Potential challenges of interpreting water vapor imagery: A tropical moisture case over San Diego on 21 Sep 2016

While water vapor imagery is no doubt very useful for forecasting, it can at times be tricky to interpret.  This blog discusses a particularly challenging case over Southern California on 21 September 2016, when deep tropical moisture produced a rain event for San Diego.  Even though the environment was very moist, indeed the precipitable water (PW) was a record for the date, GOES-15 water vapor imagery (with a central wavelength of 6.7 microns) implied a “dry” atmosphere.  GOES-R (now GOES-16) has 3 water vapor channels, one that senses higher in the atmosphere and the other lower than what is currently on GOES.  The central wavelengths for the new water vapor channels are similar to what is currently available from the GOES-15 Sounder, and for this case we will examine all 3 channels to see how the 2 new channels compared to what we have now on GOES.  Finally, we will also examine the CIRA/NESDIS Blended Total PW imagery and a new product being developed at CIRA, Blended Layered PW (LPW) imagery, to see what they reveal for this case.

We were alerted to this case by Alex Tardy, the WCM at the San Diego WFO (SGX), who also supplied some of the graphics.  Alex noted that the 12 UTC 21 Sep SAN sounding (below) had a record TPW for the date (chart below).




All this moisture produced widespread rain across far southern California, as depicted in the radar image shown below.


IR imagery at 1130 UTC indicates the clouds producing this rain did not extend to very high levels.  Sampling of the IR temperature near SAN yields a cloud top temperature of +1C or 274K.  Using the 12z SAN sounding this corresponds to a cloud top of about 580 mb.


First let’s look at a water vapor image near the time of the above imagery (1145 UTC) from GOES-15, which has a single channel at 6.19 microns (μ).  The weighting function (discussed further below) for the imager channel is fairly broad, extending generally from 300 to around 400 mb.  Note that over San Diego and areas to the south this water vapor channel shows a large area of warm brightness temperatures, which forecasters often interpret as indicative of a dry atmosphere.  The color table being used is the “RAMSDIS water vapor” table available on AWIPS2.













We can use water vapor imagery derived from the GOES-15 Sounder to get an idea what the 2 new water vapor channels that are on GOES-16 (-R) would show.  While the central wavelengths of the Sounder-based water vapor imagery compare to what is on GOES-16, the resolution is of course far worse (~8 km vs 2 km), and of course not as good as what is currently on GOES (4 km).  We can see this resolution difference (between GOES and the Sounder) by comparing the above image to the equivalent mid-level channel from the Sounder shown below.  Besides the resolution the imagery otherwise are fairly similar.

Slide14The 7.0 μ water vapor image shown above would generally sense somewhat lower in the atmosphere compared to the GOES imager water vapor image shown earlier.  The next image is the upper level water vapor channel from the Sounder-based imagery, shown below for the same time (1201 UTC), which would sense vertically a little higher than the current GOES imager channel.  The area of warmer brightness temperatures is not as extensive as in the mid-level imagery, indicating contribution from moisture at higher levels (the average weighting function for the 6.5 μ imagery is centered close to 300 mb for the standard atmosphere).


Perhaps the most intriguing of the new water vapor channels is the lower level channel, which from the Sounder would sense near 600 mb or lower.  The image for 1201 UTC from this channel at 7.4 μ is shown below.


Even though this channel senses lower into the atmosphere, we still see warm brightness temperatures from the SAN area southward.  These warm temperatures and by inference perhaps dry conditions are found even above an area where rain is occurring AND the environment has a record TPW level.  How is this possible?  To answer this question we need to look in more detail at what levels the various channels are actually sensing. Remember, the weighting functions depend on the temperature and moisture distribution in the environment, and the satellite viewing angle, and this means they will be sensing different levels across a domain.  Below is what the weighting functions look like for the SAN sounding that was shown earlier.


In the above figure the channel number is given for each band; Sounder Channel 10 = 7.4 μ, 11 = 7.0 μ and 12 = 6.5 μ, and the GOES imager water vapor channel is #3.  The brightness temperatures that are listed in the above figure would be equivalent to what one would find using the sampling tool on AWIPS2 for the various channels when sampling over SAN.

The weighting functions above differ from what would be calculated for the “standard atmosphere”, shown in the figure below.


