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

In this article I will introduce the Experimental Wildfire Detection Notification (WFDN) application first developed and used in the NWS Norman OK WFO on February 18, 2016. The WFDN was first used in conjunction with GOES-14 in super rapid scan mode. After GOES-16 was launched, and while she was still in operational testing, the WFDN was and still is being used by National Weather Service Weather Forecast Office in Norman OK in conjunction with GOES-16.


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

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

One of the 16 spectoral channels on GOES-16, channel 7, 3.9 µm, detects wildfire hot spots among other things.. Listen to Ivan Csiszar, a physical scientist with the NOAA Center for Satellite Applications, discuss wildfire detection using GOES-16 in the following video:


Direct link to video

For those of you who want to dig a little deeper, I will share three CIMSS Blog entries below with images from GOES-13 and GOES-16 of wildfires. Note the higher resolution from the GOES-16 Advanced Baseline Imager. One of my Operational Meteorologist friends from the National Weather Service  told me that their posts explain things very well. When looking at the imagery, it is important to note that red/yellow colors in the imagery depict high intensity fires and the black colors depict smaller fires. See the March 6th imagery of the Grass Fires in KS, OK, and TX for some good imagery of high intensity fires, recall that the Northwest Complex (KS, OK, TX) burned over 782,000 acres.


I think that the April 11th imagery is the best of the three at representing  the higher resolution of GOES-16 as compared to GOES-13. The March 16 imagery depicts a smaller wildfire hotspot, you will see red/yellow colors, depicting a high intensity fire at about 5 seconds on the GOES-16 ABI image.

CIMSS Blog, April 11, 2017 Fires (prescribed burns) in Eastern KS and OK

CIMSS Blog, March 6, 2017 Grass Fires-KS, OK, TX

CIMSS Blog, March 19, 2017 GOES-16 Mesoscale Sectors: Improved monitoring of fire activity

Finally, I recently contacted NOAA Satellites and Information Services on their Facebook Page (which is very nice and I highly recommend it. I told them about the article this article, asking them if they had any videos comparing GOES-13 with GOES-16. NOAA Satellites provided this link to their animations (currently page 6 of 8 pages). You may need to scroll to find two videos, one is of GOES-16 and GOES-13 images of Grass Fires in Florida and the other is of GOES-16 and GOES-13 Comparison Punch Clouds. I did not know what a punch cloud is, so I asked one of my meteorologist friends from the National Weather Service who told me punch clouds are circular or elliptical holes in clouds that can form when supercooled water begins to freeze. Note, depending on when you are arriving at this article, it is possible that the provided link may have different images, but if you look around on different pages you should find the two referenced images.

Next up in part 5: wildfire danger in Norman in western OK (February 18, 2016) 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 (this article)

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

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

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

There is a growing amount of images from GOES-16 available on the internet. GOES-16 is undergoing testing as I write this; all of these images that you see on the internet are non-operational, preliminary data. 

The three primary sources that I go to are (1) NOAA’s Satellite and Information Service , and (2) a GOES-R mission page with a data and imagery page. Third, a few months ago, a couple of my Operational Meteorologist friends from the National Weather Service suggested that I take a look at the CIMSS out of University of Wisconsin at Madison, saying that they have good information on GOES-16 and other satellites. The CIMSS has a blog with images from GOES-16 and other satellites. I have spent hours on all three sites. 

Before I move to how GOES-16 can be used for wildfire detections, I want to show you a couple of examples of the differences between GOES-13 and GOES-16. On the theory that one picture (or short video) is worth a thousand words, I am steering you to two entries from the CIMSS Blog.

CIMSS Blog, April 4, 2017, lake effect clouds, GOES-13 and GOES-15 images (left and right) will look similar. The resolution in the GOES-16 image in the center will be clearer. Note the cloud you are looking at is not very big. 

CIMSS Blog, April 4, 2017, fog/stratus dissipation Again, the fog and stratus in the GOES-16 image will be clearer.

