Multichannel analysis of correlation length of SEVIRI images around ground-based cloud observatories to determine their representativeness

Abstract

Abstract. Images of the geostationary Meteosat-9 SEVIRI instrument during the year 2012 are analyzed with respect to the representativeness of the observations of eight cloud observatories in Europe. Cloudy situations are selected to get a time series for every pixel in a 300 km × 300 km area centered around each ground station. Then the Pearson correlation coefficient of each time series to the one of the pixel nearest to the corresponding ground site is calculated. The area for which a station is representative is defined by the characteristic radius around each station for each SEVIRI channel, where the average correlation falls below 0.9. It is found that measurements in the visible and near infrared channels, which respond to cloud microphysics, are correlated in an area with a 1 to 4 km radius, while the thermal channels, that correspond to cloud top temperature, are correlated to a distance of about 20 km. The defined radius even increases for the water vapor and ozone channels. While all stations in Central Europe are quite alike, the correlations around the station in the mountains of southern Italy are much lower. Additionally correlations at different distances corresponding to the grid box sizes of forecast models were compared. The results show good comparability between regional forecast models (grid size ≲ 10 km) and ground-based measurements since the correlations in less than 10 km distance are in all cases higher than 0.8. For larger distances like they are typical for global models (grid size ≳ 20 km) the correlations decrease to 0.6, especially for shortwave measurements and corresponding cloud products. By comparing daily means, the characteristic radius of each station is increased to about 3 to 10 times the value of instantaneous measurements and also the comparability to models grows.