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On April 27, 2011, a severe weather outbreak occurred across the southeastern United States, resulting in 199 tornadoes across the region and over 300 fatalities (NWS 2011 Service Assessment).  Alabama was among the states hardest hit, with 68 tornadoes surveyed by the National Weather Service (NWS) Weather Forecast Offices (WFOs) in Huntsville, Birmingham, and Mobile, Alabama, and over 250 reported fatalities in the state. Huntsville, home to NASA’s Marshall Space Flight Center and the Short-term Prediction Research and Transition (SPoRT) Center, lost power along with most of Madison County after tornadoes severed major utility lines.  The power outage lasted well over a week in some areas. Once power was restored, SPoRT team members were able to provide satellite imagery to our partners in the National Weather Service to help clarify some of the high-intensity tornado damage tracks that occurred throughout the state. SPoRT provided pre- and post-event difference imagery at 250 m spatial resolution from the Moderate Resolution Imaging Spectroradiometer (MODIS) and 15 m false color composites from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). These surveys helped our NWS partners confirm their ground surveys, but also helped to correct the characteristics of several tracks (Molthan et al. 2011). Many of these products remain available through the SPoRT web page (link) and also through the USGS Earth Explorer portal (link).

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The MODIS Band 1 difference image above shows some of the scars left behind by the April 27, 2011 tornado outbreak. Radar snapshots were taken from various times to identify the supercell thunderstorms associated with each track.  Reproduced from Molthan et al. 2011.

Follow-on studies examined the capability of various NASA sensors for detecting and measuring the length and width of scars visible when using the Normalized Difference Vegetation Index, or NDVI, a measurement of vegetation greenness and health commonly derived from multiple satellite imaging platforms.  SPoRT examined NDVI products from MODIS (250 m), Landsat-7 Enhanced Thematic Mapper Plus (ETM+, 30m) and ASTER (15 m) collected in May and June 2011. Possible tornado tracks were identified, mapped, and were then measured to compare against the official NWS damage surveys.  In general, many of the major tornadoes (defined here with maximum intensity EF-3 and greater) were at least partially visible at resolutions of 15-250 m, though weaker tornadoes or those that occurred in complex terrain were more difficult to detect using NDVI and a single snapshot in time. As tornadoes initiated and increased in intensity, or dissipated and decreased in intensity, some of their characteristics became more difficult to detect.  However, some weaker tornadoes were also apparent in Landsat-7 imagery (30 m) in well-vegetated areas.  A summary of the study is available as a publication in the National Weather Association’s Journal of Operational Meteorology. In 2013, SPoRT received support from NASA’s Applied Sciences: Disasters program to partner with the NWS and facilitate the delivery of satellite imagery to their Damage Assessment Toolkit (DAT).  The DAT is used by the NWS to obtain storm survey information while in the field. Satellite imagery from NASA, NOAA, and commercial sensors (acquired in collaboration with USGS and the Hazards Data Distribution System) helps to supplement the survey process by providing an additional perspective of suspected damage areas.

Many of the damage scars apparent from the April 27, 2011 outbreak exhibited signs of recovery and change in the years following the outbreak.  Other tornado events also brought additional vegetation damage and scarring to the region. With five years passing since the 27 April 2011 tornado outbreak, annual views of cloud-free imagery have been obtained from the Landsat missions, operated and managed as a collaboration between the USGS and NASA.  In the viewer linked below, SPoRT has collaborated with the USGS Earth Resources Observation Systems (EROS) Data Center to acquire 30 m true color and vegetation index information from Landsat 5, Landsat 7, and Landsat 8 during the late spring and summer months when local vegetation is at its greenest, allowing the greatest contrast between damaged and undamaged areas. Users can take a look at these images in a web viewer that allows toggling between different products and years, view some of the tornado tracks surveyed by the NWS following the April 27, 2011 event, and zoom into areas of interest to examine how some of the affected areas have evolved over time:

Tuscaloosa, AL

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The above animation shows the year before and years after the EF-4 tornado impacted the Tuscaloosa area. The tornado track has seen a significant recovery, but a scar still remains in 2015. In addition to seeing how the landscape as recovered from tornado, development in and around Tuscaloosa is also apparent.  Missing pixels in 2012 are due to an issue with the Landsat-7 imager.

