Very dry and breezy conditions developed across southeast Colorado during the afternoon of 20 May 2020 ahead of a broad western US upper trough and behind a surface dryline. With deep vertical mixing occurring behind the dryline, RH values fell to around 10 %, and winds gusted 30-40 knots. A wildland grass fire initiated north of Kim, CO during the early afternoon.

A GOES-East 1-min meso sector was available over a region including the wildfire during the day in support of convective warning operations (Fig 1). A watchful eye would notice the flickering of a faint hot spot below thin cirrus clouds by around 1945 UTC. With 5x more images , a forecaster can be more confident in wildfire detection earlier when using 1-min imagery over 5-min imagery. A simple gray-scale color table applied to ABI single-band 3.9 um imagery has proven to be a very reliable method for detecting wildfire starts, especially when 1-min imagery is available.

Later, as the fire continued to grow, an impressive smoke plume developed. The 1-min visible imagery shows the rapid growth of the plume, and even development of pyrocumulus adjacent to a colder cloud shield. IRW brightness temperatures associated with the pyrocu reached -20C shortly after 0100 UTC.

A long animation of the wildfire combines visible, SWIR and IRW imagery along with RAP surface analysis RH and wind gust fields for the duration of the event. The animation shows the fire initiating as wind gust speeds increase over 30 knots and RH values drop below 15%. The fire continues to burn hot well after sunset, before decreasing in intensity as wind speeds died down and RH values rose.

A 4-panel image of the wildfire and smoke plume during the early evening provides a variety of unique RGB displays for tracking the hot spot and associated smoke plume in unison. At this time, the hot spot was quite expansive, and pyrocumulus developing within the smoke plume.

S-NPP and NOAA-20 VIIRS imagery also captured the wildfire during it’s early stages, and during the evening. The same gray scale color table is used for each VIIRS/ABI image pair.

The 375 m I-4 band (3.74 um) imagery captured the wildfire earlier than was possible in the 2-km ABI imagery, and pinpointed it to a smaller region (a single dark pixel at 1915 UTC; Fig 5). At 2000 UTC, the fire had spread to a few pixels, but was still quite faint in the ABI imagery. However, as was shown, the animations of 1-min ABI imagery (not possible with VIIRS) allowed for confident detection of a hot spot by this point. By 2051 UTC, the wildfire hot spot was obvious in both VIIRS and ABI, but with VIIRS narrowing down the location to a much smaller area.

During the evening, both instruments continue to detect heat associated with the wildfire/burned area, with VIIRS pinpointing the burn region more precisely (Fig 6).

Bill Line (NESDIS and CIRA) and Mike Umscheid (NWS DDC)

Two rounds of severe convection developed over the Texas Panhandle during the afternoon and then evening of 07 May 2020. Storms developed amid increasing forcing associated The Amarillo NWS forecast office (AMA) utilized GOES-East imagery to track development.

GOES-East water vapor imagery highlighted a well-defined upper low digging southeast into the central US plains, with periodic and much more subtle perturbations in the W/NW flow to it’s south (Fig 1). Large scale forcing associated with these features aided convective development along surface/low-level boundaries.

The first round of severe storms developed over the southeastern portion of the Texas Panhandle along a dryline during the afternoon. Leading up to convective initiation, the AMA forecasters monitored the 1-min Day Cloud Phase Distinction RGB imagery for signs of imminent convective initiation (Fig 2). By 2055 UTC, it was apparent from the imagery that convective initiation was most most likely in the near-term over the southeast portion of the panhandle along the AMA/LUB county warning area (CWA) border. The cumulus cloud field was well established and maturing, cloud color was transitioning from cyan to green (glaciation), and orphan anvils were generated (failed initiation attempts). Shortly thereafter, deep convection initiated successfully just south of the CWA border in LUB’s area.

Forecasters from AMA noted the value of 1-min VIS/IR sandwich combo imagery as the convective scenario evolved (Fig 3). Of note early on was a new, stronger updraft developing ahead of the original updraft, quickly producing an above anvil cirrus plume. By 2216 UTC, a new updraft developed ahead of the main storm per cooling of cloud tops and increased cloud texture. This area of convection developed within the AMA CWA and forced the issuance of a severe thunderstorm warning. A storm split was apparent in the imagery a little later, by 2230 UTC, with continued cooling of cloud tops on the northeast cell (left split) and development of an OT. The right split accelerated to the southeast and maintained a large OT and prolific AACP. Forecasters noted the early signs of new updraft development and storm split were apparent in the 1-min satellite imagery just prior to radar.

