Regional and Mesoscale Meteorology Branch

Introduction:

This is training that focuses on cloud-top cooling (CTC), and it replaces previous training on UW Convective Initiation as that product has evolved. The most significant cloud-top cooling is inferred to be the most intense growing convection, and that cooling correlates well with future NEXRAD signals. Vertical cloud growth – detected from satellite by cooling brightness temperatures – is what CTC keys on.

1. How clouds can give early convective information
2. How does the UW Cloud-Top Cooling algorithm work
3. Examples
4. How can CTC be used in conjunction with synoptic and mesoscale awareness to anticipate future development in NEXRAD

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 (74 MB) from the following link: http://rammb.cira.colostate.edu/training/visit/training_sessions/the_uw_convective_initiation_product/the_uw_convective_initiation_product_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

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.
• Sieglaff, J. M., L. M. Cronce, W. F. Feltz, K. M. Bedka, M. J. Pavolonis and A. K. Heidinger, 2011: Nowcasting convective storm initiation using satellite-based box-averaged cloud-top cooling and cloud-type trends. J Appl. Meteor. Climatol., 50, 110-126.
• Hartung, D. C., J. M. Sieglaff, L. M. cronce and W. F. Feltz, 2012: An inter-comparison of UWCI-CTC Algorithm cloud-top cooling rates with WSR-88D Radar Data. Wea. Forecasting (submitted)
• Hartung, D. C., J. M. Sieglaff, L. M. Cronce, and W. F. Feltz, 2013: An Inter-Comparison of UW Cloud-Top Cooling Rates with WSR-88D Radar Data. Wea. Forecasting, 28, 463-480.
• Sieglaff, J. M., L. M. Cronce, and W. F. Feltz, 2013b: Improving satellite-based convective cloud growth monitoring with visible optical depth retrievals. J. Appl. Meteor. Climatol., In submission.
• Sieglaff, J. M., D. C. Hartung, W. F. Feltz, L. M. Cronce, and V. Lakshmanan, 2013a: Development and application of a satellite-based convective cloud object-tracking methodology: A multipurpose data fusion tool. J. Atmos. Oceanic Technol., 30, 510-525.