A quick note on monitoring wildfire hot spots overnight. Wildfire hot spots observed in GOES-16 imagery will typically cool overnight due to a combination of poor fire weather conditions causing a decrease in fire activity, and cooling/loss of solar reflectance of the non-fire portion of the pixel causing an overall cooler pixel. Hot spots associated with active wildfires, however, will still typically be detectable in the 3.9 um shortwave IR channel though dimmer. Due to static thresholds required for RGB products in AWIPS, cool hot spots are not detectable in the current AWIPS Fire Temperature RGB. Therefore, hot spots that were previously active and detected in the RGB during the day may not be apparent in the RGB at night despite still being detectable in the raw 3.9 um imagery. This is reason for utilizing the raw imagery (3.9 um, 2.2 and 1.6 also if very hot fire) at night over the RGB. It is important for forecasters to be able to continue to monitor the evolution of wildfire hot spots overnight whenever possible. See two examples from southern Colorado during the overnight hours of 17/18 April.

The 117 Fire burned a large area of southern El Paso County during the day, continuing into the evening with 0% containment. Despite cooling significantly, the hot spot was still obvious through the night in 3.9 um imagery. The hot spot was not detectable in the Fire Temperature RGB except for a very brief period when a portion of the fire heated up.

Figure 1: 18 April 2018 GOES-16 5-min 3.9 um shortwave IR (top) and Fire Temperature RGB (bottom) over the 117 Fire in El Paso County, southeast Colorado. Darker (colored) pixels on left (right) represent the wildfire hot spot.

The Badger Hole Fire in eastern Baca County grew large quickly during the afternoon. Cooling overnight, the fire was still detectable in the 3.9 um channel, but not in the RGB.

Figure 2: 18 April 2018 GOES-16 5-min 3.9 um shortwave IR (top) and Fire Temperature RGB (bottom) over Badger Hole Fire in Baca County, southeast Colorado. Darker (colored) pixels on left (right) represent the wildfire hot spot.

Bill Line, NWS

A potent mid-level trough advanced east through the four corners and Rocky Mountain region during the day 17 April 2018. Strong southwest winds mixing down to the surface along with very low RH and dry fuels led to extreme fire danger across a large portion of the southern US Plains, including southeast Colorado (Fig 1). Wind gusts in excess of 60 mph were measured across the region within a High Wind Warning, including 68 mph at KCOS and 67 mph at KPUB. GOES-16 provided forecasters in the region with detailed views of developing wildfires and blowing dust. 1-min imagery was available in support of this event.

Figure 1: SPC Day 1 Fire Weather Outlook valid 17 April 2018.

Blowing dust originating from the Great Sand Dunes in the eastern San Luis Valley in southern Colorado was clearly apparent in 0.64 km 500 m visible imagery after 1400 UTC (Fig 2). The dust can be seen quickly spreading to the northeast over parts of Pueblo and Colorado Springs and eventually all the way to northeast Colorado within the strong southwest flow. The blowing dust prompted the issuance of a rare Dust Storm Warning by NWS Pueblo. Additionally, smoke plumes from developing wildfires are apparent, including a large fire in the southeast corner of the state.

Figure 2: 17 April 2018 GOES-16 5-min 0.64 um visible imagery. Full res

The 10.3 – 12.3 um “Split Window” difference depicts blowing dust particularly well given the increased sensitivity of the 10.3 um channel to absorption by airborne silicates. In the Figure 3, blowing dust (negative values in this difference product) is visualized by very dark gray to tan colors. This difference is utilized in RGBs to aid in dust identification.

Figure 3: 17 April 2018 GOES-16 5-min 10.3 – 12.3 um split window difference. Full res

NWS forecasters monitored for wildfire hot spots utilizing the rapid updating 3.9 um channel imagery. The 3.9 um channel is the most effective GOES-16 band for detecting wildfire hots pots. Multiple grass fires erupted across southeast Colorado  during the day, prompting evacuations in some instances. Figure 4 depicts the evolution of the wildfires during the afternoon and early evening, with dark gray to yellow pixels indicating progressively hotter hot spots.

Figure 4: 17 April 2018 GOES-16 5-min 3.9 um shortwave IR imagery. Full res

Bill Line, NWS

An impressive mid-level trough advanced across the central Great Plains on 13 April 2018 bringing a variety of weather to the region. Some of the weather hazards included blizzard conditions, blowing dust, extreme fire weather conditions, and severe thunderstorms, including an SPC Moderate Risk for severe in Arkansas. GOES-16 1-min mesoscale sectors were available to forecasters in the area during this event.

The 5-min animation in Figure 1 combines multiple GOES-16 channels into one to capture the myriad of hazards. The gray scale underlay is the 10.3 – 12.3 um split window difference (SWD). The negative difference values, or brown colors, represent lofted dust across parts of Mexico, southern New Mexico, and west Texas. The color areas overlaying the SWD is cold values of the 10.3 um IR channel. Apparent are clouds associated with snow across Colorado and northward, and severe thunderstorms to the east. Finally, the small yellow areas are hot 3.9 um pixels, capturing the wildfires across western Oklahoma.

Figure 1: 13 April 2018 GOES-16 5-min SWD, 10.3 um IRW, 3.9 um SWIR. See text for details. Full res

Bill Line, NWS

Extreme fire weather conditions developed across portions of CO/KS/NM/TX/OK on 12 April 2018 as winds increased and RH values decreased over dry fuels ahead of a trough digging into the four corners region. SPC highlighted a large area of extreme fire weather conditions in their fire weather outlook, along with an even broader critical area (Fig 1). Given the threat, both GOES-16 1-min meso sectors were requested and granted. SPC extreme fire weather outlook is priority number 6 for mesoscale sector requests in the case of multiple requests.

