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.
Figure 1: 22 April 2020 GOES-East 6.2 um water vapor imagery, GLM FED, and RAP 500 mb height and wind, MSLP, sfc wind. Higher res
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).
Figure 2: 22 April 2020 GOES-East 1-min VIS, NWS severe thunderstorm warning polygons. Higher res
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.
Figure 3: 22 April 2020 GOES-East 1-min VIS-IR sandwich combo, NWS severe thunderstorm (yellow) and tornado (red) warning polygons. Higher res
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.
Figure 4: 22 April 2020 GOES-East 1-min VIS-IR sandwich combo, transitioning to IR, NWS severe thunderstorm (yellow) and tornado (red) warning polygons. Higher res
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.
Figure 5: 22 April 2020 GOES-East 5-min VIS-IR sandwich combo, transitioning to IR, NWS severe thunderstorm (yellow) and tornado (red) warning polygons. Higher res
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.
Figure 6: 22 April 2020 GOES-East 5-min IR, GLM FED, NWS severe thunderstorm (yellow) and tornado (red) warning polygons. Higher res
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.
Figure 1: GOES-East Nighttime Microphysics RGB (12.3-10.3 um, 10.3-3.9 um, 10.3 um) + “Clean” IR (Band 13, 10.3 um) with temps warmer than -25 C transparent. Higher res.
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.
Figure 2: 4 Panel breakdown of GOES-East Nighttime Microphysics RGB (top left), Split Window Difference of 12.3-10.3 um (top right), “Fog/Low Stratus” Brightness Temperature Difference of 10.3-3.9 um (bottom left), “Clean” IR Band 13 10.3 um (bottom right). Higher res.
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).
Figure 3: Adjusted 4 Panel breakdown of GOES-East Nighttime Microphysics RGB (top left), Split Window Difference of 12.3-10.3 um (top right), “Fog/Low Stratus” Brightness Temperature Difference of 10.3-3.9 um (bottom left), “Clean” IR Band 13 10.3 um (bottom right). Higher res.Figure 4: A comparison between Figure 3 and 4. Higher res.
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).
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.
Figure 1: 19-20 April 2020 GOES-East 6.2 um water vapor imagery, GLM FED (yellow overlay), RAP 500 mb height (white contour), 500 mb wind (white barbs), 500 mb abs vort (blue contours). Higher res
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.
Figure 2: 0530 -0745 UTC 20 April 2020 GOES-East 1-min IRW, MRMS Composite Reflectivity, NWS Severe Thunderstorm (yellow) and Tornado (red) warning polygons. Higher res
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.
Figure 3: 0530 – 0745 UTC 20 April 2020 GOES-East 1-min IRW, NWS Severe Thunderstorm (yellow) and Tornado (red) warning polygons. Higher resFigure 4: 0530 – 0745 UTC 20 April 2020 GOES-East 1-min IRW, GLM FED, NWS Severe Thunderstorm (yellow) and Tornado (red) warning polygons. Higher res
***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.
Figure 1: 19 April 2020 GOES-East Day Cloud Phase Distinction RGB. Higher Res
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).
Figure 2: 19 April 2020 GOES-East modified Day Cloud Phase Distinction RGB imagery. Higher res
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).
Figure 3: NWS DDC Social Media post from 19 April 2020 showing the hail swath from MRMS MESH (left) and public photo (right). Higher res
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).
Figure 4: 20 April 2020 morning GOES-East Day Cloud Phase Distinction RGB imagery. Hail swath (green) is annotated. Higher resFigure 5: 1431 UTC 20 April 2020 GOES-East single/multi channel imagery over central Kansas hail swath. Higher res
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.
Figure 1: 10 April 2020 GOES-East ABI River Flood Areal Extent Product, NWS River Flood Warnings. Higher res.
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).
Figure 2: 10 April 2020 VIIRS River Flood Areal Extent product. Higher Res.
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.
Figure 5: Clockwise starting top left: 13 April 2020 GOES-East Nighttime Microphysics RGB, Split Window Difference, 10.35 um IR, Night Fog Difference. Higher Res.
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.
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).
Figure 2: 1646 UTC 13 April 2020 GOES-East Day Cloud Phase Distinction RGB. Higher Res.
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.
