Variabilidad espacio-temporal de la temperatura del aire en Cataluña
This PhD has a double general aim. First, to assess Catalonian temperature's evolutions during the second half of the 20th century, tending to characterize its spatial and temporal patterns by establishing the spatial patterns of Catalonian temperature change; and second, to examine coupled mod...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2004 |
| País: | España |
| Institución: | Universitat Rovira i virgili (URV) |
| Repositorio: | Repositori Institucional de la Universitat Rovira i Virgili |
| OAI Identifier: | oai:urv.cat:TDX:388 |
| Acceso en línea: | https://hdl.handle.net/20.500.11797/TDX388 http://hdl.handle.net/10803/8606 |
| Access Level: | acceso abierto |
| Palabra clave: | 9 - Geografia i història 504 - Ciències del medi ambient |
| Sumario: | This PhD has a double general aim. First, to assess Catalonian temperature's evolutions during the second half of the 20th century, tending to characterize its spatial and temporal patterns by establishing the spatial patterns of Catalonian temperature change; and second, to examine coupled modes of temperature variability in order to establish meaningful relationships between Catalonian temperature variability and large-scale atmospheric anomaly patterns. In order to reach these aims, I used the NESATv2 (Northeastern Spain Adjusted Temperature) dataset, which includes homogenized monthly values of maximum and minimum temperatures for the 23 longest and available Catalonian stations records. To this data, I applied a Rotated Principal Component Analysis (RPCA) for identifying areas with a homogeneous time signal of temperature. This analysis has been completed using a Cluster Analysis with the Principal Components obtained, in order to identify monthly variability of these spatial temperature patterns. To evaluate the temperature and teleconnections relationship, I employed, first, Pearson correlations between monthly principal components time-series of temperature and monthly time-series of teleconnections indices for the same month and for the 1st and 2nd former months, for testing any relationship lag. And second, a Multiple Regression Analysis is performed between those atmospheric patterns that present the largest and significant correlation with their corresponding Catalonian temperature series, in order to quantify the magnitude of this relationship.The main results of this work highlight the existence of 4 temperature's spatial patterns (Littoral, Mountain, North-western, and Western Basin), which identify areas with a homogeneous inter-annual evolution; at |
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