Normalized Burn Ratio (NBR) Imagery in AWIPS…

Landscapes that have succumbed to wildfires, or burn scars, present especially difficult hydrologic forecasting challenges for National Weather Service (NWS) Offices since they can be conducive to the development of flash flooding and debris flows.  While the relationship between burn severity and this threat is rather complicated and dependent on a number of factors, determining the severity of the burned landscape can be important.  In order to assess this threat, professionals from a range of disciplines comprising Burned Area Emergency Response (BAER) Teams conduct intensive field surveys at the burn site.  BAER Teams conduct surveys as soon as team logistics and conditions allow, including containment levels of the wildfire (50% to 80% in many cases).  However, the threat for the development of debris flows and flash flooding can occur before these assessments can be made and as the wildfire is still actively burning.  Additionally, surveys are not conducted at all burn scars, especially in non federally-owned lands.  Traditionally, satellite imagery of burn scars has been used to help remedy this gap in knowledge about burn severity at any given location.  This imagery utilizes contrasting spectral properties between burned areas and healthy vegetation from a combination of Near-IR (~0.86 µm) and Shortwave IR (~2.25 µm) bands.  Imagery from Landsat and other high-resolution instruments has commonly been sought and used in associated analyses, but passes from high-resolution imagers can be infrequent, and cloud cover cover can obscure a single pass.  Thus, waiting periods for this type of imagery can be days to weeks depending on temporal availability of satellite passes and weather conditions.  To help with this issue, NASA SPoRT has developed the generation of NBR imagery in real-time in the Automated Weather Interactive Processing System (AWIPS) using data from the GOES-16 and GOES-17 satellites (Image 1).  Additionally, imagery from the VIIRS instrument aboard S-NPP has also been developed and transferred to AWIPS on an experimental basis.

Image 1. GOES-16 NBR imagery ((0.86 µm – 2.25 µm) / (0.86 µm + 2.25 µm)) overlaid with part transparent Visible (0.64 µm) imagery, 1751 UTC 8 Nov 2019

The compromise with GOES imagery is the lack of higher-resolution and thus detail observed in other imagery, yet analysis of a few fires so far this past fire season has indicated good agreement between GOES and VIIRS imagery.  A few examples are posted below.  Based on the color scale used, healthy/undisturbed vegetation is indicated by green colors, while burned areas appear in colors ranging from brighter yellows to oranges to reds.  The difference in resolution between the 0.86 and 2.25 µm bands in GOES-17 imagery causes “false” signatures along bodies of water.

Image 2. Woodbury Fire burn scar, GOES-17 NBR 1936 UTC 1 July 2019 (left), S-NPP NBR 1936 UTC 1 July 2019 (right), along with 2019 Fire Perimeters (black outlines)

 

Image 3. Kincade Fire burn scar, GOES-17 NBR 2101 UTC 7 Nov 2019 (left), S-NPP NBR 2057 UTC 7 Nov 2019 (right), along with 2019 Fire Perimeters (black outlines)

 

Image 4.  Recent So. California fire burn scars, GOES-17 NBR 2056 UTC 7 Nov 2019 (left), S-NPP NBR 2057 UTC 7 Nov 2019 (right), along with 2019 Fire Perimeters (black outlines)

While BAER Teams and Incident Meteorologists (IMETs) have also expressed a desire to have these types of imagery outside of AWIPS, in GIS-friendly formats, the advantage of making the imagery available in AWIPS is that forecasters can overlay it with other relevant hydrologic data sets that may help forecasters to better estimate the threat for flooding and debris flows.  Another advantage of having data generated from GOES is the high temporal resolution of the data, allowing near-continuous analysis of burn scar development as the fire is ongoing (provided clear sky conditions from clouds or smoke).

Image 5. Sample loop of the Woodbury Fire in AZ, GOES-17 NBR overlaid with partial transparent visible (0.64 µm) imagery, 2101-2251 UTC 17 June 2019.  Notice the burn scar that has already developed in western parts of the burn area (orange/yellow colors), while smoke can be seen emanating from the ongoing fire in NE parts of the fire complex (red colors).

While related development work is continuing, the SPoRT team will be discussing the potential use of this imagery with collaborative NWS offices, especially in the West CONUS,  for the next wildfire season.

-Kris W.

