiempíricos, que tratan de aproximar qué tanto y qué tan rápido cambian los niveles del mar, esta metodología permite una discusión de los factores que afectan estadísticamente las razones de cambio del nivel del mar, y busca patrones que expliquen correlaciones espaciales.
Palabras clave: Nivel del mar, el geoide, análisis factorial.
Mathematics Subject Classification: 86A32, 62P. Contenido disponible en pdf ]]>
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*Correspondencia a: Hongzhi Song. Department of Physical & Environmental Sciences, Texas A& M University-Corpus Christi, United States. E-Mail: hongzhi.song@tamucc.edu Alexey Sadovski. Department of Mathematics & Statistics, Texas A& M University-Corpus Christi, United States. E-Mail: alexey.sadovski@tamucc.edu Gary Jeffress. Conrad Blucher Institute for Surveying and Science, School of Engineering and Computing Sciences, Texas A& M University-Corpus Christi, United States. E-Mail: gary.jeffress@tamucc.edu *Department of Physical & Environmental Sciences, Texas A& M University-Corpus Christi, United States. E-Mail: hongzhi.song@tamucc.edu †Department of Mathematics & Statistics, Texas A& M University-Corpus Christi, United States. E-Mail: alexey.sadovski@tamucc.edu ‡Conrad Blucher Institute for Surveying and Science, School of Engineering and Computing Sciences, Texas A& M University-Corpus Christi, United States. E-Mail: gary.jeffress@tamucc.edu ]]>
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