A long line of severe storms impacted a broad region extending from Texas to Wisconsin on 21 October 2017. The destructive storms developed along a cold front in association with a high amplitude large-scale trough advancing out of the Rocky Mountain region. Ahead of the cold front, strong southerly flow drove anomalously high levels of moisture north, and combined with warm temperatures, led to a long corridor of high instability. Deep layer shear under strong flow aloft also supported the development and maintenance of robust updrafts.

The strongest of storms were centered in Oklahoma where the greatest instability developed, necessitating an SPC Enhanced Risk for Severe Thunderstorms. Initial, large-hail-producing supercell thunderstorms transitioned to linear modes and a damaging wind threat as the cold front pushed southeast. Given the severe risk, a GOES-16 1-min Mesoscale Domain Sector (MDS) centered over Oklahoma was requested by the Storm Prediction Center.

GOES-16 imagery and products provided forecasters with valuable information even before the first storms develop. Water vapor imagery revealed the progression and amplification of the upper-level trough through the Rocky Mountain Region during the previous evening and morning hours (Fig 1). Prior to initiation, increasing moisture and instability was analyzed in GOES-16 TPW and CAPE fields (Fig. 2). Strengthening deep layer shear could be diagnosed in Oklahoma using the Derived Motion Winds (DMWs) and surface observations (Fig. 3).

Figure 1: 21 October 2017 GOES-16 UL WV, ML WV, IRW, LLW (cw starting upper right). Full res

Figure 2: 21 October 2017 GOES-16 IR, CAPE. Full res

Figure 3: 21 October 2017 GOES-16 DMWs and VIS. Full res

Careful analysis of GOES-16 1-min visible imagery reveals areas where the atmosphere is destabilizing and convective initiation is becoming imminent (Fig X). Ahead of the cold front, transition of low stratus stable wave clouds (perpendicular to low-level flow) to cumulus cloud streets (parallel to low-level flow) indicated destabilization was taking place, but that the atmosphere was still capped.  The exact location and progression of the cold front was easily tracked in the visible imagery among the abundant high and low clouds. Convective initiation appeared more and more likely as cumulus clouds along the front exhibited increasingly vertical growth.

Figure 4: 21 October 2017 GOES-16 5-min VIS. Full res

1-min imagery from GOES-16 is the first indicator that convective initiation is about to occur or is occurring. As can be seen in Figure 5, convection developed quickly along and ahead of the cold front during the mid afternoon hours.

Figure 5: 21 October 2017 GOES-16 1-min VIS. Full res

Creative displays allow forecasters to extract the maximum amount of useful information from GOES-16, quickly. The VIS/IR image sandwich combo combines the high resolution VIS with the quantitative information from IR into one display (Fig. 6).  This image combo allows a forecasters to effectively monitor the health and evolution of a storm through the analysis of  relevant storm top features and processes such as overshooting tops, enhanced V’s, cloud top cooling, and cloud top warming.

Figure 6: 21 October 2017 GOES-16 1-min VIS/IR sandwich combo. Full res

GOES-16 IR window channel shows convection develop and quickly organize into a quasi-linear convective system along the cold front (Fig. 7).

Figure 7: 21 October 2017 GOES-16 5-min 10.35 um IR window channel, warning polygons. Full res

The TPW, CAPE, and DMW products should continue to be monitored for information about the environment into which mature storms are moving.

-Bill Line, NWS

“The GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing. Users bear all responsibility for inspecting the data prior to use and for the manner in which the data are utilized.”

GOES-16 Derived Motion Winds (DMW’s) have been available to forecasters in AWIPS for a few months now. These winds are computed from the motion of clouds and moisture features in satellite data. Given the higher spatial, temporal, and spectral resolution of the GOES-R ABI, more winds can be computed spatially and vertically than with previous GOES satellites. These winds can be quite beneficial to forecasters. A few examples include: gauging NWP model performance, identifying localized jet streaks, and computing layer shear.

Unfortunately, the initial display of the winds in AWIPS-II leaves something to be desired (Figure 1). Loading each individual layer of winds yields three products: <30 knots, 30-50 knots, >50 knots. I believe this is unnecessary considering the wind bard itself tells you the speed. One product for all the winds in that layer would suffice. When loading all layers, the list is quite large. These barbs are color-coded by speed.  I would prefer to load each layer of wind data, and have them color coded by layer. As for sampling, the pressure level of the individual wind is not included, and the direction and speed not labeled.

Figure 1: 1933 UTC 19 October 2017 GOES-16 Derived Motion Winds (barbs), IR imagery (image), and point sampling. This is the current display in AWIPS-II.

I decided to have some fun and make these changes myself (Fig 2). I load only one product per wind layer, and color code by layer. In the sampling, I include the pressure level of the individual wind, and I label the direction (degrees) and speed (knots). This display is much cleaner and more useful to the forecaster. If you have any suggestions, feel free to let me know!

Figure 1: 1933 UTC 19 October 2017 GOES-16 Derived Motion Winds (barbs), IR imagery (image), and point sampling. This is a proposed display in AWIPS-II.

