The day began with an archived LMA event.  We then had a successful MRMS IOP in the Cheyenne, WY, and North Platte, NE, CWAs.  We certainly made the most of what was a marginal severe weather setup in the most marginal of weeks!  Forecasters spent some time learning the MRMS products, and then began to issue warnings.  Severe warnings were scattered initially.  Eventually, one multicell formed a cold pool and propagated forward, maintaining a severe weather threat all along its path as it approached the KLNX radar. There was plenty of discussion of MRMS products in relation to wind and hail threats, and updraft strength. Operations are winding down as of 8:25 pm CDT, and we will hold an end of day discussion to gather forecaster feedback.

All of this week’s forecasters advocate intense use of base data in warning decision making.  Mike says “We are overloaded with derived radar products.  Just give me the base data, and a better understanding of the environment (to improve warning decision making).”  Others agree that environmental data is key to warning decision making, but they also point out that there may be some tasks that algorithms can perform very well, thus freeing the human forecaster to tackle other problems.  The group also discussed certain scenarios in which algorithms can aide the forecaster during low staffing or broad geographical outbreaks.  In such cases, Matthew would use algorithms to rank storms that need further investigation in the base data.  Les and Rob particularly like the LMA and lightning trend data, as it is “Base data of a different kind.”  The forecasters, as a whole, liked the trend graphs for all types of data.  That was the most useful function of the data in Google Earth.  The group noted several areas, however, where the Google Earth data needs improving.  There is no time stamp, images are smoothed, and there is no cursor readout.  They would like the color tables to be synced to the respective products with which they were intended to be used, rather than requiring the forecaster to click on a product and then click on an appropriate color curve.  The color curves also need to be consistent across platforms so that the data looks the same on Google Earth as it does on D2D/AWIPS.  In its current state, forecasters feel the images in Google Earth are better suited to verification efforts by mapping MESH and rotation tracks to GIS data, than they are suited to warning decision making.  Within AWIPS, forecasters looked at MESH swaths and current MESH, as well as height of the 50 dbZ reflectivity.  These things were used most often to assess hail and updraft strength.  As noted in another post, forecasters would like to see height products for 60 dbZ, and they did not seem to find much use for 18 and 30 dbZ.

Patrick Burke (EWP Weekly Coordinator, 18-22 May 2009)