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  • Running MODE on HRRR-TLE members

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  • There should be six members for each HRRR-TLE product (not three)
  • Everyone agreed that the most representative plots were those with the HRRRx members run through MODE using conv_rad=0 and conv_thres=0.0127 (0.5"; to match the HRRR-TLE product)
  • Moving forward, how about we use the testbed (specifically FFAIR) to test verification approaches?
    • In order to facilitate this, a presentation will be put together to share with the participants regarding how HRRR-TLE is performing when looking at it in a variety of ways
    • Isidora/Trevor will show reliability, skill, etc. for a season that they have run HRRR-TLE for in retrospective mode (from 2015 I believe)
    • NCAR will run a few cases (to be identified by Isidora, and HRRR-TLE data will be provided) through MODE to show how the objects from HRRR-TLE compare to observations (MRMS - QPE/reflectivity?)
      • In addition to showing overall interest value, should show different attributes available in MODE
      • Isidora prefers not to call this verification because it is a probabilistic field against a thresholded observation -> she recommended something like "area of interest detection"
      • Trevor still is not sure that MODE is useful on a case-by-case basis for probablistic fields; however...
      • Julie and Jamie stressed that a forecaster on the desk for a particular day would remember how the tool helped them forecast a particular event on that day, not necessarily the aggregated skill over a season (where you can start comparing probabilities to frequency of occurrence)
      • I think both Isidora and Trevor agree that it is worth presenting this at FFAIR to see the reaction of the forecasters and to hopefully instill confidence in the product
      • It will be good to have Julie followup with the forecasters on this approach. Hopefully it intuitively follows how the they do "verification" in their head on a case-by-case basis in real-time for probabilistic fields.