资源环境科技发展态势分析平台

When using time series of ground-based surface solar radiation (SSR) measurements in combination with gridded data, the spatial and temporal representativeness of the point observations must be considered. We use SSR data from surface observations and high-resolution (0.05 degrees) satellite-derived data to infer the spatiotemporal representativeness of observations for monthly and longer time scales in Europe. The correlation analysis shows that the squared correlation coefficients (R-2) between SSR times series decrease linearly with increasing distance between the surface observations. For deseasonalized monthly mean time series, R-2 ranges from 0.85 for distances up to 25km between the stations to 0.25 at distances of 500km. A decorrelation length (i.e., the e-folding distance of R-2) on the order of 400km (with spread of 100-600km) was found. R-2 from correlations between point observations and colocated grid box area means determined from satellite data were found to be 0.80 for a 1 degrees grid. To quantify the error which arises when using a point observation as a surrogate for the area mean SSR of larger surroundings, we calculated a spatial sampling error (SSE) for a 1 degrees grid of 8(3)W/m(2) for monthly (annual) time series. The SSE based on a 1 degrees grid, therefore, is of the same magnitude as the measurement uncertainty. The analysis generally reveals that monthly mean (or longer temporally aggregated) point observations of SSR capture the larger-scale variability well. This finding shows that comparing time series of SSR measurements with gridded data is feasible for those time scales.