 

 

NASA SPoRT’s SST Composite Maps Capture Upwelling in the Wakes of Hurricanes Dorian and Humberto

Written by Patrick Duran, Frank LaFontaine, and Erika Duran

Category 5 Hurricane Dorian passed over the Bahamas between September 1 and 3 2019, producing catastrophic destruction and causing at least 60 direct fatalities in the island nation. In addition to the impacts on human life, strong, slow-moving hurricanes like Dorian can leave lasting effects on the ocean over which they travel. Through a process known as upwelling, hurricanes bring colder water from below the surface up to the top layer of the ocean.  As a result, a trail of cooler sea surface temperatures (SSTs), also referred to as a “cold wake,” is often visible behind a passing storm. Meteorologists and oceanographers can monitor changes in SST and identify a cold wake following tropical cyclones using satellite data.

NASA SPoRT produces composite maps of SST twice daily using data from the VIIRS-NPP, MODIS-Aqua, and MODIS-Terra instruments, along with OSTIA-UKMO data obtained from the GHRSST archive at NASA’s Jet Propulsion Laboratory and the NESDIS GOES-POES SST product. The input data are weighted by latency and resolution to produce the composite, which is available at 2 km resolution.

Figure 1 shows a loop of the SPoRT SST composite from August 31 – September 23, 2019 over a region that includes the Bahamas and the Southeast United States. Two rounds of SST cooling are observed as Hurricanes Dorian and Humberto move through the region.

Figure 1: Animation of NASA SPoRT SST Composite Maps from August 21 through September 23, 2019. Daily images are displayed at 1800 UTC.

On August 31, very warm SSTs of around 29-30 deg Celsius (84-86 deg Fahrenheit) overspread the waters surrounding the Bahamas (Fig. 2).

Figure 2: SST Composite Map at 1800 UTC on August 31, 2019.

After Hurricane Dorian tracked through the region and made landfall in North Carolina on September 6, the waters north of the Bahamas were considerably cooler – in the 26–29 deg Celsius (79–84 deg Fahrenheit) range (Fig. 3).

Figure 3: As in Fig. 2, but for September 6, 2019.

Over the next week, the surface waters warmed a degree or two (Fig. 4), but did not fully recover to the same temperature observed on 31 August.

As in Figs. 2-3, but for September 13, 2019.

On September 13, Tropical Storm Humberto formed 210 km (130 miles) ESE of Great Abaco Island. As the storm tracked northeast past the Bahamas, it encountered the cold wake left by Hurricane Dorian the previous week. These cooler waters, combined with the influence of some dry air and vertical wind shear, inhibited the storm’s intensification as it passed by the Bahamas. On September 15, Humberto moved over the warmer waters of the Gulf Stream off the coast of North Florida (Fig. 5) intensified to hurricane strength.

Figure 5: As in Figs 2-4, but for September 15, 2019.

Humberto continued to strengthen, and attained a maximum sustained wind speed of 125 MPH as it passed by Bermuda on September 19. Its strong winds and associated waves overturned the same region of ocean that was previously affected by Hurricane Dorian, decreasing sea surface temperatures to as low as 25 deg Celsius (77 deg Fahrenheit) in some areas (Fig. 6).

Fig. 6: As in Figs. 2-5, but for September 19, 2019.

These images highlight the effect that tropical cyclones can have on SST, and how a hurricane can make it more difficult for any subsequent storms to intensify over the same region. Satellite analyses of SSTs (such as those produced by NASA SPoRT) allow forecasters to monitor SST across the globe, helping them to produce better forecasts of tropical cyclone intensity in all ocean basins.

Soil Moisture Conditions over Southeast Texas Prior to Hurricane Harvey

As much-anticipated Hurricane Harvey approaches the southern and eastern coast of Texas today, it is worth examining the pre-existing soil moisture over the region to understand the capacity of the land surface to absorb the upcoming rainfall.  Granted, the amount of rainfall simulated by numerical guidance is off-the-charts high (e.g., today’s 0600 UTC initialized NAM model [Fig. 1] shows 84-hour maximum accumulated rainfall of over 60″ between Corpus Christie and Houston!!).  Thus, extreme flooding is anticipated, regardless of the amount that can be absorbed by the soils.

Figure 1.  The NCEP/NAM model 84-hour forecast of total accumulated precipitation (inches) over Southeastern Texas, from the simulation initialized at 0600 UTC 25 August 2017 [image courtesy of College of DuPage forecast page].