The actual weighting functions are generally narrower and more complex than those from the standard atmosphere.   One important caveat to note about the weighting functions calculated for the 1200 UTC sounding is that while the viewing angle has been considered, the profiles are calculated using a forward model for clear sky conditions.  In our case we know that there are overcast conditions with a cloud top temperature derived from the IR imagery of 274K or ~580 mb over the SAN area.  The cloudy conditions would quickly saturate a given channel if it were to sense into the cloud layer, so there will be no contribution much below the top of the cloud layer.  In our case we note that if it were clear two of the Sounder channels would penetrate below the 580 mb level, so for these two channels the presence of the cloud layer should shift the actual weighting function upwards (colder), moreso for the 7.4 μ channel compared to the 7.0 μ channel.  Indeed, when we sampled these two channels over the SAN area the brightness temperatures found were 261 K for 7.4 μ and 259 K for 7.0 μ.  For the lower 7.4 μ channel this is 3 K colder than the brightness temperature listed for this channel as calculated for clear sky conditions, so a shift to higher in the atmosphere, as expected.  For the 7.0 μ channel the difference is only one degree, as would be expected smaller since that weighting function under clear sky conditions did not penetrate below the level where the cloud top occurred (580 mb).  With this in mind, for this case there was just enough moisture in the environment above the deep moist layer to saturate even the lowest water vapor channel before it sensed down to the cloud top, so it looked relatively “dry” even though we had a record TPW present in the atmosphere.

This case shows that while the new water vapor channels will be powerful tools for forecasters, we must be careful to note that they do not necessarily tell us what the moisture profile looks like through the entire atmosphere.  In other words, we cannot determine from the water vapor imagery how much PW is present in the atmosphere.  There is, however, satellite imagery that does allow one to detect the actual TPW present.  Most forecasters are familiar with this imagery on AWIPS2 known as the NESDIS Blended TPW product, which is shown for this case below.


This imagery combines measurements from several Polar satellites into a single image, hence the “blended” title and the time stamp that covers a time period instead of a single time.  The Polar satellites used have instruments that can measure the TPW even in the presence of clouds.  What we see of course for this case is the high TPW area associated with the remnants of the tropical system just to the south of San Diego, with the higher TPW values extending to the north.  We certainly get a different picture of the water vapor present in the atmosphere from this imagery compared to what we saw with the water vapor imagery.  CIRA is experimenting with a variant of this product that shows the PW in different layers, with the blended product known as the Layered Precipitable Water product (LPW).  The LPW for this case is shown below.


In agreement with what we saw in the San Diego 1200 UTC sounding, the LPW product shows moisture through the lower 3 layers but dry conditions above 500 mb (this higher level dry air is what was implied by the water vapor imagery).  This is also a blended product and while it is labeled at 1200 UTC it actually covers several hours leading up to this time.  A future version of this product will use an advective scheme that will make it more visually appealing.  This product is currently being tested at some WFOs, and if you are interested contact us and we can make it available on AWIPS2 through the LDM.



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Challenging forecast for Colorado mountains snow event of 5 December 2016

On 5 December 2016, a significant storm was approaching the mountains of Colorado with various NWS winter weather watches/warnings posted for 6 December.  This snow event on 5 December occurred ahead of the storm in what looked like drying conditions behind a fast moving shortwave.  The GOES satellite imagery seemed to support the idea of drying on 5 December in all 3 available GOES Sounder water vapor channels.  However, enough low-level moisture remained in the presence of low/mid level steep lapse rates to produce this storm before the storm  on 5 December (generally around 6 inches at most ski resorts in the central/northern Colorado Rockies) that almost matched the amount of snow that occurred with the “main” storm on 6 December.  In this blog entry, we’ll show how the low-level moisture, while not obvious in the GOES sounder/imager water vapor bands, was observed with the CIRA Layered Precipitable Water Product.

The GOES Sounder provides water vapor imagery that includes the GOES-R/16 three water vapor bands.  Of course the resolution of the GOES Sounder imagery is considerably coarser (nominally hourly at 10 km) relative to GOES-R/16.  In order to get accustomed to looking at three water vapor channels of GOES-R/16, we can make use of current GOES Sounder bands (at least for the western CONUS since GOES-East Sounder has failed).

