Preparing for the SWOT mission in Alaska

Preparing for the SWOT mission in Alaska

NASA SPoRT is an Early Adopter for the Surface Water Ocean Topography (SWOT) mission, which will launch in 2021 to provide the first global inventory of terrestrial surface water. SWOT features a radar interferometer that provides 120-km swath measurements of water surface elevation (WSE) for rivers wider than 50 m, reservoir height, and inundation. SPoRT is investigating potential SWOT applications for Alaska, since SWOT orbit characteristics will provide measurements with much higher spatial coverage than is currently available with in situ stream gauges (Figure 1).

Figure 1. SWOT observable rivers (legend) in southcentral Alaska, number of SWOT obs. per 21 day repeat cycle (background; grayscale colorbar), and current United States Geological Survey (USGS) stream gauge sites (green dots).

SPoRT has developed a Weather Research and Forecasting Hydrological extension package (WRF-Hydro; Gochis et al. 2018) configuration in Alaska that mimics the NOAA National Water Model (NWM) conterminous United States (CONUS) configuration. The WRF-Hydro domain contains the upper Tanana River basin (upstream of Nenana) in central Alaska, as well as the Susitna River basin in southcentral Alaska (Figure 1). Figure 2 shows WRF-Hydro streamflow output for May-June 2015 and provides insight into streamflow responses to snowmelt. The animation shows two strong signals in streamflow related to snowmelt due to the seasonal rise in temperature and stemming from diurnal heating. Rapid snowmelt regularly contributes to flooding in Alaska, and monitoring streamflow in tributaries using modeling systems such as WRF-Hydro provides essential information for improving forecasts and enhancing situational awareness.

Figure 2. May-June 2015 WRF-Hydro streamflow for the upper Tanana River basin.

Using proxy SWOT data generated from an Observing System Simulation Experiment (OSSE), virtual stream gauges are used to quantify SWOT impacts on hydrological modeling in Alaska prior to mission launch (Figure 3). SPoRT has demonstrated the utility of SWOT in improving WRF-Hydro streamflow prediction through data assimilation (Elmer et al. 2018) and in calibrating hydrological models such as WRF-Hydro in ungauged (lacking in situ stream gauges) river basins (Elmer et al. 2019). Ongoing and future work seeks to integrate these new capabilities into the future NWM Alaska domain to enable immediate use of SWOT observations within operational systems immediately after launch.

Figure 3. Proxy SWOT virtual gauge WSE along the Chena River in Alaska derived from WRF-Hydro using an OSSE.

A Decade Review of SPoRT

A Decade Review of SPoRT

Written by Emily Berndt and Jordan Bell

SPoRT was established in 2002 to transition NASA satellite data and capabilities to improve short-term weather forecasting with an emphasis on National Weather Service (NWS) end users. With the goal of maximizing the benefit of NASA research and capabilities to benefit society, SPoRT has developed innovative solutions to bring research products to operations and tailor them to meet end user needs. Over the past decade SPoRT has been at the forefront of a range of activities, making notable contributions to NASA LIS and WRF Hydro, the GOES-R/JPSS Proving Grounds, and the GPM, SMAP, and SWOT Early Adopter Programs. With an initial focus on partners in the southeastern U.S., SPoRT has expanded partnerships to include end users in all NWS Regions, National Centers, and other government agencies such as the U.S. Forest Service, U.S.D.A., and state environmental agencies. Over the decade SPoRT has consistently used a research to operations/operations to research paradigm to interact with end users, involving them in the process of product development, tailored training, and product assessment/feedback. This process has even led to algorithm improvements within GPM IMERG and the NESDIS Snowfall Rate to accelerate operational use of research products.  Interaction with end users has even led to the pursuit of research projects such as limb correction to improve RGB imagery and interpretation or developing a methodology to correct land surface model data with satellite soil moisture. In order to introduce experimental products into the fast-paced operational environment SPoRT developed applications-based training concepts such as the Quick Guide that has been shared with and adopted by others in the community. Also notable- early activities within SPoRT to leverage NASA data for disaster response, led to a bigger presence in and significant contributions to the NASA Disasters Program. Below is a review of notable publications, blog posts and tweets over the past decade:

— 2010 —

Notable Publication

Utilizing Total Lightning Information to Diagnose Convective Trends

Top Blog Post

Experimental MODIS RGB Color Composites of Hurricane Earl

— 2011 —

Notable Publication

NASA satellite data assist in tornado damage assessments

Top Blog Post

Analyzing MODIS Imagery of North Alabama Tornado Tracks

Top Tweets

— 2012 —

Notable Publications

The GOES-R Proving Ground: Accelerating User Readiness for the Next-Generation Geostationary Environmental Satellite System