SPoRT manages a real-time simulation of the NASA Land Information System (hereafter, “SPoRT-LIS“), running over the Continental U.S. at ~3-km grid resolution.  The SPoRT-LIS product is a Noah land surface model climatological and real-time simulation over 4 model soil layers (0-10, 10-40, 40-100, and 100-200 cm).  The climatological simulation spans 1981-2013 and forms the basis for daily-updated total-column soil moisture percentiles (forthcoming in Fig. 3), in order to place current soil moisture values into historical context.  For real-time output, the Noah simulation is regularly updated four times per day as an extension of the long-term climatology simulation.  It includes NOAA/NESDIS daily global VIIRS Green Vegetation Fraction data, and the real-time SPoRT-LIS component also incorporates quantitative precipitation estimates (QPE) from the Multi-Radar Multi-Sensor (MRMS) gauge-corrected radar product.  The climatological SPoRT-LIS is based exclusively on atmospheric analysis input from the NOAA/NASA North American Land Data Assimilation System – version 2.

Relative Soil Moisture output from the SPoRT-LIS over the 0-100 cm layer is shown in Fig. 2 over Southeastern Texas and Louisiana at 1200 UTC this morning.  A marked gradient between very dry soils to the west and moist soils to the east occurs in the vicinity of the greater Houston metropolitan area.  The soils in the region bounded by Corpus Christi, San Antonio, Austin, and Houston (areas forecast to have the greatest rainfall from Hurricane Harvey) are extremely dry prior to Harvey’s landfall.  This dryness will help to some extent in absorbing the initial rainfall from Hurricane Harvey.  But with such excessive rainfall being forecast over a prolonged time period (3-5+ days), it won’t be long before the upper portions of the soil column saturates and widespread areal flooding occurs.  In addition, the high forecast rainfall rates could easily result in flash flooding (despite prevailing soil dryness), especially further inland where terrain plays a more important role in runoff and flash flooding.

The total column relative soil moisture percentile from 24 August shows that historically-speaking, the soil moisture is slightly drier than normal, particularly along the coastal plain between Corpus Christi and Houston (Fig. 3).  In this corridor, the soil moisture is generally between the 10th and 30th percentile compared to the 1981-2013 climatological distribution for 24 August.

Figure 2.  SPoRT-LIS relative soil moisture (RSM) distribution in the 0-1 meter layer across Southeastern Texas and Louisiana, valid 1200 UTC 25 August 2017.  RSM values of 0% represent wilting (vegetation cannot extract moisture from soil) and 100% represents saturation (subsequent rainfall becomes runoff).

Figure 3.  Total column (0-2 m) relative soil moisture percentile valid 24 Aug 2017, as compared to all 24 August soil moisture values from a 33-year climatological simulation of the SPoRT-LIS.

Finally, an hourly animation of the 1-day changes in 0-10 cm (top model layer) relative soil moisture show that the near-surface soils are quickly moistening between Corpus Christi and Houston, as the initial rainbands of Hurricane Harvey began impacting the coastal plain this morning.  As the soils continue to moisten rapidly from the top-down, subsequent rainfall will quickly lead to runoff and flooding.

Figure 4.  Hourly animation of 1-day change in top-layer (0-10 cm) relative soil moisture, for the time period spanning 0000-1400 UTC 25 August 2017.  Each hourly image is a simple difference in 0-10 cm relative soil moisture between the current and previous day at the same valid hour.  Line contours depict one-hour QPE from the MRMS product, as input to the real-time SPoRT-LIS.

Nighttime Microphysics for GOES-16

The Nighttime Microphysics RGB Imagery, provided by S-NPP VIIRS in above image, efficiently highlights the low cloud and fog areas in aqua to dull gray, to allow forecasters to better see where hazards exist to transportation (aviation, public, or marine).  This VIIRS image also provides forecasters with a look at the new geostationary capabilities that will be available soon with GOES-16 ABI.  This Nighttime Microphysics RGB Imagery was originally created by EUMETSAT around 2006, transitioned by NASA/SPoRT to forecasters within the NOAA Satellite Proving Ground over the last 5 years, and recently adopted by GOES-16 as one of the many RGB products that will be available to better utilize the ABI three fold increase in the number of bands over the current GOES imager. Currently, the Nighttime Microphysics RGB Imagery from VIIRS as well as several AVHRR and MODIS instruments is regularly used by forecasters in operations, which has allowed them to gain experience in preparation for this new capability from GOES-16.

On February 8, 2017 Dense Fog Advisories were in place across the Gulf Coast and parts of the Southeast (see image below) and there have been many similar events in the region for this winter.

