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, https://doi.org/10.1175/WAF-D-19-0082.1.

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.

Merged SFR Product Fills Radar Gap over Northeastern NM

A powerful jet stream approached NM from the Pacific Northwest on February 23, 2016 and carved out a large scale upper level trough over the southern Rockies. Meanwhile, a strong area of surface high pressure raced southward down the front range of the Rockies and provided an influx of moist, cold air into eastern NM. Winter storm warnings were issued for several counties in northeastern NM with winter weather advisories in a few surrounding zones. Forecasters were eagerly anticipating how the event would unfold on the merged SFR product given the recent stretch of very dry and exceptionally warm weather. Figure 1 below is a Graphical Briefing issued prior to the event with expected snowfall totals.

Figure 1. Graphical Briefing issued prior to the expected snowfall event over northern and central New Mexico.

Figure 1. Graphical Briefing issued prior to the quick hitting winter storm event over northern and central New Mexico.

Rain and high terrain snow developed from north to south late on the 22nd before transitioning to all snow early on the 23rd. Forecast models from the 21st indicated that an area of heavy snow would impact northeastern NM on the 23rd. Figure 2 shows a well-defined axis of higher snowfall rates stretching from Trinidad, CO to Capulin, NM and Tucumcari, NM in the stand-alone SFR product from 0912 UTC 23 February 2016. Sampling this area showed peak liquid equivalent values near 0.07″/hr. The 0900 UTC observation at Trinidad showed the visibility had fallen to 1/2 mile within the snow band while the observation at Raton, NM showed no snowfall where the SFR product had near zero values. Farther south near Tucumcari the observation showed unknown precipitation falling at a temperature of 36° south of the main snow band.

Figure 2. Snowfall Rate product from 0912 UTC 23 February 2016 over northeastern NM. An area of higher snowfall rates is shown stretching from near Trinidad, CO to Capulin, NM and Tucumcari, NM.

Figure 2. SFR product from 0912 UTC 23 February 2016 over northeastern NM. An area of higher snowfall rates is shown stretching from near Trinidad, CO to Capulin, NM and Tucumcari, NM. Values peaked near 0.07″/hr.

The following merged SFR image at 0940 UTC showed the area of higher snowfall rates persisting (Figure 3 (left)). A merged SFR product from 0950 UTC is shown to note the extent of the radar void area (Figure 3 (right)). The following stand alone SFR product at 1245 UTC indicated the higher rates had shifted farther south but were still impacting at least portions of this same area (Figure 4). In this example the observation at Las Vegas, NM was indicating snowfall with visibilities down to 1 1/4 miles while Tucumcari showed very light snow with no values on the SFR product.

Figure 3. Merged SFR product from 0940 UTC (left) and 0950 UTC (right) showing snowfall detection in radar void area of northeastern New Mexico.

Figure 3. Merged SFR product from 0940 UTC (left) and 0950 UTC (right) showing snowfall detection in radar void area of northeastern New Mexico.

Figure 4. SFR product valid 1245 UTC 23 February 2016 showing higher snowfall rates persisting over northeastern NM.

Figure 4. SFR product valid 1245 UTC 23 February 2016 showing higher snowfall rates persisting over northeastern NM.

Based on the peak values depicted in the SFR product and the persistence of the snow band in the area forecasters were anticipating snowfall reports in the 2 to 6 inch range. The Snow-Cloud RGB product later in the day in Figure 5 verified this area of snowfall very well (red shades). Spotters reports are overlaid on the RGB imagery. Feedback from forecasters during this event supported accurate observations of the SFR product during the transition from rain to snow as well.

Figure 4. Snow-Cloud RGB product from 2014 UTC 23 February 2016 showing a band of snowfall over northeastern NM overlaid with spotter reports.

Figure 5. Snow-Cloud RGB product from 2014 UTC 23 February 2016 showing a band of snowfall over northeastern NM overlaid with spotter reports.

SFR performance during transition from rain to wintry precipitation.


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?


Snowfall Rate Provides Guidance for New Mexico Snow Event

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.


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).


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.

Some Observations of the NESDIS Snowfall Rate Product During the early February 2016 Central Plains Snowstorm

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.


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.


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).


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.


Life of Winter Storm Jonas as seen by the NESDIS Snowfall Rate Product

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.


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.



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:


NESDIS Snowfall Product Captures Unfolding Winter Weather in the South

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.


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.

