Using RGBs Operationally

These are some of the questions that forecasters often ask about using RGBs. Many of the answers will be elaborated on in other parts of the module.

Click each question for a brief response.

How easy is it to interpret RGBs?

RGBs are generally easier to use than single channel images and are often more effective at depicting important meteorological phenomena. Although the color schemes for RGBs are generally straightforward, it typically takes some training and experience to use them correctly. Some products are "intuitive," while others are not and can easily be misinterpreted.

Are RGBs available in real-time? How does one access them?

RGBs are increasingly available in real-time and near-real-time via the Internet. Efforts are underway to get RGBs into forecast offices.

Here are some commonly used RGB sites:

Who produces operational RGBs?

A number of meteorological services produce their own RGBs, following a set of best practice guidelines developed by the World Meteorological Organization. The guidelines are intended to standardize channel selection and color assignment for a common suite of products across international organizations.

What are the benefits of creating your own RGBs?

It can be useful to make an RGB when you're in a unique forecasting situation for which no other products are available. However, you need to be aware of the challenges and pitfalls of making RGBs. In general, it is better to use standardized RGBs.

How do RGBs differ from single channel color enhancements and quantitative products?

RGB processing is one of a range of techniques developed to extract, emphasize, and optimize information from satellite imagery.

  • Grayscale images display imager information from single channels over a range of gray shades; products are made from 256 colors
  • Color displays of single channels are similar to grayscale images but the information is displayed using a set of assigned colors, rather than gray shades, to highlight specific features of interest, such as the colder cloud-top temperatures associated with deep convection; products are made from 256 colors
  • RGBs are generally made from three or more spectral channels or channel differences; each is assigned to one of the three primary colors, and the final product highlights specific feature(s); products are made from millions of colors
  • Classification products depict various non-quantitative classes of phenomena, such as cloud classifications (stratus, cirrus, and cumulus, etc.), using a color bar key
  • Quantitative products depict physical quantities, such as sea surface temperature and total precipitable water content, in various colors using a graded color bar; for more information, see the COMET module "Creating Meteorological Products from Satellite Data" at