Converging findings of climate models and satellite observations on the positive impact of European forests on cloud cover

Overview:This repository hosts a comprehensive dataset resulting from a Space for Time (S4T) analysis (Duveiller et al. 2018). The dataset spans monthly data from 2004 to 2014, providing detailed insights into cloud cover dynamics and land cover characteristics. Leveraging observations from the Cloud CCI MODIS-Aqua dataset (Stengel et al. 2017) and RegCM5 (Giorgi et al. 2023) model outputs at 0.05 degrees resolution, it offers valuable resources for researchers studying atmospheric and terrestrial interactions.

Contents:

s4t_ESACCI.zip:Output of the space-for-time algorithm applied to the Global MODIS-Aqua cloud cover data for low, medium, and high clouds.s4t_RegCM5.zip:Output of the space for time algorithm applied to the European RegCM5 cloud data for low, medium, and high clouds.Variables:

Cloud Area Fractions:Includes low (cll), medium (clm), and high (clh) cloud area fractions, expressed as percentages.Cloud layers are categorized based on cloud top pressure (CTP), following the convention of the International Satellite Cloud Climatology Project.