Diagnosis of a dense fog event using MODIS and high resolution GOES satellite products with direct model output

Top Blog Post

Dust Storm in the Plains Captured well in MODIS Dust RGB Imagery

Top Tweets

— 2013 —

Notable Publications

Transitioning research satellite data to the operational weather community: The SPoRT Paradigm

Transitioning research to operations: Transforming the “valley of death” into a “valley of opportunity

The emergence of weather-related test beds linking research and forecasting operations

The GOES-R Geostationary Lightning Mapper (GLM) 

Application of next-generation satellite data to a high-resolution, real-time land surface model

Multispectral imagery for detecting stratospheric air intrusions associated with mid-latitude cyclones

Top Blog Post

Long flash observed by the Colorado Lightning Mapping Array

Top Tweets

— 2014 —

Notable Publications

A Real-Time MODIS Vegetation Product for Land Surface and Numerical Weather Prediction Models 

Total lightning observations and tools for the 20 May 2013 Moore, Oklahoma, tornadic supercell

Satellite-based identification of tornado damage tracks from the 27 April 2011 severe weather outbreak 

Top Blog Post

VIIRS Day Night Band (DNB) RGB Imagery Assisted by Nighttime-Microphysics RGB

Top Tweets

— 2015 —

Notable Publications

Development and Application of Atmospheric Infrared Sounder Ozone Retrieval Products for Operational Meteorology

Satellite tools to monitor and predict Hurricane Sandy (2012): Current and emerging products

Transitioning NASA and NOAA Satellite Products, Modeling & Data Assimilation Techniques, and Nowcasting Tools to Operations

Demonstration of a GOES-R Satellite Convective Toolkit to “Bridge the Gap” between Severe Weather Watches and Warnings: An Example from the 20 May 2013 Moore, Oklahoma, Tornado Outbreak

Top Blog Post

From Drought To Flooding In Less Than A Week Over The Carolinas As Depicted By SPoRT LIS

Top Tweets

— 2016 —

Notable Publications

Assimilation of SMOS Retrievals in the Land Information System

Limb correction of MODIS and VIIRS infrared channels for the improved interpretation of RGB composites

Next Generation Satellite RGB Dust Imagery Demonstration Leads to Changes in Communication and Services by NWS Albuquerque Forecast Office

From drought to flash flooding in less than a week over South Carolina

The operational use and assessment of a layered precipitable water product for weather forecasting

Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth composites

Top Blog Post

Precip Estimates offshore using NASA IMERG

Top Tweets

— 2017 —

Notable Publications

Transforming satellite data into weather forecasts

Lightning decision support using VHF total lightning mapping and NLDN cloud-to-ground data in North Alabama 

Top Blog Post

Category 5 Hurricane Irma as Observed by the GOES 16 GLM


 Top Tweets

— 2018 —

Notable Publications

A Methodology to Determine Recipe Adjustments for Multispectral Composites Derived from Next-Generation Advanced Satellite Imagers

Utility of CrIS/ATMS profiles to diagnose extratropical transition

Correction of Forcing-Related Spatial Artifacts in a Land Surface Model by Satellite Soil Moisture Data Assimilation

Evolution of 2016 drought in the southeastern United States from a land surface modeling perspective

Snowfall rates from satellite data help weather forecasters

Impact of dust aerosols on precipitation associated with atmospheric rivers using WRF-Chem simulations

Characteristics of Lightning Within Electrified Snowfall Events Using Lightning Mapping Arrays 

Top Blog Post

Plenty of fresh Powder for Paralympic Winter Games in-Pyeongchang Three Snowstorms in Eight Days

Top Tweets

— 2019 —

Notable Publications

Incorporation and Use of Earth Remote Sensing Imagery within the NOAA/NWS Damage Assessment Toolkit

Geostationary Lightning Mapper Flash Characteristics of Electrified Snowfall Events

Limb Correction of Geostationary Infrared Imagery in Clear and Cloudy Regions to Improve Interpretation of RGB Composites for Real-Time Applications

Addressing the Cold Air Aloft Aviation Challenge with Satellite Sounding Observations

Gulf of Alaska cyclone in daytime microphysics RGB imagery

Development and Evaluation of the GLM Stoplight Product for Lightning Safety

Spatial, Temporal and Electrical Characteristics of Lightning in Reported Lightning-Initiated Wildfire Events 

