Aug 9, 2012 CTC & Radar Comparison

Given active weather pattern (deepening upper level trough over Great Lakes) with showers and storms over Wisconsin, it wasn't hard to find quick growing cells with at least moderate Cloud Top Cooling (CTC) rates.

There were some breaks in the cloud field over northwestern Wisconsin.  Perhaps this helped oen cell in a line to pulse up.  We were able to spot CTC rates in the moderate range with a value of 17 to 18 over northwestern Washburn County.  Further north in St. Louis County of northeastern Minnesota we observed a CTC value of 12 to 13. See Figure 1 below.

Figure 1. Maximum CTC rates of 17 to 18 over Washburn County.

 We then compared the cells with decent CTC rates with what the WSR-88D Radars depicted.  SEe Figure 2 below for the radar image which corresponds to Figure 1.

Figure 2. Radar image at 1643Z August 9, 2012.

The decent CTC rates would imply an increase in cell intensity observed on radar.  This intensity increase is noted in Figure 3 below, especially in the St. Louis cell which had a 60 dBZ signature.  Of course, these storms were not severe, but it was nice to see that the CTC rate idea enabled us to anticipate an increase in cell intensity.

Figure 3. Radar image at 1706z August 9, 2012.

Rusty Kapela - MKX
Ed Townsend - MKX
Justin Sieglaff - CIMSS

1.5 Hour Lead Time from UAH CI Algorithm

Figure 1.
UAH CI forecast (red) valid from the 2040 UTC GOES imagery.

















Figure 2.
Radar valid at 2042 UTC.

















Figure 3.
Radar valid at 2209 UTC.

The UAH CI algorithm forecasted CI (first instance of 35+dBZ radar echo) approximately 1.5 hours before it was detected on radar for this case in western Minnesota (Figures 1 - 3, above). As subsequent GOES imagery rolled in, the algorithm continued to forecast CI down along a line of growing clouds to the south, achieving lead times of around 1 hour. According to the Storm Prediction Center storm reports (see Figure 4, below), this line of storms quickly turned severe and went on to produce several instances of large hail and even a tornado!


















Figure 4.
SPC storm reports for 05/10/2011, valid through ~12 UTC on 05/11/2011.

Innovative Methods for Displaying UAH CI Product in AWIPS

Some of the forecasters here in the Experimental Warning Program are finding creative ways to integrate the UAH CI product (GOES-R AWG CI product proxy) into their AWIPS workstations. Above is an excellent example of this. In the top-left display quadrant, the Null (blue) and Positive (red) cloud object CI forecasts are overlaid onto GOES Visible satellite data, with an option to change the transparency of the two integrated data sets at the touch of a button. Similarly, in the top-right display quadrant, the UAH CI product is overlaid onto radar data.... This way the forecasters will know where to focus their attention on the radar for future development, especially in regions where severe weather is expected but not yet initiated.

UAH CI (SATCAST) Now Up and Flowing...

Despite a few early glitches in the product delivery, the UAH CI product is now flowing into the SPC Hazardous Weather Testbed AWIPS and N-AWIPS workstations regularly. The posted pic (above) is the first image that was received for "real-time" display in this year's newly created Convective Initiation desk.

From the time of the first GOES scan line (the image time stamp), it took only 10 minutes for the data to be processed, delivered, and displayed..... This is a significant advantage over the time latency issues the UAH CI product had from last year (our first year of "real-time" processing and evaluation). This is typical for Northern Hemisphere scans from GOES. For pure CONUS scans from GOES, it generally only takes about 8 minutes to accomplish the same process. From the moment the GOES data is downloaded, it takes a mere ~1.5 - 2.5 minutes to process it and produce the CI output forecast.