Introduction


The new generation satellite data contain more and more information offering increased insight into cloud and air mass characteristics. This poses a challenge: figuring out how to extract, distill and package the data into products that are easy for forecasters to interpret and use.

On RGB displays some of the cloud and air mass characteristics may be easily evidenced with a minimum of processing by attributing a selection of channels and/or channel differences to the individual RGB colour planes.

RGB (red, green and blue) refers to a system for representing the colours to be used on a computer display. (Colours are represented by 'number triplets'. The numbers range from 0 to 255, representing the intensity of each primary colour.) Several models are used to describe colours. The RGB colour model is just one of them.

One might create numerous different kinds of RGB images. Satellite experts developed some optimally tuned RGB types for highlighting specific features. These are the so called standard RGBs recommended by EUMETSAT. The advantage of using standard RGBs is their easy comparability.

The aim of creating RGBs is to provide fast, easily understandable VISUAL information. A 'good' RGB should convey information that would be difficult or time consuming to assess visually from one or more individual single channel images. RGB image should be unambiguous and use intuitive colours to help highlighting important meteorological and surface features. RGBs provide useful information to forecasters, in particular when looking at animated image sequences. They preserve the "natural" look-and-feel of "traditional" satellite images, e.g. they preserve texture, and the patterns are continuous in time.

The 'Operational use of RGB images' training module discusses several EUMETSAT suggested standard RGB types to be created from Meteosat SEVIRI images, but not all of them. The present training module discusses four additional EUMETSAT recommended standard RGB types: the HRV Fog RGB, the Snow RGB, the Night Microphysics RGB and the Ash RGB.

The main aim of the training module is to help the users (weather forecasters and/or other experts) to understand and use these RGB types by giving them background information, examples and exercises.

The logical structure of the discussion is the following:

  • The aim of the RGB type
  • Physical background
  • How to create the given RGB type
  • Typical colours
  • Examples of interpretations
  • Benefits and limitations
  • Comparisons with other RGB types and/or single channel images
  • Exercise


Acknowledgements

The authors wish to thank EUMETSAT for the beneficent training workshops on MSG applications and RGB images. This training module has benefited from many advices and suggestions provided by Jochen Kerkmann (EUMETSAT).