An uninterrupted loop overlays MRMS MESH on the sandwich imagery, revealing the long hail swath associated with the main cell and right split, and apparent hail development from the forward convection in the southeast corner of AMA CWA, and eventually with the left split (Fig 4).

Later on that evening, additional convection developed across SW KS and the OK/TX Panhandles along a cold front within increasing large scale forcing for ascent ahead of the aforementioned shortwave. AMA forecasters noted the value of the 10.3 um IR window channel at night for analyzing this second round of convection (Fig 5). The imagery was utilized to identify the main updrafts of the stronger cores aloft given the appearance of overshooting tops, and to infer which updrafts were more likely to sustain themselves given cloud top IR temperature trends.

An animation of grayscale IRW and GOES-derived CAPE for the full-duration of the event shows a corridor of increasing instability ahead of the dryline during the afternoon, along/within which the initial round of convection developed and evolved. Instability remained high to the north ahead of the pressing cold front, with the second round of convection developing along the northwest CAPE gradient (cold front) as analyzed in the satellite product.

This blog post from CIMSS highlights the value of NUCAPS products from this event.

Bill Line (NESDIS and CIRA) and Kaitlin Rutt (NWS AMA)

Strong winds on the western portion of a deep surface low in association with an exiting shortwave trough resulted in lofted/blowing dust from the IA/NE/MO/KS Missouri River Valley (MRV) southeast across central Missouri. This is a favorable region for winds to go unimpeded, and the lofted dust is likely due in part to sedimentation/silt left behind from the big spring flooding of 2019. Further, it is still early in the planting season, so fields are susceptible to having dirt erosion. Local media shared photos of blowing dust across I-29, which runs along the eastern side of the MRV (Fig 1).

The Omaha NWS office noted the blowing dust on social media in the nighttime microphysics RGB (Fig 2). This RGB is effective in detecting lofted dust due primarily to the inclusion of the 12.3-10.3 um split window difference (SWD), which has been shown to be an effective ABI channel combination for dust detection (see previous blog post).

Given the conditions, the NWS in Omaha issued a Special Weather Statement for “reduced visibility due to blowing dust” along I-29, and the NWS in Pleasant Hill mentioned, “reductions in visibility as a result of the blowing dust” in their Wind Advisory.

The SWD-IR combo procedure perhaps provides the best depiction from ABI of the blowing dust across the region for the duration of the event (Fig 3). The blowing dust appears as very dark gray to black (very low positive or negative difference values), while most clouds will appear as colors with the inclusion of cold brightness temperatures from the IR window channel. Small cumulus clouds will be lighter gray) The lofted dust is diagnosed to initiate near northwest Missouri in the presence of a tight surface pressure gradient and 40+ knot wind gusts. The lofted dust is carried southeast over I-29 and into central Missouri as it wraps around the southwest and southern portion of the surface low. The animation, lasting 10 hours, depicts the long duration of this event.

The blowing dust can also be diagnosed in the 500 m 0.64 um VIS channel. The color table used is modified to highlight lofted material (Fig 4). The blowing dust becomes most apparent near sunset, when forward scattering of dust particles toward the satellite is heightened.

Finally, a modified Dust RGB provides a great depiction of the blowing dust, while capturing cloud details as well (Fig 5). In this example, the dust appears as deep magenta, low/cumulus clouds dark blue, stratus or mid-level clouds as red, and cirrus clouds as black. The RGB recipe is shown in Fig 6.

SNPP and NOAA-20 consecutive overpasses provided higher resolution (750 m vs 2 km for GOES) VIIRS M-band SWD imagery near the beginning of the event, allowing for slightly more details (spatially) to be gleaned from the lofted dust. (Fig 7).

