NESDIS SFR Captures Central and NE Alabama Snow Event

SPoRT continues to work with select NWS WFOs in evaluating the NESDIS SFR product.

A rare winter storm impacted much of the deep South Tuesday morning and afternoon.  Areas of Central and Northeastern Alabama only received a couple of inches of snow, but this was enough to cause major headaches as roadways iced over resulting in highways across Alabama and Georgia being shut down, stranding thousands of motorists.  Most reports from late Tuesday morning indicated that the worse of the winter weather was falling south of Cullman, AL, through Birmingham, AL to Montgomery, AL and then eastward into areas like Fort Payne, AL.  I-65 north of Birmingham and I-20 east of Birmingham were particularly troublesome in the state of Alabama.

The AWIPS image below depicts the SFR product in AWIPS with overlaid interstate highways.  This image was taken from the AMSU on Metop-B at 1618 UTC (10:18 local Alabama time) right about the time when the heaviest snow was impacting the state.  The SFR Product indicates liquid water equivalent precipitation rates between 0.04 and 0.08 in/hr, which if you multiply by a factor of 10 to get the solid snowfall rate equates to around 0.4 and 0.8 in/hr.  Snowfall totals across this region were generally in the 1-3 inch range, so the rates that were detected by the product were consistent with what actually fell.

NESDIS SFR Product from 1618 UTC (around 10:00 A.M. Central) on 28 January 2014

NESDIS SFR Product from 1618 UTC (around 10:00 A.M. Central) on 28 January 2014

2 thoughts on “NESDIS SFR Captures Central and NE Alabama Snow Event

  1. Brad,
    I am actually working on this case with about 4 or 5 images from around 1030 UTC earlier in the morning to about 2015 UTC during the afternoon and will share with you when I finish. A definite success story for the product and may have been some help with nowcasting…even forecasting it a few hours before the snow started in the Birmingham area mid morning.

  2. That’s great, Sheldon! I look forward to seeing your detailed analysis of the case. It would definitely be interesting if we could demonstrate through this example how the product could be used to detect snow in the clouds before it begins falling and then translate that to a nowcast on the ground.

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