GOES-17 Loop Heat Pipe and Predictive Calibration

Scott Lindstorm

30 Min

Introduction:


Objectives:

  1. Better understanding of GOES Satellite calibration.
  2. Understand how and why GOES-17 infrared imagery is degraded at some times of the year because of the Loop Heat Pipe.
  3. Understand how predictive calibration will improve imagery from GOES-17 — but also understand what it will not provide, data when the sensors saturate.

Outline:

  1. How are the detectors on ABI integrated into the cooling system on GOES-R satellites.
  2. When during the year does the Loop Heat Pipe underperformance have the biggest impact on infrared imagery?
  3. How does the degradation affect the infrared signal as the Loop Heat Pipe starts to malfunction at some points of the year?
  4. Example of the degradation.
  5. Predictive calibration and its impact.

Training Session Options:


NOAA/NWS students – to begin the training, use the web-based video, YouTube video, or audio playback options below (if present for this session). Certificates of completion for NOAA/NWS employees can be obtained by accessing the session via the Commerce Learning Center.

  1. Audio playback (recommended for low-bandwidth users) – This is an audio playback version in the form of a downloadable VISITview and can be taken at any time. Create a directory to download the audio playback file (135 MB) from the following link: http://rammb.cira.colostate.edu/training/visit/training_sessions/goes_17_loop_heat_pipe_and_predictive_calibration/goes_17_loop_heat_pipe_and_predictive_calibration_audio.zip After extracting the files into that directory click on either the visitplay.bat or visitauto.bat file to start the lesson. If both files are present, use visitauto.bat
  2. YouTube video:

References / Additional Links:


Blog post Data Fusion to mitigate Loop Heat Pipe data dropouts

Blog post on Predictive Cal becoming operational

Blog post on Loop Heat Pipe effects on 14 April 2019

Blog post showing an example on Data Fusion

This course is Basic

This Course has no Prerequisites

Contact:

Scott Lindstrom

scottl@ssec.wisc.edu

Page Contact

Unless otherwise noted, all content on the CIRA RAMMB: VISIT, SHyMet and VLab webpages are released under a Creative Commons Attribution 3.0 License.