Bill Line (NESDIS and CIRA) and Andrew Ansorge (NWS DMX)

Severe thunderstorms developed across the southern plains on 4/22/2020 in association with a shortwave trough traveling east across the TX PH, OK, and N TX. GOES-East water vapor imagery shows the evolution of the large scale feature and associated thunderstorm development, with RAP analyses quantifying the wave and it’s influence on the surface pressure and surface/mid-level wind fields (Fig 1). The vorticity max becomes increasingly well-defined as it accelerates east across OK, with associated dry descending air through west Texas and moist ascending air over east TX/OK into the southeast US. Additional imagery from some of the notable thunderstorms will be highlighted in this blog post.

Thunderstorms were ongoing across the northern half of OK and initiating across the southern half of Oklahoma during sunrise on the 22nd. Analyzing GOES-East 1-min visible imagery, shadows associated with the low sun angle provided excellent detail about storm initiation and storm top features such as overshooting tops (OTs), above anvil cirrus plumes (AACPs) and anvil gravity waves (Fig 2).

During the early-mid afternoon hours on the 22nd, additional convection developed across southern Oklahoma near the interface of a dryline/cold front/warm front surface triple point. A GOES-East 1-min VIS-IR sandwich combo allows for a more detailed analysis of the thunderstorms than a either single channel alone (Fig 3). This sandwich combo was created using a VIS linear color scale with a semi-transparent IR overlay, and can be found on the STOR VLAB page. The procedure maintains details from the VIS while also including quantitative information from the IR that can be visualized and sampled. Features such as OTs and AACPs, as well as cooling/warning trends, are easily diagnosed in the imagery. Numerous NWS severe thunderstorm and tornado warnings were issued with these storms, and are shown in the animation. Note, while the base of the storms fall within the polygons, the storm tops are oriented north of the polygons due to parallax. These storms did produce tornados, severe hail, and severe wind gusts.

Further south in east Texas, a long-lived severe thunderstorm produced a track of tornado and severe hail/wind reports. This storm had an impressive appearance in GOES-East imagery, with persistent and large OTs, long-lived AACPs, and very cold tops (<-80C at times). A simple procedure in AWIPS combines the aforementioned VIS-IR sandwich combo with IR imagery to allow for a smooth transition between the two products (make the low end of the VIS transparent). A 2-hour animation of GOES-East 1-min imagery centered over the the storm using this procedure is shown in Figure 4.

A longer, 5-min animation shows the full 10-hr duration of the storm, and instead uses the “Daylight Transition” image combination feature available in AWIPS (Fig 5). Feature-following zoom is also used to provide a storm relative view of convective evolution.

Finally, a similar animation but highlighting GLM Flash Extent Density is available in Figure 6. The storm consistently produces an abundance of total lightning, with periodic lightning jumps/dips throughout the evolution.

Bill Line, NESDIS/CIRA

During the evening of April 21, 2020, several supercells developed in the Texas Panhandle into western Oklahoma producing hail resulting in numerous reports. Not only was the size of hail large, the amount of hail that fell was significant as noted by reports of accumulated hail of several inches deep. As storms snailed away from their deposited hail swaths, GOES-16 was there to view these swaths. This post will showcase how forecasters can view freshly deposited hail swaths using multispectral imagery at night.

Figure 1 depicts the Nighttime Microphysics RGB with the “clean” longwave infrared band (Band 13, 10.3 um) overlaid while making any temperatures warmer than -25 C transparent. This allows for cloud layer and phase information to be provided within the Nighttime Microphysics RGB while also monitoring very cold cloud top temperatures associated with severe storms as well as overshooting tops denoting an updraft penetrating into the tropopause. As the convective clouds and overshooting tops pull away from the border of the Texas Panhandle and western Oklahoma, notice one to three subtle, magenta-colored lines oriented northwest to southeast as skies clear (see annotated images here and here). These lines correlate well with highest reflectivities that had passed over previously in time as well as with storm reports of hail. These lines are a result of altered environmental and ground temperatures (in this case cooling) from the copious amounts of hail left behind their parent storms.

While the default composition ranges of the Nighttime Microphysics RGB within AWIPS-2 allow for just subtle signatures within the imagery, there is room for adjustment to enhance this signal. A good place to start is by looking at a 4 panel display of the RGB (Figure 2) being discussed and each of the its components set to a black to white scale with the RGB’s default ranges.