Next, we bring up a loop of the GOES-West Sounder/Imager satellite imagery between 0602 UTC 5 December to 0602 UTC 6 December:


The water vapor imagery that forecasters are accustomed to viewing in AWIPS is the GOES Imager water vapor band at 6.5 microns as shown in the upper right panel. Keep in mind that there are notes at the bottom of each frame in the loop.  To summarize what we see, an initial shortwave moves across northern Colorado between 0600 – 0900 UTC 5 Dec. followed by another shortwave thereafter with a fairly distinct signal in all water vapor bands, all within a strong westerly jet.  The dominant signal after 1800 UTC 5 Dec. is an elongated region of warmer brightness temperatures associated with the westerly jet slowly drifting southward, most readily observed in the mid- (6.5 micron imager and 6.95 micron sounder) and upper-level (6.2 micron sounder) bands.  One thing to note is that amidst the general warming signal we see an area of cooler brightness temperatures lingering over the central mountains of Colorado; what do you think this feature is?  As will be shown in other imagery later, what we are seeing are the tops of a lower cloud layer that persists.

Next, we bring up a loop of multiple products, including the CIRA Layered Precipitable Water (LPW) product, along with GOES IR, visible as well as mosaic radar at night:


Forecasters are likely familiar with a satellite derived Total Precipitable Water (TPW) product, such as the NESDIS blended TPW product on AWIPS.  The LPW product is derived from microwave instruments onboard multiple polar-orbiting satellites.  The unique aspect of the LPW product is that the moisture is shown for 4 separate layers as indicated on the looping imagery.  Keep in mind, the resolution of the instruments is considerably less than GOES and varies between instruments which is why the products appears more “blocky” at some times compared to others.  Also, the satellite passes occur at irregular times, therefore post-processing displays what data is available at 3 hour intervals.  The product time shows the latest available satellite pass, however keep in mind the most recent pass at a point may be several hours old due to irregular satellite pass intervals.  For example, look at central Nevada between 0918 and 1218 UTC 5 December, the same data is displayed since a new pass does not occur until after 1218 UTC, which shows up in the 1517 UTC image.  This product is still experimental, however it is available from CIRA in real-time, as well as in AWIPS as a satellite proving ground product (contact us at Edward.J.Szoke@noaa.gov).  Additionally, CIRA is currently developing an advected version of the LPW product that will display at higher resolution and appear less blocky.

One of the main points to emphasize in this particular case is that we do not see a sharp north-south gradient over central/western Colorado in the 700-500 mb layer of the LPW (this is the most applicable layer for moisture flowing over the elevations of the Colorado mountains).  Let’s focus on the 0018 UTC 6 Dec. LPW imagery when we had a higher resolution pass over Colorado.  We may have concluded from the GOES water vapor imagery shown earlier that the region of warmer brightness temperatures was associated with “drying” through a deep layer upstream of the mountains (i.e., western Colorado).  The LPW product clearly shows that there is moisture present in the 700-500 mb layer at 0018 UTC across western Colorado that would still be available to later move over the mountains in the westerly flow.  We don’t see this moisture in the various water vapor bands since the weighting function profile is not low enough (even at 7.35 microns).  If moisture is your primary forecast issue, the LPW product can clarify moisture at different levels in a more definitive way than implying it from GOES water vapor imagery alone.  In this case, the moisture that remained produced a period of snow that lasted past 0600 UTC 6 Dec. in the mountains which was not predicted, perhaps owing to what looked like a drying signal in the water vapor imagery.  This shallow moisture was also way underdone by even the high resolution models which predicted almost no snowfall and as seen in some of the radar mosaic images, was not resolved by radar either (due to overshooting beam).  Here, the lower level moisture was sufficient to produce moderate snowfall because of the steep lapse rates that were present behind the initial shortwave, as seen in the Grand Junction sounding:


Also note the moisture between 600 and 700 mb which would be reflected in the LPW 700-500 mb layer imagery.

GOES IR imagery from 0000 to 0600 UTC 6 Dec. displayed above with the LPW product, shows the low clouds over the central mountains of Colorado, however they are subtle due to insufficient contrast between the low clouds and cold ground.  The clouds are less subtle in the loop below:


This is the CIRA GeoColor product which is an experimental GOES-R Proving Ground product.  The low clouds at night are peach colored because this product utilizes the 10.7 minus 3.9 micron product at night to highlight lower clouds / fog.  Note that the higher level clouds are white in this product.

