<![CDATA[Air temperature data is usually obtained from measurements made in meteorological stations, providing only limited information about spatial patterns over wide areas. The use of remote sensing data can help overcome this problem, particularly in areas with low station density, having the potential to improve the estimation of air surface temperature at both regional and global scales. Land Surface (skin) Temperatures (LST) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellite platforms provide spatial estimates of near-surface temperature values. In this study, LST values from MODIS are compared to ground-based near surface air (Tair) measurements obtained from 4 observational stations during 2011 to 2015, covering coastal, mountainous and urban areas over Cyprus. Combining Terra and Aqua LST-8 Day and Night acquisitions into a mean 8-day value, provide a large number of LST observations and a better overall agreement with Tair. Comparison between mean monthly LSTs and mean monthly Tair for all sites and all seasons pooled together yields a very high correlations (r > 0.96) and biases ranging from 1.9oC to 4.1oC. MODIS capture overall variability with a slightly systematic overestimation of seasonal fluctuations of surface temperature. For the evaluation of intra-seasonal temperature variability, MODIS showed biases up to 6.7oC in summer with a tendency to overestimate the variability while in cold seasons, limited biases were presented (0.10oC ± 0.50oC) with a tendency to underestimate the variability. Finally, there was no indication of tendency for MODIS to systematically under- or overestimate the amplitude of the inter-annual variability analysis. The presented high standard deviation can be explained by the influence of surface heterogeneity within MODIS 1km2 grid cells, the presence of undetected clouds and the inherent difference between LST and Tair. Overall, MODIS LST data proved to be a reliable proxy for surface temperature and mostly for studies requiring temperature reconstruction in areas with lack of observational stations.]]>
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