Sample the signal in question within each of the RGB’s components and adjust the range within the components until there is good contrast between the signal and background. Once the component’s ranges are adjusted to your liking, adjust them within the RGB itself. In this case, there was room for improvement mainly within the red component (the Split Window Difference, 10.3-12.3 um) and the blue component (“Clean” IR, Band 13, 10.3 um). However when adjusting the red component, the RGB itself became too saturated in red coloring. Therefore we can tone down the saturation of red by lowering the red component’s gamma. Figure 3 is what the new composition looks like now (click here for actual recipe values).

Do you think the hail swaths show up better in the adjustments as shown in Figure 4? Making an adjustment on the fly works in this case, but might not for all cases. Thus adjustments to RGBs are advised to only be made on a case by case basis, especially with those having a large dependency on infrared temperatures. It is also worth noting that this approach of using multispectral satellite imagery to observe accumulated hail swaths is dependent on cloud-free skies as well as enough hail to actually make an alteration to the ambient environmental and ground temperatures.

So how does this apply to IDSS? Well besides increasing overall situational awareness, noting hail swaths in near real time lends confidence in derived products like MRMS MESH tracks through observations. This could also allow forecasters to help core partners like DOT maintenance crews target areas for hail removal should they request it. Additionally, this could also provide an opportunity for target LSR intel gathering, or even safety messaging as accumulated hail can produce hazardous travel conditions through slick roadways and reduced visibility should hail fog form (which by the way is also detectable in this approach through the use of the 3.9-10.3 um “Fog/Low Stratus” Brightness Temperature Difference as the Nighttime Microphysics RGB’s green component).

Carl Jones
Meteorologist
NWS Grand Forks

Severe thunderstorms developed across the southeast US ahead of a potent shortwave trough during the day/evening of 19 April 2020. Water vapor imagery captured the strengthening shortwave as it accelerated east across the southern plains and into the southeast (Fig 1). RAP analysis overlay helps to quantify the shortwave, revealing the sharpening 500 mb trough in the height field, increasing 500 mb wind field ahead of the wave (including wind speeds over 70 knots), and the vorticity max.

By the late evening hours, the primary region of thunderstorms had shifted east into Alabama, Georgia, and the Florida Panhandle. Unfortunately, NWS TAE required emergency backup during a period covering at least 0545 – 0745 UTC, resulting in NWS Houston taking over warning issuance. To make matters worse, data from area radars was unavailable/intermittent to forecasters, primarily during the ~0600 UTC to 0700 UTC timeframe (Fig 2). Therefore, the warning forecaster was required to rely on satellite and lightning data for warning decisions.

The primary tools used following the loss of radar data was GOES-East IR imagery (Fig 3) and total lightning data from Earth Networks (not shown in examples), and later, GLM (Fig 4) as well. Cloud top trends in the IR imagery were monitored closely, including brightness temperature trends and overshooting tops. Persistence of overshooting tops and cold temperatures for storms that had previously appeared strong/severe in radar (and were warned on) aided confidence in continued warning issuance, as did rapid increases in lightning activity. Similarly, warming of storm tops, loss of OTs, and decreases in lightning density provided confidence in letting warnings expire.

Earth Networks lightning data was also used to account for parallax in the satellite imagery, helping a forecaster determine more accurately where the updraft core was located geographically. In this case, storm tops would have been displaced roughly 10-14 km to the NNW in the GOES-East imagery and GLM data.

***AWIPS display/procedures shown in this blog post were created after the event, and are similar but not exactly that used by the warning forecaster***

Bill Line (NESDIS and CIRA) and Sean Luchs (NWS HGX)

A hail storm moved south-southeast across portions of southwest Kansas during the late afternoon hours of 19 April 2020. This storm produced copious amounts of hail along a path of about 15 miles.

The evolution of the cu field across central Kansas can be analyzed in detail using the the GOES-East Day Cloud Phase Distinction RGB. The cu field evolves from flat, liquid clouds (cyan), to a more agitated cu field with clumping clouds and enhanced vertical growth and glaciation (green; Fig 1). With convective initiation, vertical growth is rapid, and cloud tops transition to yellows and reds with cooling and continued glaciation of cloud tops. A glimpse of the hail swath (green) is seen in the wake of thunderstorms, east of Kinsley.

The sky cleared off just enough prior to sunset such that an enhanced version of the GOES-East Day Cloud Phase Distinction RGB product could remotely sense the hail swath (Fig 2).