Hackleburg-Phil Campbell

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Similar to the Tuscaloosa animation, this animation shows the recovery of the EF-5 tornado that moved through Hackleburg and Phil Campbell, before tracking northeast across the Tennessee River.  Missing pixels in 2012 are due to an issue with the Landsat-7 imager.

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On April 16th a fire was reported in the Shenandoah National Park in eastern Rockingham County, Virginia, situated roughly between the cities of Harrisonburg and Charlottesville. Estimated at about 500 acres (per latest news reports), the fire (named the Rocky Mountain Fire) is large enough and producing a sufficient amount of smoke to be seen in Geostationary satellite data from GOES-13 this afternoon (Image 1).

GOES_AfternoonLoop_18Apr2016

Image 1. GOES visible loop, 1646-1845 UTC, 18 April 2016.  A plume of smoke can be seen extending SSE of the fire in the central portion of the image.  The Charlottesville, VA observation site (in the path of the smoke) contains a report of smoke in the last couple of frames of the loop.

However, the fire can also be seen in Day-Night Band Imagery, produced by the VIIRS instrument aboard the Suomi-NPP satellite.  The first image below (image 2) shows no visible fire early on the morning of the 16th and the growth of the fire over the next couple of mornings in the next two images (images 3, 4).

DNBRadiance_0729Z16Apr2016_blog

Image 2.  VIIRS Day-Night Band Radiance RGB, 0729 UTC 16 April 2016. The circle shows the eventual location of the fire (although not evident yet in this image from the morning of April 16th).

 

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Image 3. VIIRS Day-Night Band Radiance RGB, 0710 UTC 17 April 2016. The small white dot in the center of the circle likely represents the fire early on the morning of the 17th.

 

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Image 4. VIIRS Day-Night Band Radiance RGB image, 0615 UTC 18 April 2016, showing the much larger “Rocky Mountain Fire” in portions of the Shenandoah Nat’l Park in eastern Rockingham County, VA.

 

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On December 23, 2015, an unusual early winter season tornado outbreak struck much of the Tennessee Valley. Several tornadic supercell thunderstorms developed across northern Mississippi and western Tennessee in the afternoon hours, producing several large long-track tornadoes that unfortunately resulted in numerous fatalities and injuries. These same storms then moved rapidly east-northeastward at up to 70 mph across Middle Tennessee during the evening, spawning 4 tornadoes and causing 2 deaths and 7 injuries. Prior to this tornado outbreak, only 7 tornadoes had ever been recorded across Middle Tennessee since the 1800s, easily making this the largest and worst December tornado outbreak in Middle Tennessee history.

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OHX radar base reflectivity (left) & storm-relative velocity (right) at 623 pm CST on December 23, 2015 showing a supercell thunderstorm with an EF2 tornado in progress southeast of Linden, TN

NWS Nashville sent out three storm survey teams to evaluate all of the damage from these tornadoes on Christmas Eve and again on Christmas Day. Unfortunately, the affected areas were very rural and mostly inaccessible to the storm survey teams, with few roads available to evaluate damage indicators or determine beginning and end points. Thankfully, Landsat 8 imagery was available in the online Damage Survey Interface (DAT beta version) that depicted the swaths of blown down forests along the tornado paths that tracked through areas where the storm survey teams could not access. Landsat imagery allowed NWS Nashville personnel to extend two of the tornado paths by several more miles than originally estimated.

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Landsat 8 panchromatic imagery (contrast enhanced) from March 22, 2016 showing the damage swath from an EF2 tornado that killed 2 people southeast of Linden, TN. The beginning point of this tornado was adjusted ~2 miles further southwest than originally estimated based on the satellite imagery.

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Conditions have been very warm and dry lately in parts of the Southern Plains and the Southwest.  This has resulted in a few blowing dust events and over the last 24 hours or so, and some very large grass fires in the open prairie.  Take a look at this loop of GOES 3.9 um imagery from 1655 UTC to 2115 UTC today, to see this rapid expansion of a very large fire ongoing on the Oklahoma/Kansas border, encompassing Comanche, Barber and Woods Counties.  The black colors represent the fire hot spots developing and expanding in the very dry and windy conditions.  In fact, widespread wind gusts around 40 to 50 mph were common in the region today.

