Robin Hogan
20 August 2004
There is a growing recognition of the usefulness of cloud radar for evaluating numerous aspects of the representation of clouds in numerical forecast models, but to make the best use of such data it should be combined with information from other sources such as lidar, radiometers, rain gauge and a forecast model. For cloud retrievals to be useful for evaluating models they must be applied to large volumes of data, rather than just a few case studies, which necessitates the development of robust algorithms for performing essential preprocessing such as identifying cloud types and hence to which data certain algorithms can be applied. Differences in data formats and conventions can make it a major undertaking to adapt an algorithm developed for the instruments at one site to work with data from another.
The following document describes an intermediate data product designed to facilitate the application of multi-sensor algorithms by performing most of the typical preprocessing that such algorithms require and providing the results in a common format for all sites. It was developed for the Cloudnet project involving three European remote sensing sites. In the context of Cloudnet this product is designated `Level 1c', lying between calibrated instrumental data in NetCDF format at Level 1b and meteorological products at Level 2.