STAR GOES-R Algorithm Working Group website National Oceanographic & Atmospheric Administration website NOAA Center for Satellite Applications and Research website

STAR - GOES-R Algorithm Working Group

Cloud-Top Pressure product image:Cloud drift winds from Hurricane Sandy

Cloud Top Pressure

May 1, 2013 - Cloud-Top Pressure product generated from simulated GOES-R ABI imagery over the Continental United States (CONUS). (Andy Heidinger, AWG cloud team)

Cloud Drift Winds from Hurricane Sandy

May 1, 2013 - Cloud-drift winds derived from 15-minute GOES-13 imagery over Hurricane Irene at 1930 UTC on 26 August 2011 using the clear-sky mask, cloud, and derived motion wind algorithms developed for the future GOES-R Advanced Baseline Imager (ABI).

The GOES-R Algorithm Working Group creates the algorithms that process the quality controlled satellite instrument data and produces resulting data "products" that are easier to use than the satellite data. For example, the algorithms transform signal strength values from various wavelengths into information about cloud characteristics, atmospheric properties, surface characteristics (snow, wild fires). The product links to the left in the Data Products section of the list describe the specific algorithm products.

  • Background introduces the data product and how it will be used for readers unfamiliar with the data product
  • Product Description provides more formal and technical details about the product
  • Improvements and Benefits highlights the data enhancements from GOES-R and how they will improve NOAA's ability fullfil its mission
  • How does it done? - Algorithms Explains how the algorithms process the satellite data to produce the data product
  • How are the results compared to existing data? - Calibration and Validation describes in some detail how the results from the algorithms are evaluated to ensure they are consistent with existing, correct data. This includes comparison with valid data from other satellites and from ground-based and aerial observations.
  • Product Preview includes interesting examples of the data, near-real-time proxy data results, and validation

Unlike other satellites, the algorithm development process for GOES-R combines government, academia and private industry in a unique collaboration which provides superior algorithm development that meets end user requirements!