Numerous pictures of significant hail accumulation were received by NWS Dodge City on social media, some of which showing 4 to 5 inches of accumulation (Fig 3).

The hail swath stuck around through the cool evening hours, and was still apparent in GOES-East imagery the following morning (Fig 4, Fig 5).

GOES-East provides a fairly high resolution confirmation as to where exactly accumulating hail fell following passage of a thunderstorm and clearing of clouds. While MRMS provides a good estimate to where hail fell and how large it was, it doesn’t lend much detail about hail accumulation. The satellite imagery provides an observation of the hail swath, or where the more significant accumulating hail occurred. In this case, the swath diagnosed in GOES imagery matched up well with the MRMS MESH track, but the actual length of the accumulation of hail did not extend as far south into Kiowa County as what may have been suggested by MRMS MESH.

Mike Umscheid (NWS Dodge City, KS) and Bill Line (NESDIS and CIRA)

Flooding within the Red River of the North basin is practically a yearly rite of passage for those living there signaling the exit of winter and coming of summer. This area straddling the North Dakota and Minnesota border is well prepared for river and overland flooding because of its frequency. Spring of 2020 is proving to be no different with major flooding occurring over much of the Red River and its tributaries due to seasonal snow melt.

It can be difficult to keep a pulse on how impactful flooding really is with a lack of comprehensive reports in an ever-evolving and fluid situation. Plus with extensive flood mitigation systems in place, the majority of floods that occur in this area are nothing more than just an inconvenience for most people. Still for the minority that have property impacted by flooding, it can be quite notable and our services can be tailored to them, or at least towards the emergency services aiding them. Additionally, a threat to life can come to fruition if one finds themselves in very cold floodwaters (an example could be a car sliding off the road into floodwaters). This is ultimately our mission as National Weather Service meteorologists: to protect life and property.

This post will explore the satellite imagery that aided NWS Grand Forks in flood operations in mid-April 2020. In this case, flooding was due to springtime snow melt, but the following procedures and workflows may be applicable to warm season convection as well.

On April 10, 2020, moderate to major flooding was occurring along the Red River and its tributaries within the central and northern basin. Wondering if there were any areas experiencing impactful flooding outside of current flooding warnings, forecasters initially turned to GOES-R ABI River Flood Products for help in highlighting areas of observed floodwater coverage. Overlaying flood warning polygons, forecasters then looked for areas highlighted by the ABI River Flood Extent product not encompassed by polygons. This was the case in western Polk and Marshall counties, Minnesota, as noted in Figure 1. Values higher than 60% (orange and red coloring) were of particular interest as lower values into the 30-50% range were believed to be that of non-impactful standing meltwater in agricultural fields. While the ABI River Flood Products are updated every hour, the ABI’s spatial resolution of 1 km can smooth out the spatial extent of potentially impactful flood waters. VIIRS offers this same imagery at a finer resolution of 375 m, but at the expense of one or two images per day which require a daytime, cloud-free sky to provide useful information.

Luckily this area of interest was mostly cloud-free during one of the VIIRS passes. It confirmed higher percentage values in the same areas of interest, particularly in northwest Polk County, Minnesota (Fig 2).

There is additional satellite imagery available to further provide details on floodwaters and its potential impacts. Higher resolution satellite imagery down to 10 m from Sentinel-2 and Landsat 8 has recently become available on the web and already processed for quick viewing at sites like Sentinel-Hub and Remote Pixel. A timely, cloud-free pass from the Sentinel-2 satellite over the area of interest was available to forecasters for interrogation (Fig 3). It revealed extensive break out water from the Red River north of Grand Forks, North Dakota, and surrounding Oslo, Minnesota, although these areas were well within the flood warning polygons. What about the other areas of expansive meltwater in agricultural plots between Alvarado, East Grand Forks, and Tabor, Minnesota? Sentinel-2 imagery hinted that some of these floodwaters might be over roads and surrounded farmsteads. These areas of adjacent flooded plots of land correlated nicely with higher percentages within the ABI and to an extent VIIRS River Flood Extent products, thus confirming impactful flooding would possible here.