The GOES-16  Derived Motion Winds highlighted some of the key ingredients on 10/20/2017 that would lead to widespread severe storm development the next day across the southern plains (Fig. 3). The winds outlined an upper-level trough digging through the western US. Advancing into the scene toward northern California was a strong upper-level jet, with a couple barbs over 130 knots. This verifies the strength and timing of the 18z GFS NWP model forecast of the jet progression. Further east from Texas north through Oklahoma and Kansas, potent low-level return flow of 20-35 knots was analyzed in the wind field.

Figure 3: 20 October 2017 GOES-16 Derived Motion Winds (barbs colored by pressure level) and UL WV imagery (image). This is a proposed display for AWIPS-II. Full res

-Bill Line, NWS

“The GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing. Users bear all responsibility for inspecting the data prior to use and for the manner in which the data are utilized.”

The wildfires across California have been covered extensively by the news and social media lately. The Lion wildfire had burned 15,450 acres by early 13 Oct 2017 in Tulare County in central California. This wildfire was in a remote area in the southern Sierra mountains in the Sequoia National Forest, so firefighters would let it burn. It’s position in the middle of the Kern River valley and abundant smoke provided a great visualization of up-valley/down-valley winds (Fig. 1).

Figure 1: Graphical depiction of mountain valley winds courtesy of COMET.

At night well after sunset and under an inversion, draining of cold air off the slopes (katabatic winds) converges in the valley and creates relative high pressure, accelerating down-valley. During the day, the slopes and valley floor are heated, creating relative low pressure and upslope and up-valley flow. The smoke from the Lion fire could be seen flowing down-valley just after sunrise in GOES-16 visible imagery (Fig. 2). After a few hours of heating under clear skies, the smoke reverses course and begins to move up-valley. The inversion eventually breaks leading to smoke being dispersed out of the valley as well. The high temporal (5-min) and spatial (0.5 km) resolution from GOES-16 visible imagery and presence of wildfire smoke allowed for this mountain meteorology process to be clearly visualized. Such a reversal of winds in the vicinity of a wildfire is important information for firefighting efforts.

Figure 2: 13 October 2017 GOES-16 0.64 um visible satellite imagery in Tulare County, CA. Full res

-Bill Line, NWS

“The GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing. Users bear all responsibility for inspecting the data prior to use and for the manner in which the data are utilized.”

During the morning of 10 October 2017, NWS Pueblo forecasters noticed a small, very bright (high reflectance) signal in the GOES-16 visible channels in the San Luis Valley of southern Colorado (Fig. 1). Interrogating further, the localized area appeared relatively warm in the 3.9 um channel (Fig. 2) and had relatively high reflectance in the 0.86 um, 1.38 um, 1.6 um and 2.2 um near-IR channels.

Figure 1: 10 October 2017 GOES-16 0.64 um VIS. Arrow points to area of reflectance off solar energy generating facility. Full res

Figure 2: 10 October 2016 GOES-16 3.9 um shortwave IR. Full res

After quickly ruling out a cloud, wildfire, explosion, and alien invasion, it was determined that this phenomenon was very high reflectance off of a smooth surface feature. There was no smoke in the VIS, and a wildfire hotspot would not exhibit such high reflectance, especially so early in the life of the fire. This phenomenon know as “sunglint” most often occurs off of a calm water surface given the high degree of smoothness, but can occur off of smooth land surfaces as well.  Interrogation of google earth revealed this feature was in fact a Solar Energy Generating Facility (Fig. 3)! The angle of the sun during that period of day lined up just right with that of the solar panels to have its sunlight reflected directly into the GOES-16 ABI.

Figure 3: Google Earth satellite view of Solar Energy Generating Facility in the San Luis Valley, CO

After some investigation, two other solar farms were found causing the same phenomenon in GOES-16 imagery. The Ivanpah Solar Power facility is located in southeast California near the Nevada border in the Mojave desert, and is a concentrated solar thermal plant. As of 2014, this was the world’s largest solar thermal power station. The reflectance signatures and hotspots were picked up by GOES-16 during a similar period as was found in Colorado (Fig. 4).

Figure 4: 12 October 2017 GOES-16 0.64 um 5-min VIS over Ivanpah facility southwest of Las Vegas near California/Nevada border. Full res

The Crescent Dunes Solar Energy facility in west central Nevada also had a reflectance and hotspot signature detected by GOES-16 (Fig. 5). This facility is also a concentrating solar power plant. Interestingly, the reflectance and hotspot signatures were detected in GOES-16 imagery at this plant from sunrise through early afternoon, much longer than the other two facilities. Why? Perhaps the angles of the large number of panels must vary considerably to be reflecting energy toward GOES-16 for such a long period of time. Or, maybe the solar power central towers are so bright that they are picked up by GOES-16. Neither explanation, however, explains why the Crescent Dunes signal was picked up for such a long period but the Ivanpah signal was significantly more brief.

Figure 4: 12 October 2017 GOES-16 0.64 um 5-min VIS over Crescent facility near Tonopah in central Nevada. Full res

-Bill Line and Tom Magnuson, NWS

“The GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing. Users bear all responsibility for inspecting the data prior to use and for the manner in which the data are utilized.”