SFR Product Verifies Snow Coverage over Four Corners

The NESDIS Snowfall Rate (SFR) product assessment is in full swing at NWS Albuquerque and forecasters are already capturing some good cases over data sparse regions. The first week of January 2016 was very active across New Mexico as back to back winter storm systems crossed the area. The second system in the series crossed over the Four Corners region on 4 January 2016, producing light to moderate snowfall rates for several hours. The forecaster on shift noted the observation at Farmington, NM (KFMN) indicated light snow with a visibility of 5 statute miles. A quick glance at the SFR procedure used in Figure 1a shows the extent of any precipitation echoes well to the east of KFMN at 0000 UTC 5 January 2016. The nearest radar (KABX, not shown) is located roughly 150 miles southeast of KFMN near Albuquerque, NM. The arrival of a SFR product at 0010 UTC 5 January 2016 showed the extent of the precipitation was much greater with the merged POES image overlaid on the radar data (Figure 1b). Sampled liquid equivalent values in the light green areas to the east of KFMN were near 0.03″/hour.

Figure 1a. Liquid equivalent values of the merged SFR product valid 0000 UTC 5 January 2016. KFMN is denoted by the white circle. Note the extent of the radar coverage is well east of KFMN.

Figure 1b. Liquid equivalent values of the merged SFR product valid 0010 UTC 5 January 2016. KFMN is denoted by the white circle. Note the extent of the snowfall coverage is much greater with the addition of the POES image.

The Terminal Aerodrome Forecast (TAF) issued for KFMN shortly before the receipt of this image indicated temporary fluctuations in the visibility to 1 statute mile with light snow and an overcast ceiling near 1,200 ft between 0000 UTC and 0400 UTC (Instrument Flight Rules, IFR). It is not clear whether any operational changes occurred based on the receipt of the merged SFR product or whether the product increased confidence on the IFR forecast. However, it is entirely possible given the improvement in product latency compared to the 2015 assessment that the imagery could be used in this way.

The webcam available at San Juan College just a short distance from the KFMN observation showed significant decreases in the visibility between 330pm and shortly after sunset (Figure 2a and 2b). The two images below show the decrease in surface visibility as well as notable accumulations on grassy surfaces in front of the college. An observer 3 miles southeast of Farmington did report a total accumulation of 1″ from this event. The merged SFR product did in fact show higher rates immediately to the east of KFMN. The last image in the series shows the impact on travel conditions noted by the NM Department of Transportation web page (Figure 3). The areal coverage of the difficult travel impacts (yellow highlights) was greater than that depicted by what can be seen based on poor radar coverage.

Figure 2a. Webcam at San Juan College around 330pm. Note the light snowfall beginning to develop over the distant mesas behind the college.

Figure 2a. Webcam at San Juan College around 330pm. Note the light snowfall beginning to develop over the distant mesas behind the college.

Figure 2b. Webcam at San Juan College shortly after sunset. Note the dramatic decrease in visibility and light snow accumulations on grassy surfaces in front of the college.

Figure 2b. Webcam at San Juan College shortly after sunset. Note the dramatic decrease in visibility and light snow accumulations on grassy surfaces in front of the college.

Figure 3. Screen capture of NM DOT web page showing areal coverage of difficult travel conditions (yellow highlights) and some text summaries detailing the impacts.

SFR picked up band of heavier snow across some areas…but not as well in others.

Another arctic front and associated precipitation moved across the region on Tuesday (Jan 12, 2016). The airmass was cold enough that the precipitation generally began as snow and remained as snow during the event.

A band of heavier snow developed along the arctic front as it pushed across Ohio into Pennsylvania and West Virginia. When comparing the SFR image and the radar, the SFR product picked up the band of heavier snow quite well across southwest Pennsylvania. Some places in the heavier band of snow in Pennsylvania reported visibilities of 1/4 mile.

The band of heavier snow extended southwest along the Ohio River across southeast Ohio into Kentucky with some visibilities of a mile or less. However, the SFR product did not seem to pick up the band in southeast Ohio or Kentucky as well. In fact, it seemed to miss the snow in Kentucky all together.

Based on the radar mosaic, it appears the band of snow across southeast Ohio and portions of Kentucky was generally as intense as that across southwest Pennsylvania. However, the band in southeast Ohio and Kentucky was not as wide. Could this be part of the reason for the SFR not indicating as heavy snow in southeast Ohio and Kentucky?