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 (this article)

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

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

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

I want to begin with a little background on our geostationary weather satellites. Most of you know that we have a new geostationary weather satellite was launched last fall. GOES-16 -then known as GOES-R), was launched on November 19, 2016. GOES-16 is the first in the GOES-R series of satellites, GOES R-T. GOES-S is undergoing pre-launch testing and will launch in 2018. As I write this, GOES-16 is still under going in-orbit operational testing. GOES-16 represents the sixth generation of NOAA’s Geostationary satellites. The fifth generation is GOES 13-15 (GOES N - P). GOES-13 is also known as GOES East, GOES-15 is also known as GOES West, and GOES-14 is an in-orbit spare. I wrote about GOES 13-15 on November 30, 2016. I wrote a little more about GOES-16 here.


One of the instruments on GOES-16 is the Advanced Baseline Imager (aka ABI), go here to read a brief description about improvements in the GOES-R series ABI. NOAA and NASA have a nice short fact sheet that introduces GOES-R (GOES-16) ABI, it may be found here. This is one of many fact sheets on the GOES-R series. Some of you may be interested in a listing of GOES-R ABI products on the GOES-R products page, a sub-page accessible from the GOES-R mission page.


Finally, please take three minutes to watch this video, made in 2013, describing the ABI on the GOES-R series:



Direct link to video on Youtube


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 (this article)

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

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

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

Regular readers of my blog will know that I have been following GOES-16 since it was launched, then known as GOES-R, on November 19, 2016. As I learned more about GOES-16 I wondered what improvements GOES-16 and her sister satellites (GOES R-T) would bring to the detection of wildfires.   One exciting use of GOES-16 for wildfire detection is the development of an Experimental Wildfire Detection Notification Application that was first developed and used by the National Weather Service Weather Forecast Office in Norman Oklahoma. Learning about the Experimental Wildfire Detection Notification Application lead to this eight-part series on an application of GOES-16 for wildfire detection. This introduction is part 1 of 8, the rest of the articles in the series are listed below.

I start off in part 2 with a short article on the GOES-16 Advanced Baseline Imager, followed by two articles on improvements in wildfire detection with GOES-16. I then turn to the development and use of the Experimental Wildfire Detection Notification Applications in parts 5 through 7, followed by my own brief reflections in part 8.


As I post each article in the series, I will update this article with links to each article in the series.

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

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 AppWildfire Detection Notification App

Field Campaign to calibrate and test GOES-16 ABI and GLM

GOES-16 began an eleven week period of field testing to calibrate the GOES-16 instruments on March 22nd, see this March 22nd press release from NASA/NOAA for more information The March 22nd press release says in part:

During this three-month campaign, a team of instrument scientists, meteorologists, GOES-16 engineers, and specialized pilots will use a variety of high-altitude planes, ground-based sensors, unmanned aircraft systems (or drones), the International Space Station, and the NOAA/NASA Suomi NPP polar-orbiting satellite to collect measurements across the United States . . . 

Although these data are collected on Earth, GOES-16’s operators will obtain similar measurements of the same locations using two of the satellite’s most revolutionary instruments—the Advanced Baseline Imager and the Geostationary Lightning Mapper. The data sets will be analyzed and compared to the data collected by the planes, drones, and sensors to validate and calibrate the instruments on the satellite.  (http://www.goes-r.gov/mission/fieldCampaignBegins.html)

 NOAA Satellites shared a very cool video on Youtube of a NASA ER-2 over the Sonoran Desert on a March 23rd flight to validate and calibrate the GOES-16 Advanced Baseline Imager (ABI):


Direct link to video

The first phase of the GOES-16 field campaign was over on April 11th. In phase two, from April 12 to May 18, 2017, the ER-2 was based out of  Robins Air Force Base in Georgia for calibration and validation of the GOES-16 Geostationary Lightning Mapper (GLM). See this press release for more information on the first and second phases.