Forecasters took this approach of using satellite imagery to hone in on targeted areas for intel gathering of flood impacts. Looking for road closures on state Department of Transportation and county websites, data mining on social media, and calling emergency managers confirmed impactful flooding in these areas. Thus, these areas could warrant a flood headline. Ultimately the decision was made to not issue an Aerial Flood Warning as the majority of these areas fell just within current flood warning polygons.

So does the application of this imagery stop here? Not quite. ABI and VIIRS River Flood Extent products highlight nicely the extent of observed floodwater. In this case it was used as a source for the graphic in Figure 4. The imagery answers the “where” and “when” of flooding within the graphic while the photo depicts the impact, capped off with safety messaging. This imagery also yielded high confidence in overland flooding impacts which was messaged via the Hydro section within the Area Forecast Discussion from NWS Grand Forks. Additional imagery analysis was conveyed to the North-Central River Forecast Center which was useful in assessing the current state of snowpack, river and ditch ice, and floodwater expanse.

In summation, satellite imagery from ABI and VIIRS River Flood Products as well as from Sentinel-2 provided excellent details in gauging flooding impacts from river and overland flooding. Starting with the most coarse spatial resolution, yet highest temporal resolution imagery like ABI was a good starting point in searching for floodwaters over a broad area. Then, incrementally honing in on highest flood extent signals at higher spatial resolution imagery proved to be a good workflow in pinpointing areas of interest to target intel gathering of current impacts from flooding. Furthermore, this imagery was useful in messaging through graphics, discussions, and collaboration.

Honorable mentions:

Did you know Nighttime Microphysics RGB can by used to diagnose floodwaters (Fig 5)? The highest contribution of sensed floodwater comes from the Split Window Difference product. In this case, there was high contrast between lower values of liquid bodies of water and higher values of land. However, due to dependence on sensed infrared energy, seasonal and air mass differences can change the appearance of floodwaters within the RGB. You can adjust the RGB to help draw out this floodwater signal from the Split Window Difference as well.

Besides high resolution imagery from Sentinel-2 and Landsat 7/8, cloud penetrating Sentinel-1 offers similar resolution imagery while capable of detecting liquid water versus snow and bare ground (Fig 6). Although, it does take a more careful eye in interpretation of the imagery, especially when looking at “waterlogged” snowpack which can give a false signal for liquid water. This type of imagery can be extremely useful when pesky clouds prevent imaging radiometers from sensing the ground.

Resources:
NOAA Global Flood Product Quick Guide
VIIRS Flood Areal Extent Quick Guide
VIIRS Flood Detection Map Quick Guide
AWIPS Instructions Document

Carl Jones
Meteorologist
NWS Grand Forks

Bill Line, NESDIS and CIRA

GOES-East upper level (6.2 um) water vapor imagery with GLM and RAP analysis overlay depicted the Friday night – Sunday morning evolution of a storm system that brought severe thunderstorms to the southern US (Figure 1). A closed upper low initially centered over southern California on Friday accelerated east across northern Mexico Saturday as it evolved into an open wave, and eventually progressed ENE into the southern plains and southeast Sunday into Monday morning. Water vapor imagery shows the drying/warming descending air (warm colors) wrapping around the southern portion of the strengthening shortwave in conjunction with the intense upper level jet. Strong ascent is apparent east/northeast of the upper energy below the exit region of the upper jet represented as regions of cooling (cool colors and white) and developing thunderstorms. The RAP overlays help one to conceptualize what is being observed in the more detailed (temporally and spatially) water vapor imagery.

Additionally in Figure 1, a shortwave trough is diagnosed digging southeast across the northwest US Saturday and then east across Colorado into the central high plains on Sunday as it swings around the base of a broad upper low slowly sinking south into the far north-central US. This system brought a swath of snowfall to the Rockies, central high plains, and into the Midwest, which is apparent in the GOES-East Day Cloud Phase Distnction RGB as green (Fig 2).

Visible/GLM FED Sandwich combo imagery with NWS warning polygons during the daytime shows the development and evolution of thunderstorms throughout the day, and the relationship between lightning activity and strong (warned) storms (Fig 3). GLM is effective in highlighting the location of updraft cores and updraft trends within a messy cloud field and long flashes extending outward from the main updrafts and into the anvils. The image combination includes quantitative information from GLM without sacrificing the vital texture information from the VIS.

