Snowband Probability Prototype Page

Available Data

Ensemble Resolution Runs Per Day Membership Run Length
HREF ~4 km 2 8 (4 time-lagged) 36 h
HRRRv3 TLE ~3 km 24 4 (3 time-lagged) 15 h
HRRRv4 TLE ~3 km 6 3 (2 time-lagged) 30 h
HRRRe ~3 km 2 9 18 h at 00 UTC, 36 h at 12 UTC

Additional Details

  • The HRRRv3 time lagged ensemble (TLE) consists of the four most recent HRRR runs. This ensemble updates every hour with new information.
  • The HRRRv4 is also a TLE, but consists of only the extended runs (i.e. the runs that go out to forecast hour 36), which are performed every 6th hour.
  • The HREF consists of 4 members and 4 time-lagged members, and updates at 00, 06, 12, and 18 UTC.
  • MODE-Time-Domain (MTD) Info

    The Method for Object-Based Diagnostic Evaluation-Time-Domain (MODE-TD) tool from the Model Evaluation Tools v8.0 software developed by the Developmental Testbed Center (DTC) is used to identify and track ensemble member Quantitative Precipitation Forecast (QPF) objects. 1 hour accumulated QPF from all of the members within each ensemble listed above are used as input into MODE-TD. To identify snow-only QPF, all models are masked using the categorical snow precipitation type grid.

    After applying the snow-only mask, MODE-TD is used to identify and track modeled snowbands through space and time. MODE-TD initially applies a convolution filter (5 grid spaces) to smooth the data, before masking and removing all data below a certain hourly precipitation amount. This simplifies the process of identifying the desired objects by removing small, noisy objects. Thereafter, MODE-TD is run to identify modeled objects and their attributes (e.g., centroid location, intensity, orientation, area). The methodology for identifying objects is complex and involves the following two processes illustrated in the figure below:

      1. Identify coherent space/time objects of a certain size
      2. Merge nearby space/time objects that are likely the same object

    The above figure illustrates an example of this process where raw precipitation is input into MODE-TD in (a), resulting in two identifiable objects in (b), with only the raw QPF within these objects being retained in (c). For more information, please see the DTC description about MODE-TD at

    About the Graphics

    As discussed above, MODE-TD outputs a variety of object attributes, including object centroid location, velocity, orientation, area, and intensity. Displaying some of these attributes is not informative in the context of modeled snowbands. To create visually appealing graphics of the most useful attributes, only the outline (i.e. object area) and intensity of the object are displayed. The intensity is calculated as the 90th percentile of QPF within each object (see panel c in the figure above), and is represented by the color of the outline of the object.

    About dModel/dt

    dModel/dt is a tool to look at the forecast evolution or trends for a particular valid time. This is a function of both how far out a particular model forecast extends and the how often a new model cycle is available. For example, dModel/dt of a 1-h hourly-updating HRRRv3 forecast will have 14 of the previous forecasts valid for that time beginning with the 15-h forecast from the cycle initialized 15 hours ago. However, looking at dModel/dt for a 12-h forecast will only show the previous 3 forecast cycles valid for that time from an hourly-updating model. For a model updating less frequently like the HREF that is issued every 12 h out to 36 h, no dModel/dt is available after FH 24 because that extends beyond the forecast range of the previous cycle.