Top Blog Posts

GLM Sees Apparent Meteor Flash in Western Cuba

Normalized Burn Ratio (NBR) Imagery in AWIPS

Top Tweets

Into the next decade

During the past decade SPoRT has made notable contributions to bridge the valley of death to transition research to operations and maximize the benefit of NASA and NOAA remote sensing observations for the benefit of society.  SPoRT has conducted a range of research in key areas including modeling and satellite data assimilation, remote sensing, and lightning.  In addition, SPoRT has partnered with other researchers, product/algorithm developers, and end users to assess products in the operational environment, create training, and assess their utility.  The team has observed research capabilities transform into operational products as a result of end user interaction and many of those examples are highlighted above! Into the next decade SPoRT will continue to foster interaction between research and operations as well as conduct research in focus areas that include lighting, synoptic/mesoscale meteorology, tropical meteorology, land surface modeling, health/air quality, and hazards.  SPoRT has already begun engaging in new NASA missions such as TEMPO and TROPICS that will bring unprecedented observations to benefit science and applications.  In addition, SPoRT is using their expertise in transition of research to operations to anticipate applications of future missions by actively participating in the NASA Decadal Survey Designated Observable studies.  We look forward to continuing to bridge the gap between research and operations, bringing new NASA capabilities to end users, in the new decade ahead! Thank you to all the SPoRT team members,  collaborators, and end users who have contributed to many of the projects described above.

Tracking Snow Squalls with our NESDIS mSFR product

Written by Sebastian Harkema

On December 18th/19th, the National Weather Service (NWS) produced over 40 snow squall warnings in the northeastern portion of the United States. Snow squalls are fast moving and are extremely hazardous, as snowfall rates can exceed 1 in/hr and drastically drop the visibility to near zero. One such squall created whiteout conditions in midtown Manhattan for a short period of time and another caused a major pileup on I-80 in central Pennsylvania.

The first snow squall warning was issued at 1815 UTC on 18 Dec. 2019 near the Finger Lakes region of New York. From this point forward the NWS had numerous snow squall warnings over the next 6+ hours from Pennsylvania to Maine. Two hours after the first warning was issued, the NWS issued the first snow squall warning for New York City which provided residences with at least 10 minutes of lead time before whiteout conditions would occur. The ability to identify these snow squalls highlights the hazards that these phenomena are associated with, and could be lifesaving now and in the future.

Fig 1: NESDIS mSFR product and NWS snow squall warnings (light blue polygons) from 1300 UTC on 18 Dec. 2019 through 0250 UTC on 19 Dec. 2019.

With a temporal resolution of 10 minutes, forecasters can use our NESDIS merged snowfall rate (mSFR; Meng et al. 2017) product to track snow squalls with the heaviest snowfall rates. SPoRT has collaborated with NESDIS to transition this experimental product to the NWS forecast offices. Figure 1 (above) highlights the mSFR product from 18 Dec. 2019 at 1300 UTC to 19 Dec. 2019 at 0250 UTC, with NWS snow squall warnings popping up in light blue. Throughout the event, there is good spatial and temporal correlation between the warnings and regions of heavier snowfall rates. At 2100 UTC, the mSFR product indicates snowfall rates at or above 1.5 in/hr around New York City (Fig. 2; below). Around this time, numerous videos were produced showing the visibility dropping drastically in a short period of time.

Fig. 2: NESDIS mSFR product and NWS snow squall warnings at 2100 UTC on 18 Dec. 2019 for the snow squall that caused whiteout conditions in midtown Manhattan.

Additionally, something interesting shows up in the mSFR product data over New Hampshire. A snow squall warning was issued at 2318 UTC for central New Hampshire with the squall associated with snowfall rates exceeding 2 in/hr (Fig. 3; below). Over the next 60 minutes, it appears as though the snow squall “bows out” and quickly dissipates just as the snow squall warning expired at 0015 UTC on 19 Dec. 2019. Again, this demonstrates the benefit of the mSFR product, which can be used in tandem with other methods and/or observations to identify mesoscale snow squalls.

Fig. 3: NESDIS mSFR product and NWS snow squall warnings at 2300 UTC on 18 Dec. 2019 for a snow squall that appears to be bowing out.

With meteorological winter officially starting on Dec. 1st, we are likely to see numerous snow squall events in the coming months. Be aware and stay safe, especially if you’re caught on the road, when one of these snow squalls moves through. The mSFR product enhances situational awareness for many winter weather scenarios including the ability to track these mesoscale snow squalls. See the JPSS Quick Guide and a past JPSS Science Seminar for more product information.


