Todd Lindley, Science Operations Officer with the National Weather Service Weather Forecast Office (WFO) in Norman Oklahoma is the senior author of a 2016 paper in the Journal of Operational Meteorology: T. Todd Lindley, Aaron R. Anderson, Vivek N. Mahale, Thomas S. Curl, William E Line, Scott S. Lindstrom and A. Scott Bachmeier. 2016. Wildfire Detection Notifications for Impact-Based Decision Support Services in Oklahoma Using Geostationary Super Rapid Scan Satellite Imagery. Journal of Operational Meteorology, 4 (14), 182-191, http://nwafiles.nwas.org/jom/articles/2016/2016-JOM14/2016-JOM14.pdf. I have been privileged to have exchanged e-mails and had a telephone conversation with Mr. Lindley about an Experimental Wildfire Detection Notification Application (WFDN) that he and his colleagues have written about in this 2016 paper. Unless otherwise noted, this post is based on Lindley et al’s 2016 paper.
In February 2016, GOES-16 (GOES-R) was not yet launched. GOES-14, the in-orbit spare, was operating in what is known as super rapid scan mode (SRSOR), an experimental mode where GOES-14 can take special one-min imagery. GOES-14 was operating in this SRSOR mode in mid to late February 2016 when there were wildfires in OK. Lindley et al explain how this works in their 2016 paper:
Although not capable of the improved spatial or spectral attributes of the Advanced Baseline Imager (ABI) of GOES-16, the GOES-14 imager was operated by NOAA in SRSOR mode during several multi-week periods spanning late 2012 through early 2016. These SRSOR windows have demonstrated the high-temporal resolution sampling capability of the GOES-R ABI when operating in mode 3, known as “flex mode,” by providing 1-min imagery. The SRSOR data have been utilized in algorithm development, in various NWS field offices and national centers, and in operational support of experiments including those in the NWS’s Operations Proving Ground and Hazardous Weather Testbed. Experimental use of SRSOR and the operational benefits of high- temporal resolution satellite imagery is well documented for numerous phenomena including fog and low stratus, convective storms, wildland fire and smoke, and tropical cyclones (Lindley et al (2016, p, 184).February 18, 2016 was a busy day at the NWS Norman OK Weather Forecast Office. They were monitoring both wildfire danger and existing wildfires in their forecast area. GOES-14 in SRSOR mode (one-minute imagery) was available to them where data and images were being fed into their AWIPS computer system. I’ll let Todd Lindley, Science and Operations Officer at the National Weather Service in Norman, OK explain:
We had a request by Oklahoma Forestry Services (OFS) to provide a courtesy call as we detected new fire on the morning of 18 February 2016. It just so happened that we were ingesting 1-min SRSOR data that day as part of an experimental window in preparation for GOES-R/16. My Meteorologist-in-Charge had the vision that morning to suggest that this was an opportunity to ‘innovate’. We quickly brainstormed on how best to do that, and the Experimental Wildfire Detection Notification (WFDN) App was born (May 10, 2017 e-mail with author).Specifically, the NWS Norman OK Weather Forecast Office Information Technology staff quickly wrote a Python application where after the satellite imagery was analyzed by NWS forecasters for wildfire hotspots. After the imagery was analyzed, the NWS forecasters could transmit wildfire detection notifications through AWIPS to a list of predetermined OFS officials by SMS e-mail to text. The SMS includes the latitude and longitude of the wildfire hotspot plus a link to the local weather forecast. Todd was nice enough to send me a sample of one of the Experimental Wildfire Detection Notifications for you to look at:
|Courtesy of NWS Norman OK Weather Forecast Office|
Among the wildfires in the February 18, 2016 wildfire outbreak was the Buffalo Fire that ultimately burned 17,280 acres in Northwest Oklahoma. GOES-14 in SRSOR mode detected wildfire hotspots that would not have been detected by GOES East (GOES-13) and GOES West (GOES-15). The high resolution capabilities of GOES-14 in SRSOS mode and the WFDN App meant an 18 to 23 minute advantage leading to improved response time by responding fire departments and wild land firefighters.
A total of eight wildfire notifications were transmitted by WFO Norman on 18 February 2016. Post-event feedback from OFS stated that these notifications were 'key contributors to a measure of effectiveness in response to very aggressive and fast-paced fire activity' and that the dissemination of this information ‘enhanced situation awareness’ and ‘permitted contact [with] a few departments in advance of 911 calls.’ It was additionally noted that 'fire location often plays a role in resource allocation priority' and that text messages enabled a timely dispatch of resources and aided in prioritization of fires ‘with structures and improvements at risk' (D. Daily 2016 personal communication cited in Lindley et al, 2016, 185).After the February 18th wildfire outbreak, the Oklahoma Department of Emergency Management developed a GIS based display system that monitors wildfires and allocation of equipment and firefighters. During the remainder of the 2016 late-winter early-spring wildfire season the WFO Norman OK continued to use GOES-13 (GOES East) or GOES-14 in SRSOR mode. After analyses by NWS Forecasters at WFO Norman OK, the imagery was fed into AWIPS, and to the WFDN App and many notifications were received by first responders prior to 911 calls.
The WFDN App continued to make a difference in wildfire response time in NW Oklahoma during the rest of the late-winter early-spring wildfire season in NW OK:
… continued use of text notifications on 5 April 2016 prompted the following feedback from Major County Emergency Manager, Tresa Lackey: ‘We were very grateful when NWS detected a fire south of Bouse Junction and was able to route forestry planes to the location...to assist in fire suppression. Our resources were spread thin already fighting fires across the county. The extra help in the fire detection and suppression really saved us. Fire- fighters were able to contain the fire before the wind [shift] later that evening’ (Lindley et al, 2016, 189).I will write about the further developments of the Experimental Wildfire Detection Notification App by WFO Norman OK and other WFO offices in 2017 in part 6.
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 (this article)
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
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