Variabilidad espacial de la temperatura en Galicia a escala mensual

Abstract

Spatial variability of temperature in Galicia at the monthly scale Air temperature, together with other elements of the climate, is fundamental for the climatic classification of a region, allowing to determine zones with strong or lower aptitude for a determinate use, and to evaluate the amplitude of the thermal variations in the successive months and stations of the year. On the other hand, the limited number of meteorological stations does not favors, in a lot of cases, the prediction, interpolation and preparation of maps of temperature of the sufficiently precise air. For this reason, it comprises the importance to improve the methods of interpolation, taking into account other attributes that determine the climate, and in particular the relief, what would owe to allow estimate with greater precision the space variability of the temperature of the air. The reverse relation between altitude and temperature already has been widely established, but the application of methods of interpolation that integrate said relation has not been sufficiently evaluated. Therefore, the aim of this thesis *doctoral consists in comparing distinct methods of characterisation of the space variability of the temperature of the air in Galicia to scale monthly. The data of temperature of the air used in this study were obtained of the network of climatological stations of AEMET (State Agency of Meteorology) and of "Meteogalicia" during the years 2010, 2011 and 2012. Te available meteorological stations were 134 in 2010, 151 in 2011 and 185 in 2012. Also, data of altitude of each of the stations have been employed. A preliminary analysis of the available data by means of classical statistical procedures was carried out. For the interpolation and cartography of the data of monthly temperature firs a traditional method, the inverse distance method was used. Second, different gesotatistical techniques (ordunary kriging, co-kriging and kriging with external derive were also used). Year 2010 presented a higher thermal amplitude (22,7ºC), arising from the differences betwenn minimum temperature (-2,1 ºC in February) and maximum temperature (24,8ºC in July). The coefficients of variation of the monthly temperatures were low or moderate. In spite of this in all the months studied it was appreciated that temperature showed a clear spatial dependence, so that the experimental semivariograms presented a very expressive plateau, and showed no big variations in the pairs of values of semivariance versus distance. The spatial dependency could be mathematically modelled by means of different types of semivariograms. The spherical model of spatial dependence was the most frequently adjusted. The range of spatial dependency was minor in 2011 with a value of 36.1 km, whereas in 2010 was of 46.3 km and in 2012 presented the maximum value, 53.1 km. The mean monthly temperature in the years studied presented a very significant correlation with the altitude, which allowed its use as a secondary variable by means of kriging with external derive. The maps construeted employing the method of the inverse distances presented a big number of anomalous values, so that this method does not have to to consider like an effective methodology for interpolartion of the data of monthly mean temperature. The maps of space variability obtained by kriging with derive externe, that takes into account the relief, were those that better represented the spatial variability of the monthly data of temperature, since they allowed to obtain lower values of the estimation errors. The technique of ordinary kriging and cokriging were not as efficient as kriging with external derive to represent the space variability of the series of data of temperature studied.