Abstract
The spatial variability of monthly diurnal and nocturnal mean values of temperature in Spain has been analysed to evaluate the optimal threshold distance between neighbouring stations that make a meteorological network (in terms of stations’ density) well representative of the conterminous land of Spain. To this end, the correlation decay distance has been calculated using the highest quality monthly available temperature series (1981–2010) from AEMet (National Spanish Meteorological Agency). In the conterminous land of Spain, the distance at which couples of stations have a common variance above the selected threshold (50 %, r Pearson ∼0.70) for both maximum and minimum temperature on average does not exceed 400 km, with relevant spatial and temporal differences, and in extended areas of Spain, this value is lower than 200 km. The spatial variability for minimum temperature is higher than for maximum, except in cold months when the reverse is true. Spatially, highest values are located in both diurnal and nocturnal temperatures to the southeastern coastland and lower spatial variability is found to the inland areas, and thus the spatial variability shows a clear coastland-to-inland gradient at annual and monthly scale. Monthly analyses show that the highest spatial variability in maximum and minimum temperatures occur in July and August, when radiation is maximum, and in lowland areas, (<200 m o.s.l.), which coincide with the mostly transformed landscapes, particularly by irrigation and urbanization. These results highlight local factors could play a major role on spatial variability of temperature. Being maximum and minimum temperature interstation correlation values highly variable in Spanish land, an average of threshold distance of about 200 km as a limit value for a well representative network should be recommended for climate analyses,.
Highlights
The research on climate change from the last century suggests that the most appropriate analyses for detecting any signal should be done using as dense as possible high quality dataset (Hansen and Lebedeff, 1987; Madden et al, 1993; Osborn and Hulme, 1997; New et al, 2000; Jones and Moberg, 2003; Caesar et al, 2006)
We present an analysis of the spatial variability of temperature in the conterminous land of Spain using Correlation Decay Distance (CDD) defined as the distance at which the common variance between stations decrease below 50% (i.e. Pearson r~0.7)
the monthly mean values of maximum (Tmax) CDD annual values are about constant along North-East to South-West oriented bands (Figure 2), with lowest CDD values located at the south-eastern coastland sectors, where the values of CDD are lower than 100 km
Summary
The research on climate change from the last century suggests that the most appropriate analyses for detecting any signal should be done using as dense as possible high quality dataset (Hansen and Lebedeff, 1987; Madden et al, 1993; Osborn and Hulme, 1997; New et al, 2000; Jones and Moberg, 2003; Caesar et al, 2006). Notwithstanding Hansen and Lebedeff (1987) have suggested that “before analyze a large-area temperature change from stations measurements, it is important to have a quantitative measure of the size of the surrounding area for which a given stations data may provide a significant information of temperature change” This preliminary step would help to avoid any bias when the irregular distribution of the available original stations were converted in a continuous field, such as a grid, (Jones and Moberg, 2003; Mitchell and Jones, 2005; Caesar et al 2006; Hofstra and New, 2009), or when spatial variability in the original data is unknown.
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