Statistics on low cloud occurrence per month along the South-Western African coast at 7:00 and 14:00 UTC, 2004 to 2009

The spatial and temporal patterns of fog and low clouds along the South-Western African coast are characterized based on an evaluation of Meteosat SEVIRI satellite data. A technique for the detection of fog/low clouds in the region is introduced, and validated using 1 year of CALIOP cloud lidar products, showing reliable performance. The frequency of fog and low cloud in the study area is analyzed by systematic application of the technique to all available Meteosat SEVIRI scenes from 2004 to 2009, for 7:00 UTC and 14:00 UTC. The highest frequencies are encountered in the area around Walvis Bay, with a peak in the summer months. Fog and low clouds clear by 14:00 UTC almost everywhere over land.

Reference list of sources used for two experimental data files dataBSRN and dataMixed

Increasing amounts of data is collected in most areas of research and application. The degree to which this data can be accessed, analyzed, and retrieved, is a decisive in obtaining progress in fields such as scientific research or industrial production. We present a novel methodology supporting content-based retrieval and exploratory search in repositories of multivariate research data. In particular, our methods are able to describe two-dimensional functional dependencies in research data, e.g. the relationship between ination and unemployment in economics. Our basic idea is to use feature vectors based on the goodness-of-fit of a set of regression models to describe the data mathematically. We denote this approach Regressional Features and use it for content-based search and, since our approach motivates an intuitive definition of interestingness, for exploring the most interesting data. We apply our method on considerable real-world research datasets, showing the usefulness of our approach for user-centered access to research data in a Digital Library system.