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1-minute imagery of warm conveyor belt on 1-2 February 2016 winter storm


A winter storm that passed through Colorado on 1-2 February 2016 resulted in significant snowfall over northern / northeast Colorado:


One of the key aspects of this extra-tropical cyclone was the development of a warm conveyor belt (Harrold 1973).  The 4-km NSSL WRF-ARW synthetic water vapor imagery from the 0000 UTC 1 February run valid 1800 UTC 1 Feb to 0600 UTC 2 Feb:


forecasts what appears to be a warm conveyor belt (WCB) by around 0100 UTC 2 Feb, highlighted here:



Keep in mind, one the of the limitations of the synthetic water vapor imagery from the NSSL WRF is that that areal coverage of cold cloud tops tends to be underdone due to the microphysics scheme of this model run.  Interpretation should focus on the feature of interest (the WCB) rather than the specific cloud top temperatures to compare with GOES.

For this event, GOES-14 Super Rapid Scan Operations for GOES-R (SRSOR) was in effect, meaning that 1-minute imagery was collected (Schmit et al. 2015).  This is in preparation for GOES-R (scheduled for launch in October 2016) since 1-minute imagery will be available much more frequently for significant weather events.

In the 1-minute GOES-14 water vapor imagery between 1800 UTC 1 Feb to 0100 UTC 2 Feb:


We can see the development of the WCB over eastern Colorado and western Kansas, consolidating by the end of the loop:


Next, lets consider the perspective of the GOES-IR (10.7 um) 1-minute imagery:


Note the rapid expansion in areal coverage of colder cloud tops from the Texas panhandle / western Oklahoma into western Kansas then curving cyclonically westward into Colorado.  This is the WCB of interest.  Where is the surface low in this loop?  Note the highlighted region below:



In the animation near this time, we observe a circulation with colder brightness temperatures just after 2300 UTC followed by what appears to be a deformation zone that is quasi-stationary.  The surface low is slightly southeast of this zone that is quasi-stationary.

Later, between 0100 and 0600 UTC 2 Feb:


We see the continued expansion of colder cloud tops associated with the WCB that is impacting Colorado.  During this period, snowfall rates increased as a result of this WCB as heavy snow impacted much of northern / northeast Colorado.

We observe a number of interesting features in the 1-minute imagery that we normally would not see under routine GOES scanning at 15 minute intervals.  For example, note the highlighted region in the following two images at 0300 and 0418 UTC:




Closer inspection of the animated imagery during the time period shows the development of transverse bands along the western edge of the WCB (which has a well defined limiting streamline).

Moving on to the next time period of IR imagery:


We see a number of gravity waves along the edge of the WCB that appear and disappear over short-time scales, for example, note the highlighted region at 0645 UTC:


1-minute imagery from this winter storm illustrates one of the reasons why GOES-R will be a “game changer”.  The high temporal resolution imagery will show features that were not sampled adequately to be observable under current/past temporal resolution.  Since some of these features have not been seen before, there will be an opportunity for research into these new features to understand what we are observing, and more importantly, potential applications for use in operational meteorology.  Another consideration is the 1-minute imagery latency on AWIPS will be approximately 1-minute, much greater than currently available for GOES RSO (Rapid Scan Operations), this impacts how much more effectively the data could be used operationally.

For completeness, analyze the 1-minute water vapor imagery for the remainder of the event.  What additional features do you see?



How does the development of the WCB relate to the increase in snowfall rates as observed from the NESDIS Snowfall rate product retrieved from polar orbiting satellites?




Harrold, T.W. 1973: Mechanisms influencing the distribution of precipitation within baoclinic disturbances. Q.J.R. Meteorol. Soc., 99, 232-251.

Schmit, T.J., and Coauthors, 2015: Rapid Refresh Information of Significant Events: Preparing Users for the Next Generation of Geostationary Operational Satellites. Bull. Amer. Meteor. Soc.96, 561–576.

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Himawari imagery of 924 mb low in the Pacific

At 0600 UTC 13 December 2015, the NOAA Ocean Prediction Center analyzed a 924 mb surface low in the north Pacific in the vicinity of the western Aleutian islands:


The analyzed minimum central pressure of 924 mb ties the record for lowest pressure in the north Pacific during the period of record (since the winter of 1969-1970).

Satellite imagery from the new Japanese satellite (Himawari-8) provided a spectacular perspective of this cyclogenesis event.  First, we will look at the larger scale by analyzing the RGB airmass product (please allow sufficient time for this loop to load):


Warmer air is displayed in green and red where the green regions have higher moisture content than the red regions. Mid-latitude air has a bluish color and areas of dark red show areas of subsidence and high ozone and potential vorticity.   Click here for more detailed information.