Bill Line, NESDIS and CIRA

A significant winter storm moved through the Northern Plains and Upper Midwest April 1-3, 2020, bringing over a foot of heavy snow, more than a quarter inch of icing, thunder–sleet and -snow, gusty winds, and moderate rainfall over an area already experiencing seasonal snowmelt flooding. The combination of ice, snow, and flooding made for particularly hazardous travel conditions as well.

It was known ahead of the event that mixed precipitation of sleet and freezing rain would cause ice accumulation on the “warm” side of a slow moving front and eventual surface low. Regional NWS offices messaged this threat ahead of time, although there remained some uncertainty of how much and exactly where ice accretion would take place. The FRAM (Freezing Rain Accumulation Model) from SPC’s HREF as well as NBM’s ice accretion percentiles offered useful guidance to forecasters, although painted a very broad threat area including the entire state of Minnesota.

So how did it pan out?

Well, we can turn to the ABI on board GOES-East to help fulfill this answer, specifically the 1.61 um channel known as the Snow/Ice Band. At this wavelength, solar radiation energy is strongly absorbed by snow and ice with little reflected energy travelling back towards the sensor. This is why snow and ice show up relatively dark in the 1.61 um channel compared to snow-free ground and liquid phased clouds. While both are efficient at absorbing in this wavelength, ice still more strongly absorbs radiation than snow, allowing ice to appear even darker than snow. Additionally, wide areas of liquid water are even more strongly absorbed in the 1.61 um. This makes flood waters including major flooding along the Red River of the North and other ice-free lakes very dark. It is possible that darker swaths in southern Minnesota into Iowa may be enhanced from higher soil moisture from rain prior to a wintry mix producing ice.

With a mostly clear sky in place on April 4, we can use these properties to get an idea of where ice accretion occurred. While we are at it, let’s go down the multispectral imagery path and look at the Day Snow-Fog RGB which includes the 1.61 um channel.

Notice a dark red swath extending down the spine of Minnesota, into eastern South Dakota and into Iowa. There is also another area in southeastern Minnesota, again into Iowa, and western Wisconsin. These are areas where ice from freezing rain and sleet accrued. The streak-like nature of this signature within Iowa and southern Minnesota points to convective elements and showery activity leading to widely varied accretions and likely associated impacts telling us this was a very difficult forecast to pinpoint. Overall, guidance from HREF and NBM did well highlighting the general area, although they likely smoothed out these high spatially varied accretions within their ensemble systems.

The Day Snow-Fog RGB utilizes the 1.61 um channel as it’s green component. Less reflectance of snow and ice in this channel leads to lesser green values added to the overall combination. Within the RGB’s red component, the visible-like 0.87 um channel, snow is much more reflective with little or no reflectance from ice accrued areas. These differences make for easily noticeable contrasts between snow and ice, making it easier for forecasters to diagnose areas that experienced overall more ice than snow.

While the darker signature of icing helped forecasters see where icing may have been more prevalent than snowfall, it does not mean this was the only area of icing. Just to the west of the dark red strip in western Minnesota significant icing still occurred as depicted in this USGS photo of ice accrual on a river gage near Fargo disrupting data transmission. However, a transition from wintry mix later to accumulating snowfall lead to accumulated snow hiding the icing signature. The same could be said for patch around southeastern Minnesota.

As the power of an April sun warmed ground temperatures in the Upper Midwest, ice and thinner snowpack quickly disappears on the Day Snow/Fog RGB and CIRA’s Snow/Cloud Layers RGB.

So how is this information useful after the storm? Not only does it increase a forecaster’s situational awareness of potentially highest impacted areas, it can be used as an Impact Decision Support Service tool for illustrating to partners where exactly these conditions occurred. Forecasters at the National Weather Service in Grand Forks, North Dakota, and hydrologists at the North Central River Forecast Center used this imagery to gauge important spatiotemporal characteristics of the associated liquid water equivalent leading to conclusions of which locations would first see this water move into area rivers already undergoing flooding from winter snowpack melt. Additionally, satellite imagery including the Day Snow Fog RGB image above was used in a hydrologic briefing to core partners within the Red River of the North basin, giving them an idea of these important characteristics while using imagery to justify some aspect of updated river forecasts.

Carl Jones
Meteorologist
NWS Grand Forks