Part 7 of 8 Application of GOES-16 for wildfire detection: Experimental Wildfire Detection Notification App making a difference

I have exchanged several e-mails and have had a couple of telephone conversations with Todd Lindley (Science and Operations Officer, NWS Weather Forecast Office Norman OK about the Wildfire Detection Notification (WFDN) App. In a telephone conversation on May 1, 2017, I asked Todd if he could provide a couple of examples that I could share with you about how the Experimental WFDN App has made a difference. He discussed two examples that I will share with you.

February 8th 2017: The NWS Norman OK Forecaster analyzing GOES-16 wildfire detection images detected a hot spot in Logan County, OK. After the analysis and evaluation of these images was complete, the data released to Oklahoma for dispatch. Upon dispatch to Oklahoma, it turned out that the hot spot detected by GOES was a  structure fire in a very rural location. This WFDN dispatch was the only dispatch, there was no 911 dispatch. The house, which was not occupied at the time, was fully engulfed. 

February 23rd, 2017: In the period leading up to February 23rd, weather forecasters at WFO Norman OK used some historical wildfire outbreak data coupled with elevated wildfire danger conditions in the area to communicate extreme fire danger conditions to their State partners. The Oklahoma Forestry Services used this information to preposition ground and aviation resources (in this case Blackhawk helicopters) on February 22nd. 

On February 23rd Forecasters at NWS Norman OK analyzing GOES-16 images detected a hotspots, after analysis and evaluation, the data was released to their State partners for dispatch. One of the hot spots was near where OFS had prepositioned ground and aerial assets on February 22nd. Units responded quickly to the wildfire with good initial attack. The fire was contained at about 200 acres.. Similar outbreaks in nearby areas of Texas in the same time period grew to about 5 to 8,000 acres. The key to the containment of this particular fire at 200 acres was the prepositioning of ground and air resources coupled with the WFDN resulting in moving resources to the hotspot. The key was initial attack.

In part 8, I will conclude this series with some  of my own reflections on what I have learned in writing this series on the application of GOES-16 for wildfire detection and the development of the Experimental Wildfire Detection Notification App.

List of articles in this eight part series on the Application of GOES-16 for wildfire detection 


June 21: Part 1 of 8: Application of GOES-16 for wildfire detection: Introduction

June 23: Part 2 of 8: Application of GOES-16 for wildfire detection: A little about the GOES-16 Advanced Baseline Imager

June 26: Part 3 of 8 Application of GOES-16 for wildfire detection: examples of improved imagery with GOES-16

June 28: Part 4 of 8 Application of GOES-16 for wildfire detection: wildfire detection improved with GOES-16

June 30: Part 5 of 8 Application of GOES-16 for wildfire detection: February 18, 2016 wildfire danger in western OK and development of the Experimental Wildfire Detection Notification App

July 3: Part 6 of 8: Application of GOES-16 for wildfire detection: Experimental Wildfire
Detection Notification App in use Spring 2017

July 5: Part 7 of 8 Application of GOES-16 for wildfire detection: Experimental Wildfire
Detection Notification App making a difference (this article)

July 7: Part 8 of 8 Application of GOES-16 for wildfire detection: Reflections on using
GOES-16 for wildfire detection and the Experimental Wildfire Detection Notification App