Meng, H., Dong, J., Ferraro, R., Yan, B., Zhao, L., Kongoli, C., Wang, N.‐Y., and Zavodsky, B. (2017), A 1DVAR‐based snowfall rate retrieval algorithm for passive microwave radiometers, J. Geophys. Res. Atmos., 122, 6520– 6540, doi:10.1002/2016JD026325.

Storm Tracking and Monitoring with the Geostationary Lightning Mapper (GLM)

Written by Chris Schultz

One of the unique capabilities of the Geostationary Lightning Mapper (GLM) is two-dimensional mapping of lightning from space.  This two-dimensional information allows for the tracking of storm features in space and time, while providing insight into the strength and magnitude of mixed phase vertical motion in thunderstorms.  During the severe weather event across the Southeast US on December 16-17, 2019, GLM information helped identify discrete mixed phase updrafts within a convective line as it moved across North Mississippi, Southern Tennessee, and North Alabama.  Often co-located with these discrete updraft locations was low-level rotation that produced wind damage and possible tornadoes, pending the outcome of storm surveys at the time of this post.

We begin the analysis at 2200 UTC, as the line is pushing through Northeast Mississippi and South Central Tennessee (Figure 1). Horizontal reflectivity (left) and radial velocity (center) at 0.5 degrees elevation shows a solid line of convection and three distinct areas of low-level rotation from the Columbus, MS NEXRAD radar, KGWX.  Co-located with each of these rotation areas were local maxima in GLM flash extent density (FED; Figure 1, right panel), with the highest values located with the strongest rotation in Prentiss and Alcon Counties in Mississippi.

Fig 1. Horizontal reflectivity (left), radial velocity (center) and GLM flash extent density (right) and 22:00 UTC on Dec. 16, 2019

Stepping forward 30 minutes to 2230 UTC, the three main areas of rotation at low-levels continue to be co-located with local maxima in GLM FED (Figure 2). The FED has increased near the circulation in Hardin and Wayne Counties in Tennessee, while the other two FED maxima have maintained or slightly weakened their intensity. The low-level circulation in Itawamba County Mississippi remains strong as it crosses the Alabama/Mississippi state line, while the southern circulation has weakened.

Fig 2. As in Fig 1, but for 22:30 UTC on Dec. 16, 2019

At 2300 UTC the storms have exited Mississippi and entered Northwest Alabama (Figure 3).  The strong rotation in southern Tennessee continues near Lawrenceburg, and FED continues to indicate strong lightning activity and a robust mixed phase updraft. Two areas of concentrated GLM activity have emerged in Lauderdale and Colbert Counties in Alabama, both co-located with low-level rotation signatures (this time from the NEXRAD at Hytop, Alabama, KHTX).  Shortly after this time, a tornado debris signature was observed on the southernmost area of interest as the storm entered Lawrence County Alabama. 

Fig 3. As in Figs 1-2, but for 23:00 UTC on Dec. 16, 2019

By 2330 UTC, the northern and southern-most areas of concentrated FED have weakened, but continue to be co-located with areas of rotation (Figure 4). The center area of interest that developed around 2300 UTC in Figure 3, has ramped up in intensity.  Strong low-level radial velocity signature now straddles the Tennessee/Alabama border.

Fig 4. As in Figs 1-3, but for 23:30 UTC on Dec. 16, 2019

At 0000 UTC, the area of interest along the Alabama/Tennessee state line continues to show strong lightning activity co-located with low-level rotation (Figure 5).  The southernmost circulation has taken on a backward C shape indicating strong low-level winds, and coincidentally, the GLM activity has ramped down at this location, indicating less robust mixed phase updrafts.  The northernmost area of interest in Bedford County, Tennessee has ramped back up, and a strong low-level signature continues. By 0030 UTC, the low-level rotation along the Tennessee/Alabama state line and in South Central Tennessee have weakened (Figure 6). GLM activity has ramped down, indicating that strong mixed phase updrafts are not as prevalent in these storms as they had been in the previous 2.5 hours.

Fig 5. As in Figs 1-4, but for 00:00 UTC on Dec. 17, 2019
Fig 6. As in Figs 1-5, but for 00:30 UTC on Dec. 17, 2019

Talking with WFO Huntsville this morning, their forecasters were utilizing the GLM measurements for critical situational awareness and as another metric for intensification within their warning decision framework. Thus, this case is one example of how radar and GLM can be complementary in a warning decision environment.