Areas of dense fog impacted southern Colorado during the evening and early morning hours of 05 October 2017. A moist airmass and weak upslope flow allowed for low clouds and fog to quickly develop during the evening of the 4th in the vicinity of the I-25 corridor between Colorado Springs and Pueblo. GOES-16 Nighttime Microphysics imagery, discussed in previous blog posts, was utilized to monitor the development and evolution of the low clouds and fog (Fig 1).

Figure 1: 05 October 2017 GOES-16 Nighttime Microphysics RGB. Full res

There was, however, another tool available to forecasters to aid in fog analysis during a period of the very morning hours: The Suomi NPP VIIRS Near Constant Contrast Imagery. This channel, also known as the Day Night Band (DNB), uses primarily moonlight and starlight to allow for visible imagery at night. Because the DNB has a horizontal spatial resolution of 750 m, it provides more detail than is available from the 2 km GOES-16 IR nighttime products. The key negative of DNB is that because it is a polar-orbiting satellite, a given location over the CONUS will typically receive only one scan at night and one scan during the day. However, many locations will see overlap between scans on occasion, as was the case over eastern Colorado early on the 5th. Additionally, city lights make it difficult to diagnose some features such as clouds in urban areas.

VIIRS swaths were available over eastern Colorado at 0800 UTC and 0942 UTC on 05 October 2017 (Fig 2). Not only did the DNB allow for a higher resolution view of the low clouds and fog impacting southern Colorado, but the sequence of two images provided a glimpse into how the fog was evolving. One can see that the fog in the Colorado Springs area and along I-25 between Colorado Springs and Pueblo had dissipated, while fog had increased within the Arkansas River Valley from Canon City through Pueblo and east of Pueblo.

Figure 2: 0800 and 0942 05 October 2017 Suomi-NPP VIIRS Day Night Band Imagery.

Comparing the VIIRS DNB with GOES-16 Nighttime Microphysics RGB at 0942 UTC, the higher spatial detail of the DNB more precisely pinpoints the position of the fog and better detects areas of very thin/shallow and narrow fog (Fig 3).

Figure 3: 0942 UTC 05 October 2017 VIIRS DNB and GOES-16 Nighttime Microphysics RGB comparison. Full res

Figure 4 combines the VIIRS DNB images with the GOES-16 RGB imagery.

Figure 4: 05 October 2017 Suomi NPP VIIRS DNB and GOES-16 Nighttime Microphysics RGB. Full res

JPSS-1 will launch later this year and will provide similar capabilities to that of Suomi-NPP.

-Bill Line, NWS

“The GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing. Users bear all responsibility for inspecting the data prior to use and for the manner in which the data are utilized.”

Hurricane Maria made landfall in Puerto Rico early on 20 September as a strong category 4 Hurricane, packing maximum sustained winds of 155 mph. The island received significant damage, including the loss of both radars (TSJU and TJUA). Given the vast devastation, WFO Miami was providing service backup for Puerto Rico. Without radar coverage over the island, forecasters needed to rely heavily on other datasets such as satellite imagery from GOES-16. To provide the best/most information possible, a GOES-16 1-min mesoscale sector was available continuously over Puerto Rico.  Having this sector was especially important because, from checkout position, the GOES-16 5-min CONUS sector coverage ends halfway across Puerto Rico (Fig 1). Outside of that sector, coverage is 15-min.

Figure 2: 30 September 2017 GOES-16 1-min VIS/IR sandwich image combination. Full res:

On 30 September, a tropical wave interacting with an upper-level trough was producing strong thunderstorms near Puerto Rico. Given the expected heavy rain and already saturated soils, a flash flood watch was issued for the island. During the morning, strong thunderstorms were oriented just south of the island. The appearance of these storms in satellite imagery led to the issuance of a Special Marine Warning per warning text (SOURCE…SATELLITE IMAGERY INDICATED). The 1-min GOES-16 IR/VIS sandwich image combo shows the burst of thunderstorms and warning product.

Figure 2: 30 September 2017 GOES-16 1-min VIS/IR sandwich image combination. Full res: https://satelliteliaisonblog.files.wordpress.com/2017/09/20170920_pr_1min1.gif

-Bill Line, NWS

“The GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing. Users bear all responsibility for inspecting the data prior to use and for the manner in which the data are utilized.”

In May, it was announced that GOES-16 would become GOES-East late in the calendar year. This week, detailed drift plans were released!

• GOES-16 will begin drifting from the checkout position (89.5W) on 30 November, reaching the GOES-East position (75.2W) on 11 December. After a period of calibration, the satellite will return to operations as GOES-East on 14 December.
• GOES-16 ABI, GLM, SUVI, SEISS, and EXIS data will not be available between 30 Nov and 14 Dec.
• GOES-13 (current GOES-East) will remain at 75W until 2 January, when it will begin drifting to its storage location at 60W. It will reach the storage location on 22 January.

-Bill Line, NWS

“The GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing. Users bear all responsibility for inspecting the data prior to use and for the manner in which the data are utilized.”