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Image 1. GOES 3.9 um loop from 1655 to 2115 UTC 23rd March 2016.

 

This fire even showed quite up well last night in the Suomi NPP VIIRS Day-Night Band imagery.

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Image 2. Suomi VIIRS Day-Night Band Radiance RGB, 0818 UTC 23rd March 2016. The white circle indicates the location of the large grass fire in Woods and Comanche Counties.

Interestingly, the smoke from these grass fires is apparently not sufficiently dense or reflective to show up very well in the nighttime visible imagery.  Only a faint wisp of smoke can be seen extending to the NE of the fire in the prevailing direction of the surface wind last night.

Meanwhile, the Dust RGB showed significant dust plumes in and around the region…

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Image 3. Suomi NPP VIIRS Dust RGB, 1946 UTC 23rd March 2016. Circles indicate areas of blowing dust evident in the Dust RGB. At this time, blowing dust was reported in Lubbock, TX and Hobbs, NM (not shown).

 

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SFR_0220UTC_02162016

During the afternoon and early evening hours on 2/15/2016, a large area of rain covered much of northeast Kentucky and southeast Ohio as well as the western half of West Virginia.

An upper level disturbance then moved across the area during the evening and overnight hours with the rainfall mixing with and then transitioning to all snow.

I wanted to show how the SFR image performed during this transition.  The image above is from 0220 UTC on 2/16/2016.  At that time, much of the precipitation across West Virginia was still in the form of rain…with an area of snow extending from northwest Pennsylvania across central Ohio into southwest portions of that state.

There appears to be several observations of rain across Ohio with surface temperatures  of 32 to 35 DegF  where the SFR product indicated snow in the clouds.  It does appear that where surface temperatures were warmer than 35 DegF, the SFR product did not indicate any snow in the clouds.

From an earlier post, I believe the SFR throws out snow when the model-based 10-m temperatures exceeded 33 DegF.  Is this filter working in this situation?

 

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I’ve had some opportunity to view the NESDIS Snowfall Rate (SFR) Products today, in particular, to see how it performs during the central Plains/Midwest snowstorm.  These products are being delivered by SPoRT to several collaborative offices in the CONUS and Alaska for evaluation during the current winter.

Background info:  the Merged SFR product contains NSSL Multi-Radar Multi-Sensor (MRMS) precipitation data with insertions of polar-orbiter derived precipitation rate data when those are available.  The precipitation rate data from the polar-orbiters is available in AWIPS in individual swaths or contained within this merged product (in the merged product, the MRMS data replace the polar-orbiter data).  The data are available in AWIPS as liquid equivalent values or a snowfall rate with three distinct snowfall-to-liquid ratios: 10:1, 18:1, 35:1.  To learn more about this product, you may click here to see training material provided by researchers at NESDIS and SPoRT.

So, let’s take a quick look at some of the data today and I’ll share a few comments and thoughts.  This first image is the Merged SFR product valid at 1130 UTC with METAR plots (yellow) at 12 UTC.

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Image 1.  NESDIS POES Merged Snowfall Rate (10:1) valid 1130 UTC 2 Feb 2016, METAR plot valid 12 UTC 2 Feb 2016.

 

Without any polar orbiting data available at this time, this image contains only the MRMS precipitation data.  In the image (Image 1), notice the band of heavier precipitation stretching roughly west-east across southern Nebraska and Iowa, and the relatively tight precipitation gradient in southern Iowa.  At the time of this image, notice no snowfall was occurring at the Des Moines location, per the SFR product or the 12 UTC METAR.  Pay particular attention to the discrepancy in times between the METARs and the SFR product at this point…there is a 30-minute offset.  Now, let’s look shortly later as a swath of polar orbiter data became available.

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Image 2. NESDIS SFR Merged product valid 1140 UTC, NESDIS SFR swath data valid 1145 UTC, and METAR plots valid at 12 UTC 2 Feb 2016.

