This thesis provides insights into the relation betwen two vital elements within the physical precipitation system: cloud top temperature (CTT) and precipitation. It investigates gauge data from ground stations in Germany and satellite data on CTT, targeted at the same stations in Germany. Cloud and rainfall characteristics
are considered and both simple and advanced mathematical tools are covered.
Statistical methods show that the data present is not stationary. Stationary data is required for applying time series analysis, either in the time or frequency domain. The key step in this research is dividing the big dataset into smaller subsets based on the provided characteristics: elevation, region and time. For these subsets the Pearson correlation and Spearman’s rank correlation coefficient show that significant correlations can be found. Lastly, this thesis looks into the possibilities for setting thresholds for cloud top temperature in
relation to the precipitation. These thresholds should be able to tell whether a day can be considered ’dry’ or ’wet’. Due to the incoherent data, these thresholds are not very optimal. Many circumstances need to be considered in order to make these thresholds fit specific situations.