1840Z 12_Jan_16 SFR product

1842Z 12_Jan_16 Radar Mosaic

19Z 12_Jan_16 Surface Observations

Latest Version of NESDIS Snowfall Rate Product in AWIPS

Researchers at the National Environmental Satellite and Information Service (NESDIS) have recently wrapped up development of the latest iteration of their Snowfall Rate (SFR) product to aid WFOs in situational awareness of snowfall events and snowfall forecasting.  The developers within NESDIS have teamed up with SPoRT, utilizing SPoRT’s unique transition, training, and evaluation capabilities to deliver the SFR products to several WFOs in the CONUS and Alaska.  During the evaluation period this winter, I will be evaluating the SFR and merged SFR products for use mainly here in the Tennessee Valley (provided the atmosphere obliges), but I will also be looking at the product CONUS-wide (and perhaps AK too, as the opportunity affords).

The SFR products are being delivered in two main versions: a merged snowfall rate product (merged polar-orbiter and radar data) and a product that contains only data from polar orbiters.  Through collaboration with researchers and forecasters (especially at the Boulder NWS office), SPoRT is including SFR data with liquid to snow ratios of 10:1, 18:1, and 35:1.  These data are being ported in AWIPS II workstations at the NWS offices.  In the merged product, the polar swath data are complimented with NSSL’s Multi-Radar/Multi-Sensor (MRMS) precipitation data, and update much more frequently (every 10 minutes).  Swaths containing polar orbiter data of course come in as associated polar orbiter swaths cross a region, with updates from about every 30 minutes to as long as ~4-5 hours over any location.

A look at the products the past several days has brought the opportunity for some initial evaluation.  So far, the SFR product looks rather promising.  Here’s a quick look at the product as a snowstorm was ongoing yesterday evening (Dec 15th) across the northern/central Rockies and the Northern Plains.  The loop below (Image 1) shows data from 0110Z through 0410Z 16 Dec 2015.

NESDIS Merged Snowfall Rate Product (showing 10:1 liquid to snow ratio) 0110Z to 0410Z 16 Dec 2015

Image 1.  NESDIS Merged Snowfall Rate Product (showing 10:1 liquid to snow ratio) 0110Z to 0410Z 16 Dec 2015

The loop above shows the Merged Snowfall Rate product (displaying 10:1 liquid to snow ratio).  Most of what you see is the MRMS precipitation during the loop.  At the end of the loop however, you will notice a sudden expansion of the apparent snowfall over the region as an insertion of snowfall rate derived from a polar orbiter swath is incorporated into the product.  So, let’s take a closer look at that single image containing the polar orbiter data (Image 2).


NESDIS Merged Snowfall Rate product (10:1 ratio) with polar orbiter data insertion, 0410Z 16 Dec 2015

Image 2.  NESDIS Merged Snowfall Rate product (10:1 ratio) with polar orbiter data insertion, 0410Z 16 Dec 2015

In the image above, you will notice that MRMS data remain and replace satellite retrievals where these data are available.  That is, the MRMS data take precedence over the satellite data in the merged SFR product.  However, data are inserted for locations where snowfall is detected by satellite instruments and radar (MRMS) data are not available.  For large areas of Wyoming and Colorado, where radar coverage is certainly more limited, notice that the insertion of polar-orbiter data allowed for a more thorough and proper analysis of locations likely experiencing snowfall.  Many of the surface observations (in yellow) likewise corroborate the snow that was occurring, particularly for locations in Wyoming, where coverage from radar data alone was very lacking.  However, there are some surface observations that do not corroborate where the SFR product is indicating snowfall.  Multiple reasons for this apparent discrepancy may exist, but it’s important to remember that the polar orbiting satellite instruments are detecting snowfall in the clouds.  Some of this snowfall may not be reaching the surface due to sublimation aloft.  Also, the snowfall could be very light and patchy in some instances with detection issues at some of the automated ground observation sites.

Now, let’s take a quick look at the polar orbiting data alone (Image 3).

NESDIS SFR product (liquid to snow ratio 10:1) 0345 UTC 16 Dec 2015

Image 3.  NESDIS SFR product (liquid to snow ratio 10:1) 0345 UTC 16 Dec 2015

The resolution of the polar orbiting data still allowed for the detection of banded structures across parts of the Dakotas that were evident in the MRMS data.

Further evaluations and posts about this product will be forthcoming as we progress through the winter.  Perhaps I’ll have the chance at some point to evaluate the product here in the Tennessee Valley…that is, if the current mild Eastern U.S. pattern changes.