In the following Facebook posts from the NOAA Satellites and Information Services you will hear from some scientists about the field campaign. The videos are short. The text explanations from the folk at NOAA Satellites and Information Service that accompany each video are, I feel important. I am not sure if I was able to successfully embed the video and the text, so I have included a direct link to each post. Added on September 25 2018, I was having trouble with the audio on the videos, even tried two browsers. If this happens to you, hover your mouse at the bottom of the video and click on the microphone icon at the bottom of the video and that should toggle the sound on and off. Or click on the direct link to each facebook post.

Frank Padula, GOES-16 Project Manager explains why they are using NASA’s ER2 Direct link to facebook post.



Meterologist talking about how they will use ER2 to calibrate GOES-16 Direct link to facebook post.



Field Campaign testing of the GOES-16 geostationary lightning mapper (GLM) Direct link to facebook post.

Introduction to NASA's ER-2 "high altitude" aircraft

GOES-16 began an eleven week period of field testing to calibrate the GOES-16 instruments on March 22nd. I will be posting an article about the GOES-16 field testing campaign on June 19th. Portions of the field campaign will involve one of two NASA ER2 high altitude aircraft. So, today I will introduce NASA’s ER2 aircraft.

These aircraft are flying laboratories, each having four pressurized laboratory modules. Examples of experiments include research on ozone depletion, development of tropical cyclones, and assisting in the development and testing of satellite instruments. For more information on the ER-2, see this factsheet from NASA on the ER-2.

The ER-2 is a versatile aircraft well suited to perform multiple mission tasks. The ER-2 operates at altitudes from 20,000 feet to 70,000 feet, which is above 99 percent of the Earth's atmosphere. Depending on aircraft weight, the ER-2 reaches an initial cruise altitude of 65,000 feet within 20 minutes. Typical cruise speed is 410 knots. The range for a normal eight-hour mission is 3,000 nautical miles yielding seven hours of data collection at altitude. The aircraft is capable of longer missions in excess of 10 hours and ranges in excess of 6,000 nautical miles. The ER-2 can carry a maximum payload of 2,600 lb (1,179 kilograms) distributed in the equipment bay, nose area, and wing pods. (https://www.nasa.gov/centers/armstrong/news/FactSheets/FS-046-DFRC.html)

Here are some videos about the ER-2.

Airshow video

Direct link to video

Cockpit

Direct link to video


Take-off (no sound)

Direct link to video

Pre-operational images from GOES-16 Geostationary Lightning Mapper

On June 12th, 2017 I posted an article where I shared some videos and other information from NOAA about the Geostationary Lightning Mapper (GLM) on GOES-16. If you are arriving here first, I hope that you go back and read the article.

Before I share some pre-operational images from the GOES-16 Geostationary Lightning Mapper, I want to share a little more information about the Geostationary Lightning Mapper.  After I posted the article on June 12th, I had a chance to have an e-mail exchange with Al Cope, Science and Operations Officer of the National Weather Service Weather Forecast Office at Mt. Holly, NJ. I asked Al to share one thing that he would like you to know about the Geostationary Lightning Mapper on GOES-16. This is his response:

I would say that the Geostationary Lightning Mapper, together with ground-based lightning detection systems, will enable us to more closely monitor rapid changes in lightning activity within a thunderstorm. Rapid increases in lightning are often precursors of damaging thunderstorm winds and large hail.

NOAA Satellites released the first imagery from the GOES-16 GLM on March 6th. There is a nice press release with some information and a video that you may find here.

The information that I am sharing below are from NOAA Satellites and Information Service's Facebook Page. I believe that both of these videos of pre-operational imagery from the GOES-16 GLM may be found on NOAA Satellite's You Tube Pre-Operational GOES-16 Channel. However, I found their Facebook posts to be very illuminating, so I am embedding two of their posts below.