The first feature that catches your attention is typhoon Melor east of the Philippines.  As you may suspect for an intensifying tropical cyclone, green colors in the vicinity of the storm indicate higher moisture.

Focusing our attention to the extra-tropical cyclone further north.  Early in the loop, we see the system over Japan moving northeast with a trailing deformation zone on the northwest flank of the cyclone.  In time, this feature dissipates as we see the system intensify, it develops a comma cloud followed by a strong surge of high ozone air (orange/red colors) associated with the dry slot.  This corresponds to a stratospheric intrusion deep into the troposphere.  Soon after this feature we see a cusp that develops and eventually wraps cyclonically around the upper low until becoming vertically stacked by the end of the loop.  Note the red/orange colors during this process as well, corresponding to high potential vorticity that is tracked by the high ozone air caused by the stratospheric intrusion.

Next we’ll look at the longwave infrared (11 um) loop zoomed in over the north Pacific:


In this channel, we can see low-level cumulus clouds which correspond to low-level cold advection over the relatively warm sea surface.  The position of the cold front can readily be tracked by following the low-level cumulus.  When the cold front wraps around the low and intersects the warm front, the occlusion process begins.  The leading edge of the relatively colder clouds that wrap around the system appear to be associated with a sting jet.  Wind gusts over 100 knots were observed with this storm.

Finally, we analyze a zoomed in perspective of Himawari True Color / Geocolor imagery:

Alternately, you may view this loop:


True color imagery is shown during daylight hours, and Geocolor imagery is shown during nighttime hours.  The CIRA Hybrid Atmospherically Corrected (HAC) method is applied to produce this “true color” imagery.

The Hybrid Atmospherically Corrected (HAC) true color method uses the red, green, and blue Himawari bands, in addition to some information from bands 4 (0.86 micrometers) and 13 (10.4 micrometers).  A Rayleigh correction is performed at each band in order to correct for the effects of Rayleigh scattering.  The result is an image that is significantly more crisp and clear, and less milky, than without the correction.

Once the imagery transitions over to nighttime the CIRA Geocolor algorithm is applied to the imagery.  White colors are high level ice clouds, reddish colors represent lower level liquid water cloud and city lights (static) are shown in yellow.

For more detailed information on analyzing spiral rings around extra-tropical cyclones, see this article.

Real-time Himawari-8 imagery may be viewed at:



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Himawari-8 True Color / Geocolor product

CIRA now provides Himawari-8 daytime true color imagery and nighttime geocolor imagery:


The example above begins at 0230 UTC 12 November 2015 with most of the scene in daylight, therefore true color imagery is shown.  The CIRA Hybrid Atmospherically Corrected (HAC) method is applied to produce this “true color” imagery.

The Hybrid Atmospherically Corrected (HAC) true color method uses the red, green, and blue Himawari bands, in addition to some information from bands 4 (0.86 micrometers) and 13 (10.4 micrometers).  A Rayleigh correction is performed at each band in order to correct for the effects of Rayleigh scattering.  The result is an image that is significantly more crisp and clear, and less milky, than without the correction.

Once the imagery transitions over to nighttime the CIRA Geocolor algorithm is applied to the imagery.  White colors are high level ice clouds, reddish colors represent lower level liquid water cloud and city lights (static) are shown in yellow.  More information on the Geocolor imagery may be found here:


Real-time Himawari-8 imagery may be viewed at this page:


See the “Full Disk AHI True Color” for the imagery in the example illustrated above.

A similar product is planned for GOES-R so you may familiarize yourself with this imagery from the Himawari-8 satellite presently.

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GOES-14 SRSOR 1-minute visible imagery for 19 May 2015 over Texas

GOES-14 will be in Super Rapid Scan Operations for GOES-R (SRSOR) mode between 18 May – 12 June, 2015.  This special mode allows for 1-minute temporal imagery for GOES, similar to what will be available when GOES-R becomes available in 2016.

We will discuss the 1-minute imagery over Texas on 19 May, 2015.

First, we will look at the early period between 1730 to 1940 UTC:


Regions of convection at this time include:

1) southeast Texas (moving southeast), which leaves behind a stable air mass (clear area to its northwest)

2) central Oklahoma

3) eastern Texas panhandle moving into western Oklahoma

Next, we turn our attention on southwest Texas.  We see indications of developing cumulus along a dryline (clear to the west).  The northern portion of the developing cumulus has multiple failed attempts at convective initiation since the anvils get detached (commonly called orphan anvils) from the main updraft base.  By the end of the loop we begin to see more robust looking cumulus slightly further south down the dryline.

