A forecaster's efficiency in assimilating information is critical to ensuring a timely determination of a storm's track and intensity. Satellite image displays form the bedrock of any modern-day forecaster's suite of display products, especially for tropical systems that are far from land. Can these displays be made more efficient for information assimilation? All current displays of satellite data use an Earth centered coordinate loop control. In this conventional technique, the images are matched so that the Earth, and map features, hold still and the weather moves across the frame. The time looping of these displays allows one to see the storm's movement and changes in the storm's characteristics. While this is the most common use of satellite imagery, there is another equally valid approach, one in which the image follows the center of circulation of a feature – a Lagrangian reference frame that follows the storm. Just as the flow of air over, or around, a moving car or wing is very different from the wind field that would be experienced by a stationary observer, the wind field experienced by a moving weather system can be dramatically different from the stationary, or Eulerian, reference frame.

When geostationary satellite images first became widely available 30 years ago, there was considerable experimentation as to the best way of displaying this new data set. One method that was tested was a “storm relative reference frame” image loop where the images where shifted so that the storm's motion was zeroed out, leaving only the motions relative to the storm. There are a number of useful applications to this method that would allow users to better understand storms from the mesoscale to the synoptic scale. However, storm relative loops required special workstations and individual attention to set up and maintain each loop. In spite of the early studies that suggested this was an important technique, it was impractical to create the products.

This project implements this display technology, utilizing data streams and processing software that are part of the Embry-Riddle Aeronautical University Applied Meteorology infrastructure. We utilize our existing Mcidas and GEMPAK software packages to process the data, and then display the data using the NMAP2 software that is used in the classroom environment. Additionally, web images are developed for use on Internet accessible pages. Sample images may be found at http://wx.erau.edu/~herbster/demo/LSI/.