Intro to GOES-16 Geostationary Lightning Mapper

Those of you who are following news relating to GOES-16 may know that she is carrying a Geostationary Lightning Mapper (GLM). I'd like to introduce you to the GLM. I am embedding below two very short videos that will introduce you to the GLM, both are from NASA Goddard Media.

Direct link to video

Direct link to video

Some of you may be familiar with COMET/MetEd which offers various online courses in meteorology and related issues. Registration is free, but you need to registered to take their courses. I have taken some of the MetEd Courses over the last couple of years and have learned a lot. COMET/MetEd did a nice video on the GOES-R/16 Geostationary Lightning Mapper that I am sharing below. It takes a little under five minutest to watch the video.

Direct link to video

More information on the GOES-16 Geostationary Lightning Mapper (GLM) from NOAA's GOES-R Mission Page:

• About the GOES-R/16 GLM
• GLM Fact Sheet

Stay tuned, on June 14th, I'll share some images from the GOES-16 GLM.  Note that NOAA's GOES-16 satellite has not been declared operational and its data are preliminary and undergoing testing.

About Rhabdomyolysis and Wildland Firefighters

I hope that I never stop learning about wildfires and the risks that wildland firefighters take to protect us from wildfires. Several days ago, thanks to my friends at the B10 NJ Wildfire Page who shared a video from the Wildland Fire LLC, I learned about a medical condition known as Rhabdomyolysis and how Rhabdo (as it commonly called) affects wildland firefighters. Rhabdo can affect kidney function and sometimes leads to death. Before I share the video, Wildland Fire Lesson Learned has some materials on Rhabdomyolysis on their website that those of you who want to learn more may want to read. Wildland crew supervisors are encouraged to carry this one-pager that describes symptoms of Rhabdo that they and their crew should watch for, see the image below. Bill Gabbert of Wildfire Today has written about Rhabdomyolysis (tagged posts), I point you to the article that he posted on May 17, 2016 about an analysis by the Wildland Fire Lessons Learned Center of May 2, 2016 Rhabdo injury.

obtained on June 2, 2017 from the Wildland Fire Lessons Learned Center

Direct link to video by Wildland Fire LLC (about 21 minutes)

DC-10 and USFS C-130 arriving at Santa Maria Tanker Base

Thanks to Mike Archer at WNOTD for steering me to a nice story from KSBY with a video about the arrival of T-116, a USFS C-130 at Santa Maria Tanker Base. The C-130s were based out of Sacramento, but with the closure of that tanker base, the USFS C-130 will be based out of Santa Maria. She arrived last Saturday, joining one the 10 Tanker Carriers DC-10s which has been based out of Santa Maria for the last couple of years. Because of the wet winter, the fire season in California is expected to start later and last longer. T-116 and the DC-10 tanker (T-911?) will provide important aerial support to wildland firefighters on the ground fighting wildfires this season. Go here for the story and accompanying video. I am sorry that I could not get the embed code to work, which may be for the best as I am never sure how long videos from local media will be live.

Florida 2017 wildfire season - tribute to wildland firefighters

Many of you who are regular readers of my blog know that I have a special place in my heart for Florida. As I can, I have been following the 2017 wildfire season in Florida. According to the Wildland Fire Division of the Florida Dept. of Agriculture and Consumer Services (updated regularly to reflect current wildfire conditions), there have been 2,377 wildfires that have burned 233,923 acres in Florida from January 1 to May 29, 2017. The Florida Forest Service has a Facebook page where they have reported on wildfires. I hope that you join me in pausing to thank the man and women who have worked hard fighting wildfires in Florida in 2017.

Thanks to my friends at the B10 NJ Wildland Fire Page (video of the week, changes weekly) I learned about the following video about the Florida 2017 wildfire season, dedicated to the wildland firefighters that have worked wildfires this season. You will see some footage of tankers and helos working wildfires in support of the firefighters on the ground.


Direct link to video