Next, we’ll look a the period between 1941 to 2136 UTC:


We keep our attention in southwest Texas along the dryline and note that convective initiation occurs in two areas (a northern area and southern area), along the dryline.  The northern area continues to show the earlier trend, which is soon after development the storms dissipate (perhaps moving into more stable air?) then another storm develops and follows the same fate.  Meanwhile the storm to the south quickly expands and intensifies with multiple reports of tornadoes associated with it. We see cumulus streets just southeast of this storm indicating an unstable air mass that is feeding into this storm.  We also see a nearly east-west oriented line of cumulus on the western flank of the storm.  This appears to be a pre-existing convergence line that is augmented by the flanking line of the storm itself.  Note the northern storm eventually dies off by the end of this loop, storms had struggled to persist in this region earlier, and now with the larger storm to the south it may have completely cutoff the inflow into the northern storm.

Look at convection developing in other parts of Texas and Oklahoma, notice how much more clear features appear in 1-minute imagery relative to what you are used to analyzing.  A cold front exists in the northern Texas panhandle extending northwest into northeast New Mexico, stratus clouds and/or stable wave clouds exist behind the cold front.  Any convection that crosses the cold front briefly are enhanced along the cold front but quickly dissipate as they move to the cold side of the front where CAPE goes away.  The convection in western Oklahoma leaves behind an outflow boundary that may play a role later in the day.

Now we will consider our final loop between 2137 to 2349 UTC:


Our storm in southwest Texas continues to exhibit numerous characteristics of a severe storm – overshooting top, back-sheared anvil, crisp edge to the anvil cirrus, flanking line with enhanced cumulus and unstable air (cumulus streets) feeding into the storm.  Note the weaker storm that developed near the Mexican border and moved north, the pulsing updraft with that storm can be followed underneath the anvil cirrus of the dominant storm for a while.  It looks like it moves just east of the main updraft of the more intense storm.

In the Texas panhandle, we see an MCS outflow boundary that originated from the MCS in western Oklahoma oriented ESE to WNW with an area of convection riding along that boundary that seems to enhance the intensity of the convection.  Further north and west, we see the cold front with its stratus clouds behind it, and any convection that crosses it towards the cold air quickly dissipates.

Further east, just west of the Dallas metroplex and south of the Oklahoma-Texas border we see a number of new thunderstorms developing.  A number of these were severe including tornadoes.  Note the anvil orientation is towards the southeast, different than some of the other anvil orientations we were looking at for other storms.  Remember that anvil orientation is a function of the vector difference between the mid-level steering flow (in this case west-southwest) and storm motion.  The storm motion varies across Texas, accounting for the different anvil cirrus orientations that we observe.

Real-time 1-minute imagery may be viewed here:


Also, be sure to check out the CIMSS Satellite blog entry on this same event:


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Synthetic imagery from the 4-km NSSL WRF-ARW model for the 22 April 2015 severe weather event

This blog entry consists of a youtube video:



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10 November 2014 Colorado Dust Storm Matched to Aircraft Photo

By Steve Miller (CIRA)

This blog entry is in Powerpoint show format, click on the link below to view the Powerpoint show:

Powerpoint show file

Posted in Blowing Dust (Blue-light absorption technique), Blowing Dust Detection (Split-window technique) | Leave a comment

Leeside cold front of 10 November 2014: Blowing dust and deep-tropospheric gravity waves

A strong cold front pushed southward across the Plains during the day on November 10, 2014.  The temperature gradient across the front was quite dramatic, as seen by the surface observations at 23:00 UTC:


Visible imagery from GOES-East during the afternoon hours centered over Colorado clearly showed the southward progress of the cold front as dust was being lofted at the edge of the cold front where surface winds are strongest:


Note the rapid movement of the cold front as it moves from southeast Colorado towards northeast New Mexico as you can easily trace it by the blowing dust.

The GOES-West shortwave albedo product also clearly shows the blowing dust:


Confirming the existence of the dust is this webcam along I-25 at Raton Pass (along the New Mexico / Colorado border):


Another interesting aspect of this event are the deep-tropospheric gravity waves created by the leeside cold front.  The GOES water vapor imagery shows narrow bands coincident with the cold front as it moves southward immediately to the lee of the Rockies:


Relatively strong vertical motion exists along these narrow bands in a broad zone through the upper troposphere and into the lower stratosphere.  The resulting vertical displacements are up to 1 km, making them appear in the water vapor imagery.