I have layered the imagery so that the polar imagery swath data are laid atop the Merged SFR product.  Notice that the polar orbiter derived data indicate a band of relatively heavier precipitation spreading northward into Nebraska and Iowa.  This is important because the polar orbiters observe precipitation within the clouds on average ~30 minutes before it manifests at the surface.  In this image (Image 2), notice that this band of heavier precipitation has now spread northward to include Des Moines and points to the west of there, where little to no precipitation was occurring earlier.  So, the NESDIS polar data suggested significant snowfall production was translating northward within the mid/upper cloud layer.  Knowing the data typically offer about a 30 minute lead time for observations at the surface, a forecaster could have surmised something about precipitation production aloft, intensity and overall storm evolution while obtaining more data about timing to impacts at a metro area.

The next image shows the timing of the arrival of the precipitation at Des Moines  per the merged SFR product and the Des Moines surface observation (Image 3).

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Image 3.  NESDIS Merged SFR product valid 1230 UTC, METAR plots valid 1300 UTC 2 Feb 2016.

In image 2, remember that the SFR swath data indicated high snowfall rates, >1 inch/hr (per the 10:1 ratio…which may be understimated) directly over Des Moines and surrounding areas at 1145 UTC, while the Merged SFR above (Image 3) shows precipitation finally entering the city and the observation site at ~1230 UTC.  Notice that the Des Moines METAR showed light snow during the 1300 UTC observation (Image 3).

Let me point out something important here.  In the Merged SFR product, the satellite derived data are purposely delayed 30 minutes for insertion into the official delivered product.  This was decided as the configuration of the official product since precipitation in the satellite derived data typically precede the arrival of precipitation at the surface by about 30 minutes.  The thinking being that this apparent discrepancy would be observed between the MRMS data and the satellite derived data, and would lead to forecaster confusion.  That is understandable, especially for this latest experimental iteration of the SFR product.  However, after viewing these data in a few cases, I think it is advantageous that the satellite derived data contain important information about the evolution of snowfall and precipitation production aloft, well before it manifests at the surface.  The fact that satellite derived observations of precipitation rates precede the occurrence of snowfall at the surface by about 30 minutes, and if you noticed, by about one hour in this case, makes these satellite derived swath data operationally relevant and important.

 

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This past weekend’s storm which brought record-breaking snow to the Mid-Atlantic and Northeast Corridor also brought something that gets the Earth Science Office at Marshall Space Flight Center (MSFC) excited…lightning from the view point of a camera lens aboard the International Space Station (ISS).

NASA Commander Scott Kelly (@CDRScottKelly) tweeted out this photo early Saturday morning from an overflight down the East Coast just before sunrise.

https://twitter.com/stationcdrkelly/status/690905921980080130

The corresponding satellite and lightning data show that the ISS camera captured a 4 stroke incloud lightning flash within the storm as the system pushed its way out to sea in the North Atlantic.

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GOES East IR imagery from 0945 UTC on 23 January 2016. Red plus signs indicate the location of 4 incloud strokes as observed by the Earth Networks Total Lightning Network that represent the location of the flash in the ISS photo from Saturday.

Over the next year the weather enterprise will expand its capability to monitor lightning flashes from space in a similar manner to how the ISS captured this lightning flash. In the next year, two spaceborne lightning measurement instruments which NASA MSFC has played a major role in developing during many decades of hard work will be launched into space: the International Space Station Lightning Imaging Sensor (ISS-LIS) and the GOES-R Geostationary Lightning Mapper (GLM). These instruments will monitor energy from lightning flashes escaping the top of the cloud when a lightning flash occurs, utilizing a narrow oxygen emission line at 777.4 nanometers.

What does this mean for the public? Increased public safety and confidence in decisions which are affected by hazardous weather. Data from the ISS-LIS and GLM instruments will help scientists better understand the internal structure of all types of storms, helping develop better models for how storms grow, intensify and decay. Forecasters will be able to utilize flash rate information on storms acquired from these instruments to enhance severe weather prediction, determine where the heaviest snowfall rates are occurring in winter systems, or help reroute air traffic away from dangerous storms over the ocean. Most importantly, the ability to monitor the area of individual flashes will lead to better decisions on how to take shelter in an appropriate amount of time before the first lightning strike occurs in their area.

A special thank you to Mike Trenchard, Will Stefanov of Johnson Space Center for helping us acquire the ISS telemetry and camera information used to sync the meteorological observations with the lightning photo from Commander Kelly.

(Posted on behalf of the Earth Science Office)

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