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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).

2016-02-09-1644_LESBand-LEO-wLakes-Aug

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.

SnowCloud_10Feb2016_Aug

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.

MODIS Air Mass RGB (left) and 11 um image (right) from 08 February 2016 at 1427 UTC.

MODIS Air Mass RGB (left) and 11 um image (right) from 08 February 2016 at 1427 UTC.

An image captured this morning by the MODIS Terra instrument shows an impressive cyclone off the eastern coast of the US. The image on the left shows the cyclone in SPoRT’s Air Mass RGB and the image on the right shows the 11.0 µm from Terra (from 8 February 2016 at 1427 UTC). The deep red color on the RGB shows the intrusion of ozone-rich stratospheric air, which is an indication of deformation zones, jet streaks, and potential vorticity anomalies associated with rapid cyclogenesis, which itself indicates strong winds at the surface. This RGB is also limb-corrected for cooling at the edges of the swath, so we can assume the cyclone in this imagery is every bit as intense as it looks.

The new generation of geostationary satellites being deployed globally, such as Himawari, MTG, and GOES-R, will allow us to observe imagery like the Air Mass RGB several times an hour, enabling us to watch the cyclogenesis as it happens.

Forecaster Jennifer Palucki from Albuquerque, New Mexico submitted a nice case study to our online evaluation form being used during the current 2016 NESDIS Snowfall Rate Evaluation.  Here are some of her discussion and impressions of using the product:

A very well defined band of snow developed along a frontal boundary extending from the southern Sangre de Cristo Mountains, toward Las Vegas, and continued southeastward toward Melrose. Initially the southeast part of the band was rain, but as temps dropped it changed to snow. At 0052z (552pm MST; see image below) the merged SFR likely did very well distinguishing where there was snow and no snow, however, in areas that there was snow, amounts were way underdone. At 545pm, approximately 4″ of snow had fallen in Sapello in the southern Sangre de Cristo Mtns. Snow likely started around 1 or 2pm, which is an average of about 1″/hr compared to the 0.3″/hr the SFR product was showing with an 18:1 ratio. Thus, the amounts via the SFR product were largely underdone. It was still snowing heavily according to the spotter at 545pm. At 645pm, approximately 1.5 inches of snow was reported in Las Vegas. The SFR product was showing around 0.1″/hr for this area.

ABQ_160203_0052Z_annotated_zoom

NESDIS SFR Product at 0052 UTC on 03 February 2016 showing light snow over Las Vegas, NM.

Another pass at 0330z (830pm MST; see image below), the SFR product missed the southeastern extent of the snowfall, and again had amounts that were likely underdone. A report of 0.5 inches of snow in the last hour was reported at 841pm in Taos. The SFR product showed around 0.02 liquid equivalent, or around 0.3″/hr snowfall rate given 18:1 ratio (which should be close to the snow ratios in that area).

ABQ_160203_0330Z_annotated

NESDIS SFR Product at 0330 UTC on 03 February 2016 showing some heavier snow over Taos, NM.

Really like using this product to gather intel on where it is snowing in areas without radar coverage. Do have some concerns about the amounts, especially in these scenarios where the heavier amounts are likely isolated. In this case, the band was very narrow, likely no more than 10 to 15 miles wide.

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.

2Feb2016_CentralPlainsSnow-04

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.

2Feb2016_CentralPlainsSnow-05

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).

2Feb2016_CentralPlainsSnow-10

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.

 

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.

goes_lightning_23jan16_0945_v2

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)

Winter Storm Jonas tracked across the eastern United States this past weekend dropping near-record amounts of snowfall in a track from West Virginia through southern New York.  Two things about this storm are particularly interesting:  1) the heavy amounts of snow that fell for long periods of time and 2) the relatively narrow swath of the heaviest snows.  Below is the 48-hour snow accumulations from the National Weather Service ending Sunday, January 24.  It is striking that New York City received on the order of 30 inches of snow, while areas less than 100 miles to the north received little if any snow.

NWS_SnowTotals

48-hour snowfall totals ending Sunday, January 24, 2016 (from NWS Central Region).  Contours are every 3″ with the darkest reds indicating 30″ of snow.

Select Eastern Region WFOs are currently evaluating the NESDIS Snowfall Rate product, which uses passive microwave observations from 5 sensors, to observe total column snowfall rates.  Below is a series of images from this past weekend showing the SFR product displayed as a 10:1 solid/liquid conversion.  The darkest greens indicate snowfall rates at the top of the sensor detection range at approximately 2″/hr.  Depending on the actual solid/liquid ratio in individual areas, rates may have been higher.

SFR_Collage_first4

SFR_Collage_second4

NESDIS SFR Product showing the evolution of Winter Storm Jonas from late on Friday through early Sunday.  The darkest greens indicate solid snowfall rates of around 2″/hr.

In the images, the NESDIS SFR product shows very good agreement with the location and track of the heaviest snows (greens) compared to the heaviest totals in the ground reports.  Additionally, the SFR product does well in picking up the abrupt northern edge of the snowfall (especially across southern New York).

UPDATE:  The Sterling, VA WFO included mention of the SFR product in a forecast discussion to confirm snowfall rates that would cause white out conditions:

Sterling_AFD

Beginning in the morning hours of 22 January 2016, rain began to change to snow across Mississippi, Tennessee, and Alabama.  The NESDIS Snowfall Rate, which is currently being evaluated by a handful of Weather Forecast Offices, has the ability to differentiate rain from snow.  This ability was particularly important for the large winter storm impacting much of the eastern half of the United States.  The animation below shows the 10:1 Solid SFR Product with METAR station observations indicating temperatures and precipitation.

AL_TN_SFR_Example_20160122_07-19Z_slower

The animation shows the evolution of snow across the area beginning with snow in Western Tennessee and Eastern Mississippi at around 1200 UTC (6:00a local time).  Also of note at that same time is that the SFR Product indicates relatively heavy snow (~1.5 in./hr. solid snow) directly over the Nashville area; however, the METAR site at the airport is still reporting rain.  In the following hour (1300 UTC; not shown in the loop here because there was no SFR product valid near 1300 UTC) Nashville was reporting snow.  Thus, the SFR product was seeing in-cloud snow in that area that began to reach the ground within an hour of the observation.  This is one way forecasters can use the product to view in-cloud snow to determine the potential for snow to reach the ground.

Later in the period, a similar set up appears in the Huntsville area at the Madison County Executive Airport (KMDQ).  The 1853 UTC SFR product shows light snow over Madison County, but the 1900 UTC METAR was not yet reporting any snow.  However, the 2000 UTC METAR showed snow beginning to fall across the Huntsville area.  The change over to snow falling across Western Madison county into Central Madison county was between 1830 and 1900 UTC, verified as I drove home from work.

The NESDIS SFR product will continue to be evaluated as blizzard conditions begin to set up along parts of the East Coast.

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