Interestingly enough, the synthetic water vapor imagery from the 4-km NSSL WRF-ARW model also depicts these narrow bands associated with the leeside cold front:


The model was too slow with the leeside cold front, and this is a known model bias due to sharp inversions that exist with shallow arctic fronts.

For more information on leeside cold fronts and their appearance in water vapor imagery see:

Ralph, F.M., P.J. Neiman, and T.L. Keller, 1999:  Deep-Tropospheric Gravity Waves Created by Leeside Cold Fronts. J. Atmos. Sci., 56, 2986-3009.

Posted in Synthetic NSSL WRF-ARW Imagery | Leave a comment

Convective Initiation Application via the Split Window Difference product

One of the exciting new products that will be available on GOES-R is the split window difference (SWD) which is simply the difference between the 10.35 micron and 12.3 micrometer channels.  This channel difference has been shown to provide information about atmospheric column water vapor.  Higher SWD values (larger positive difference) can correspond to deepener low-level moisture in a cloud-free environment.  This signature can be utilized to anticipate where and when convective initiation will occur in cloud-free conditions away from complex terrain (such as the Great Plains).  Although similar bands were available on some previous GOES instruments, their coarse resolution and poor signal-to-noise ratio made them less useful for identifying subtle small-scale features in the low level moisture field.

In order to demonstrate this product (since the 12.3 micron channel is not available on the current GOES imager), we use synthetic imagery from the 4-km NSSL WRF-ARW model.  Here is an example of the SWD on a day with a dryline across Texas:

The larger (positive difference) values of SWD are shown in warm colors, while the location of the cross section (shown below) is illustrated by the east-west oriented black line.  Next, we will look at output from the NSSL WRF-ARW model along the cross section line:

The white line indicates SWD values (scale on the right) while the colors are specific humidity.  SWD values are greatest along the dryline where the depth of the moisture is greatest.  The low-level temperature lapse rate also plays a role in the SWD, but as can be seen in the cross section, the depth of the moisture is the dominating factor.

A loop of the synthetic SWD from the NSSL WRF-ARW:


shows the animation from 1500 – 0000 UTC at hourly intervals from the model.  On the left is the synthetic IR (10.35 micron) band and on the right is the synthetic SWD product (larger SWD values are shown in warmer colors).

The first thing to note is the skies are clear before convective initiation across Texas which is necessary to make use of the product in this way.  The larger SWD values develop along the dryline prior to convective initiation.  Keep in mind this synthetic data is at hourly intervals, but once GOES-R becomes available, the data will be displayed at 5 (or even 1) minute intervals.

We can preview how this data may appear on GOES-R by looking at an example from the MSG (Meteosat Second Generation) SEVERI instrument over Europe.  An event occurred on 6 July 2012 where convection developed along a convergence boundary under clear skies prior to initiation.  Also, this event occurred over flat terrain (Poland) which is important since complex terrain complicates this signature.

Here is the zoomed in visible imagery (over Poland) from the MSG satellite from 0845 – 1500 UTC 6 July 2012:


The key to note is the clear skies prior to convective initiation.

Here is the zoomed in SWD imagery (over Poland) from the MSG satellite over the same time period:


Focus on the clear area (that was shown in the visible image) from the center of the scene southeastward.  SWD values gradually increase (going toward warmer colors) indicating deepening moisture along this convergence boundary, followed by convective initiation (expanding regions of blue/purple later in the loop).

A local maximum in SWD developed over a convergence boundary (under clear skies) about 2 hours prior to convective initiation.  Forecasters can make use of this information when attempting to predict where / when convective initiation will occur.  As looking at this imagery becomes routine with GOES-R for diagnosing convective initiation (under clear skies beforehand), experience with this product will lead to greater forecaster confidence in timing and location of convective initiation.

For more detailed information on this product, see this article:

Lindsey, D.T., Grasso, L., Dostalek, J.F., and J. Kerkmann, 2014: Use of the GOES-R Split-Window Difference to Diagnose Deepening Low-Level Water Vapor. J. Appl. Meteor. Climatol., 53, 2005–2016.  http://dx.doi.org/10.1175/JAMC-D-14-0010.1

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