Regional high-resolution cloud climatology based on MODIS cloud detection data

Abstract

Most satellite cloud climatologies come in the form of global, low-resolution datasets: so- called ‘gridded’ Level 3 products, resulting from the reprojection and spatio-temporal aggregation of swath (Level 2) data. Their coarse resolution means that global datasets are of limited usefulness in regional studies. In this paper we develop and evaluate a new, regional cloud climatology over Poland and its neighbouring countries (∼10% of the area covered by Europe), based on observations performed with the state-of-the-art cloud imager, the moderate resolution imaging spectroradiometer (MODIS). In contrast to the operational, global MODIS cloud climatology, which is delivered as a Level 3 product at a spatial resolution of 1° × 1°, this regional climatology maintains the MODIS nadir spatial resolution of 1 km/pixel. The resulting high-spatial-resolution climatology is compared with AVHRR and SEVIRI datasets, and surface-based (SYNOP) observations at the level of monthly and annual means. The results shows that the standard MODIS Level 2 cloud mask product MOD35/MYD35 can be successfully used to develop a regional, high-resolution cloud climatology. MODIS provides reliable estimates of cloud amount at the national scale (annual mean: 64.0% or 70.8%, depending on the MODIS data interpretation scheme), and correctly reproduces the annual cloud amount cycle (correlation between monthly means with SEVIRI/AVHRR >0.98). A comparison with monthly mean surface observations reveals a bias ranging from −1.1% up to 5.9%, and a root mean square error of 4.2% − 6.6%. MODIS data also correctly indicates the spatial distribution of clouds. However, local anomalies were detected that were identified as artifacts of the MODIS cloud detection algorithm. Those artifacts covered 9% of the study area, but had no impact on spatially-averaged metrics.