Near 1000 UTC (~4:00am CST) large areas of low ceilings and visibility were occurring in the advisory regions, as seen in the first image of the post.  In the images below, take a look at how the Nighttime Microphysics RGB Imagery (this time from NOAA-19/AVHRR) compares to using a single longwave infrared channel in the split scene of the Gulf Coast region and then compare this with the same scene where only the Nighttime Microphysics  RGB Imagery is shown.  Note that the fog and clear areas can look similar in the infrared image and that the fog itself is a bit warmer than the ground areas in Texas. For help interpreting these types of images, NASA/SPoRT has RGB Quick Guides available at  https://weather.msfc.nasa.gov/sport/training/ .

VIIRS Day-Night Band Imagery and Fog Detection

Working midnight shifts this past weekend, I had the opportunity to take a look at the VIIRS Day-Night Band Imagery for the detection and analysis of fog.  Early Monday morning, the observation at Ft. Payne was indicating fog with 1/2 statute mile visibility.  However, the presence of thin cirrus over parts of the area did not allow for the observation of ground phenomena, including fog, in the region via traditional Shortwave IR imagery (Image 1).  However, low clouds and fog were observed in the VIIRS Day-Night Band imagery since the cirrus were sufficiently translucent in the visible portion of the spectrum (Image 2).

Image 1. VIIRS 3.9 µm IR image provided by NASA SPoRT, valid 0728 UTC 22 Aug 2016. Fog cannot be observed in the 3.9 um imagery since the cirrus are sufficiently opaque at this wavelength.

Image 2. VIIRS Day-Night Band Reflectance provided by NASA SPoRT, valid 0728 UTC 22 August 2016. Fog can be seen in the narrow Paint Rock Valley of western Jackson County (in northeastern Alabama). Despite the observation of fog at Ft. Payne (DeKalb County AL, –located to the SE of Jackson County), fog cannot be readily observed in the imagery, suggesting that the fog was very localized and perhaps shallow.

I could show the standard fog product imagery (11-3.9 µm), but the story is essentially the same as that of the 3.9 µm imagery of course.  The ability to see through thin cirrus is one of the primary advantages offered by the VIIRS Day-Night Band imagery and thus is among its most useful applications, operationally speaking.  These imagery are a part of the JPSS Proving Ground and have been available in AWIPS here at the HUN office for several years now, including other SPoRT collaborative partners.

In this particular case, it was operationally advantageous to see that the extent of the fog was not widespread and was just confined to some of the more fog-prone valley locations, especially the Paint Rock Valley, and may have only been highly localized to Ft. Payne, or even just the Ft Payne airport observation location.  Had the fog been observed through a larger area in Jackson and especially in DeKalb Counties, then a dense fog advisory might have been necessary.

 

Snow Cover Blankets Northeastern New Mexico

A potent winter storm system impacted portions of New Mexico on March 26, 2016, ending an extended stretch of very dry weather. Snowfall amounts of 3 to 9 inches were reported from the Sangre de Cristo Mountains eastward across the northeast plains. The MODIS and VIIRS satellite products proved useful for illustrating the extent of snow cover in both the daytime and nighttime scenes. The images below are graphical briefings posted to the NWS Albuquerque web page and shared via Twitter after this much needed snowfall event.

Graphical briefing (part one) showing the extent of snow cover during the nighttime and daytime periods on March 27, 2016.

Graphical briefing (part two) showing the extent of snow cover through RGBs on March 27, 2016.

LEO Perspective of River-Effect Snow in North Alabama

The cold air outbreak over the eastern United States had impacts far and wide, including the development of snow showers all the way into northern Alabama.  However, between unseasonably low 850 mb temperatures and northwesterly flow, the outbreak also caused a semi-persistent band of snow to develop along the Tennessee River (downwind of a reservoir known as “Lake Wheeler”).

While most of the river-effect monitoring occurred with radar, the late-morning MODIS overpass captured one of the narrow river-effect bands (and did so more effectively than the lower-resolution GOES-East Imagery).

Figure 1. MODIS visible image, valid 1644 UTC 9 February 2016.  Larger lakes are outlined in blue, and the river-effect band is circled in yellow.

Snowfall reports from underneath the band have indicated 2 to 3 inches of snow, compared to the 1-2 inches reported with heavy or persistent snow showers elsewhere.  Unfortunately, orbit timing and cloud cover have not allowed us to view the snow swath using the Snow-Cloud RGB.  However, the Snow-Cloud RGB from the edge of this morning’s MODIS pass still illustrated the river-effect band persistence.

Figure 2. MODIS Snow-Cloud RGB image, valid 1549 UTC 10 February 2016.  The Tennessee River is the dark blue feature in the center of the image; the river effect band is circled in red.