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.



Observing the First Major Thundersnow Outbreak of the 2019-2020 Winter Season

Written by Sebastian Harkema and Emily Berndt

The first major heavy-banded snowfall event of the 2019-2020 winter season occurred from Oct. 9-12 and produced over two feet of snowfall in North Dakota. Throughout the event, the NESDIS merged snowfall rate (mSFR; Meng et al. 2017) product tracked the heaviest snowfall rates, including bands with snowfall rates greater than 2 in/hr. With a temporal resolution of 10 minutes, this product can be used in real-time to forecast the location and evolution of snowbands producing heavy snowfall, and even anticipate cloud-seeding. SPoRT has collaborated closely with NESDIS to experimentally transition and assess the passive microwave and merged snowfall rate products with NWS forecast offices (Ralph et al. 2018).  Therefore, this product is available in AWIPS and forecasters can select different snow-to-liquid ratio values to best fit the situation.

Figure 1: NESDIS mSFR product and GOES-EAST ABI (Ch. 13) on October 9, 2019.

Figure 1 demonstrates the mSFR product overlapping GOES-East ABI (channel 13) for October 9th as the snowband traversed across Montana. While the mSFR product provides a unique way to monitor snowfall, the phenomenon known as thundersnow captivated the attention of some operational forecasters as well as the general public, in part by the availability of Geostationary Lightning Mapper (GLM) observations. Recent work from NASA SPoRT has shown that the overlap of GLM and mSFR data can be used to objectively identify and characterize electrified snowfall (i.e., thundersnow; Harkema et al. 2019a). In fact, Harkema et al. 2019a demonstrated that thundersnow flashes identified by GLM contain on average more total optical energy per flash area than other flashes in the GLM field-of-view. Harkema et al. 2019a also demonstrate that thundersnow flashes observed by GLM are spatially larger compared to non-thundersnow flashes and is likely a result of weaker mesoscale updrafts and slower charging rates compared to severe summertime convection.

Figure 2: NESDIS mSFR product, GOES-EAST ABI (Ch. 13), and GLM flash extent density observations on October 10, 2019.

Figure 2 demonstrates the objective identification of thundersnow based on the overlap of mSFR and GLM flash extent density observations on October 10th around the Colorado/Nebraska/Wyoming border region. From the loop, this region experiences an enhancement of snowfall rates approximately 30-40 minutes after the first occurrence of thundersnow. Even though it appears as though thundersnow can be used as a precursor for enhancement of snowfall rates in the near future, thundersnow has a spatial offset of 131±65 km from the heaviest snowfall rates (Harkema et al. 2019b, In Review). This spatial offset is evident when examining the thundersnow that occurred along the Minnesota/Manitoba border between 12-15 UTC on October 11th (Fig. 3).

Figure 3: NESDIS mSFR product, GOES-EAST ABI (Ch. 13), and GLM flash extent density observations on October 11, 2019.

The thundersnow observed by GLM occurs on the northern extent of the heaviest snowfall rates (purples/whites). The separation of thundersnow and the heaviest snowfall rates is likely caused by hydrometeor lofting of the snowfall as it descends to the surface because of the low terminal fall speed of the ice crystals.

Winter is fast approaching and the NESDIS mSFR product and GLM can be used in tangent with each other to improve situation awareness. NASA SPoRT is at the forefront of understanding the operational implications of electrified snowfall and continues to investigate the thermodynamic and microphysical properties that are associated with it. See the official JPSS Quick Guide and a past JPSS Science Seminar for more product information.


Harkema, S. S., C. J. Schultz, E. B. Berndt, and P. M. Bitzer, 2019a: Geostationary Lightning Mapper Flash Characteristics of Electrified Snowfall Events. Wea. Forecasting, 43(5), 1571–1585,

Harkema, S. S., E. B. Berndt, and C. J. Schultz, 2019b: Characterization of Snowfall Rates, Totals, and Snow-to-Liquid Ratios in Electrified Snowfall Events from a Geostationary Lightning Mapper Perspective. Wea. Forecasting. In Review.

Meng, H., Dong, J., Ferraro, R., Yan, B., Zhao, L., Kongoli, C., Wang, N.‐Y., and Zavodsky, B. ( 2017), A 1DVAR‐based snowfall rate retrieval algorithm for passive microwave radiometers, J. Geophys. Res. Atmos., 122, 6520– 6540, doi:10.1002/2016JD026325.

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

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.