Figure 3: 12 April 2020 GOES-East VIS, GLM FED, NWS Warning Polygons. Higher res. With Controls
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?
GOES-East Snow/Ice Band (1.61 um). April 4 2020 13:00 – 16:00 UTC. Larger loop.
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.
GOES-East Day Snow-Fog RGB (0.87, 1.61, 3.9-10.3). April 4 2020 13:00 – 16:00 UTC. Larger loop.
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.
GOES-East Day Snow-Fog RGB, Veggie Band (0.87 um), Snow/Ice Band (1.61 um). April 4 2020 13:00 – 16:00 UTC Larger loop.
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.
GOES-East Day Snow-Fog RGB (0.87, 1.61, 3.9-10.3). April 4 2020 16:00 – 20:00 UTC. Shows rapidly melting snow and ice Larger loop.CIRA’s Snow/Cloud Layers RGB. White denotes snow cover. Larger loop.
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.
Day Snow-Fog RGB over Grand Forks CWA used in hydrologic briefing to core partners. Larger image.
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.
A low pressure system deepened rapidly over the Atlantic just off the Carolina coast during the day on 01 April 2020. GOES-East water vapor imagery and RAP surface analysis provide a great visualization of the strengthening low as it progressed east away from the coast (Fig 1). Dry/warming descending air (warm colors) is evident wrapping around the low from the south, while ascending/cooling air (including deep moist convection) is obvious further east, north, and west of the low.
Figure 1: 01 April 2020 GOES-East 6.2 um Water Vapor Imagery and RAP MSLP analysis. Higher res
As the low strengthened, very gusty winds developed at the surface, prompting the issuance of a Hurricane Force Wind Warning by the NWS. HRRR model analyses indicate widespread wind gusts in excess of 50 knots wrapping around the southern and eastern portion of the low (Fig 2).
Figure 2: 01 April 2020 HRRR surface wind gust analysis. Higher res
GOES-East low-level DMWs, while not abundant nearest the center of circulation where cloud streets developed and winds were likely strongest, did produce several wind vectors over 50 knots near the low center, indicating strong flow just above the surface.
Figure 3: 01 April 2020 GOES-East 0.64 um VIS, 600 mb – SFC DMWs. Higher res
METOP-B ASCAT observed surface winds in excess of 50 knots wrapping around the western portion of the low between 1500 and 1600 UTC (Fig 4a). Later between 1800 and 1900 UTC, AMSR2 measured surface wind speeds between 50-60 knots on the western portion of the low, and 40-50 knots wrapping around the southern quadrant, between 18-19 UTC (Fig 4b).
Figure 4a: 01 April 2020 METOP-B ASCAT surface wind speed. Higher resFigure 4b: 01 April 2020 AMSR2 surface wind speed (knots). Higher res
An area of clearing was present adjacent to deep moist convection near the low center during the morning hours after sunrise. GOES-East visible (0.64 um) imagery captured rough seas (white caps) and associated/implied sea spray under the clear skies, confirming gusty winds reaching the surface during that period (Fig 5). The white caps/sea spray is diagnosed by regions of higher reflectance compared to nearby calmer seas. A modified gray-scale colortable is utilized in order to best highlight the white cap/lofted sea spray signature.
Figure 5: 01 April 2020 GOES-East 0.64 um VIS. Higher res
A zoomed in feature following animation provides an alternative means for viewing the evolution of the white caps through the morning (Fig 6). The phenomenon is most prolific extending south and east from the region of thunderstorms in the center of the scene.
The longer wavelength 0.865 um imagery provides better contrast for detecting the white caps (compared to clear sky calmer seas) given less influence of atmospheric aerosols compared to at the shorter wavelengths (Fig 7). However, spatial resolution is degraded by 4x compared to the 0.64 um channel with ABI, reducing clarity of the feature.
Figure 7: 01 April 2020 GOES-East 0.856 um VIS. Higher res
The white caps can be diagnosed in the snow-cloud RGB as regions of bright blue (Fig 8).
Finally, the milky appearance of the white caps was easily apparent in the Geocolor (true color) imagery (Fig 9).
Figure 9: 01 April 2020 GOES-East Geocolor imagery. Higher res
A longer feature following animation shows white caps and sea spray continued along the southern portion of the low center into the afternoon and early evening hours (Fig 10).