Regional and Mesoscale Meteorology Branch

Introduction:

This training session is part of a series that focuses on applications of synthetic imagery from the NSSL 4-km WRF-ARW model. In this training session we’ll consider applications of the synthetic imagery in forecasting low clouds and fog. The primary motivation for looking at synthetic imagery is that you can see many processes in an integrated way compared with looking at numerous model fields and integrating them mentally.

This is an experimental GOES-R Proving Ground Product designed to foster GOES-R readiness.

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 Learn 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 anytime. Create a directory to download the audio playback file (67 MB) from the following link: http://rammb.cira.colostate.edu/training/visit/training_sessions/synthetic_imagery_in_forecasting_low_clouds_and_fog/synthetic_imagery_in_forecasting_low_clouds_and_fog_audio.exe 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:

• Talking points are available for this lesson and may be printed out to easily review the session in detail at any time.
• GOES-R product suite
• Product Information page on NSSL 4-km WRF-ARW Synthetic low-cloud and fog product
• Experimental 4-km NSSL WRF-ARW Fog Forecast Product
• NSSL 4-km WRF-ARW model output
• Bikos, D., Lindsey, D.T., Otkin, J., Sieglaff, J., Grasso, L., Siewert, C., Correia Jr., J., Coniglio, M., Rabin, R., Kain, J.S., and S. Dembek, 2012: Synthetic Satellite Imagery For Real-Time High Resolution Model Evaluation. Wea. Forecasting,27,784-795. http://dx.doi.org/10.1175/WAF-D-11-00130.1
• Grasso, L.D., M. Sengupta, J.F., Dostalek, R.L. Brummer, and M. DeMaria, 2008: Synthetic Satellite Imagery for Current and Future Environmental Satellites. International Journal of Remote Sensing. 29:15, 4373.
• Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang and J. G. Powers, 2005: A Description of the Advanced Research WRF Version 2, NCAR technical note.