Figure 1: 12 April 2018 SPC Day 1 Fire Weather Outlook. Full res

Some of the largest and most threatening wildfires developed across western Oklahoma during the afternoon. GOES-16 1-min visible imagery captured the impressive smoke plumes under an otherwise clear sky (Fig 2), while the 3.9 um channel depicted the hot spots (Fig 3). The 1-min imagery allows for the detection of wildfires early in their development. This  capability is being used in some NWS offices to alert fire weather partners to new fire starts, sometimes prior to 911 calls.

Figure 2: 12 April 2018 GOES-16 1-min visible satellite imagery. Full res

Figure 3: 12 April 2018 GOES-16 1-min 3.9 um shortwave IR imagery. Dark gray/black to yellow are progressively hotter fires. Full res

Pyro-cumulus clouds were observed in the 1-min VIS with one of the Oklahoma fires a little later in the early evening hours (Fig 4).

Figure 4: 12 April 2018 GOES-16 1-min VIS of smoke plume over W Oklahoma. Full res

Bill Line, NWS

With a moderate risk for severe thunderstorms across the southeast US on 19 March 2018, 30-sec GOES-16 imagery was made available over the region. SPC High or Moderate risk for severe is the number 1 priority for mesoscale sector requests.

Figure 1: 19 March 2018 GOES-16 30-sec visible imagery over northern Alabama. Full res

A tornado was confirmed with storms a little later in the evening. 30-sec IR imagery captured persistent overshooting tops and rapid anvil expansion with these storms indicating strong updrafts.

Figure 2: 19 March 2018 GOES-16 30-sec IR imagery. Full res

• Bill Line, NWS

For those working at higher elevation offices, have you ever noticed surface features (e.g. lakes, rivers) in satellite imagery displaced slightly horizontally (lat/lon) from their designation in a placefile (a.k.a. from where they “should” be)? This is, in fact, normal behavior for satellite imagery. In brief, a satellite imager assumes a constant, low elevation across the viewing plane.  When viewing the earth at an angle, therefore, higher elevation surfaces (and associated features) will be displaced a distance radially away from the satellite subpoint. The displacement of a given target will be a function of the elevation and distance from the satellite subpoint. The further away from the satellite subpoint and the greater the elevation, the greater the displacement will be. See figure 1 for details. The displacement is rarely more than a few km.

Figure 1: Graphical depiction of elevation displacement for three viewing scenarios. Full res

We analyze an example using GOES-16 visible imagery (Fig 2). A series of lakes across the southeast Colorado plains, elevation around 4,000 ft above sea level, are displaced a couple hundredths of a degree latitude and longitude north and west from the actual lat/lon location. The distance is slightly less than 1 km. From GOES-West (not shown), these features are displaced a similar distance to the north and east. In all examples below, lakes will appear dark gray, and solar farms will appear bright gray to white.

Figure 2: GOES-East visible imagery over southeast Colorado. Lake contours overlaid.

In the San Luis Valley, a high valley in southern Colorado, lakes and a solar array are displaced closer to 2 km from their actual position due to the higher elevation (~7,500 ft) and further distance from satellite subpoint (Fig 3).

Figure 3: GOES-East visible imagery over San Luis Valley, Colorado. Lake and Solar Farm contours overlaid.

Lakes in California, further west from the satellite subpoint but at lower elevation (1,000 ft – 1,500 ft), show very little displacement (Fig 4).

Figure 4: GOES-East visible imagery over southern California. Lake contours overlaid.

Lakes in Florida, closer to the satellite subpoint and at around sea level, have no apparent displacement from their actual location (Fig 5).

Figure 5: GOES-East visible imagery over Florida. Lake contours overlaid.

Comparing GOES-East and GOES-West using Bear Lake, ID/UT at around 6,000 ft as a high elevation landmark, the horizontal shift is quite obvious (Fig 6). From GOES-East, the lake (and surrounding terrain features), are shifted considerably to the north and west of the actual lake location. From GOES-West, the lake (and surrounding terrain features), are shifted similarly to the north and east of the actual lake location.  Disclaimer: navigation issues with GOES-15 (current GOES-West) causes the image to bounce around. A time was chosen when the ocean coastlines appeared closest to accurate.

Figure 6: 10 March 2018 GOES-16 (East) and GOES-15 (West) visible satellite imagery at 1617 UTC and 1615 UTC, respectively. Full res

The displacement may be relatively small, but is an important consideration for high elevation offices when completing tasks that identify the precise lat/lon of a surface feature. One example of such a task is the identification of a wildfire hot spot, and subsequent notification (with lat/lon of hot spot) to partners. High elevation Rocky Mountain offices completing such a task should consider placing their hot spot “point” identifier on the southeast part, or just to the southeast, of the hottest pixels in the hot spot when using GOES-East imagery for detection.

Bill Line (NWS) and Eric Guillot (NWS)

The third nor’easter in less than two weeks was poised to have significant impacts from the Ohio River Valley up through the northeast US March 12-14.

GOES-16 1-min imagery captured the evolution of the system in detail, starting with it’s strengthening across the Ohio River Valley on March 12. 500 m, 1-min visible imagery at sunrise revealed fresh snow cover from southern Illinois through southern Indiana and into much of Kentucky (Figure 1).

Figure 1: 12 March 2018 GOES-16 1-min visible imagery. Full res

Bill Line, NWS