3D GOES-16/17 Imagery at NWS Huntsville

Yes, you read the title correctly.  We have 3D visible imagery from the GOES-16/17 satellites in the Advanced Weather Interactive Processing System (AWIPS) at the Weather Forecast Office in Huntsville!  So, how did we do this?  I’ll explain.

Several days ago, Kevin McGrath at NASA SPoRT created Facebook and Twitter posts detailing the capability of generating 3D imagery when using both the GOES-16 and GOES-17 satellites in one image.  This is made possible by taking advantage of the slightly different viewing angles by the two satellites in their current GOES East and Center positions.  Yesterday, we explored the possibility of doing this in AWIPS here at the Huntsville WFO and were successful.  I’ll tell you how we did it (which is actually not that difficult), but first I’ll show some 3D imagery from around the Southeast U.S. region this morning.  By the way, to view the imagery in its full 3D glory, you’ll need some standard red/cyan 3D glasses.  Let us also add that the original imagery appears much better in AWIPS as there is always some loss of fidelity when generating images in .gifs and then transferring and viewing these from other platforms.  Anyway, hopefully you’ll get a good sense of the 3D aspects contained within the image loops, and I’ll add it’s better to view with your screen brightness turned up and under darker ambient conditions.


Image 1. GOES-16/17 3D Visible image loop (0.64 µm), 1307-1442 UTC, 14 Sep 2018

Next, we’ll take a closer look at some of these cloud scenes.  First, here’s a look at Hurricane Florence as it churns along the N. Carolina coast.  You may notice (as we did) that it is much easier to observe the differential motion and distinguish among the various cloud layers in this type of imagery.  Unfortunately, some of the image fidelity is lost when saving as a .gif, as observed particularly in the cirrus cloud layer in the image loop.


Image 2. GOES-16/17 3D visible image loop (0.64 µm) of Hurricane Florence, 1317-1452 UTC, 14 Sep 2018

It is rather extraordinary to view developing convection in 3D.  This convective cloud scene in the NW Gulf of Mexico details this capability well (Image 3).


Image 3. GOES-16/17 3D visible image loop (0.64 µm) centered over the NW Gulf of Mexico, 1317-1452 UTC, 14 Sep 2018

This next cloud scene is not as active, however, it is interesting how one can get a sense of the differences in cloud depth between the fog hugging some of the southern Appalachian valleys and the outer cirrus band extending far west of Hurricane Florence.


Image 4. GOES-16/17 3D visible image loop (0.64 µm) centered over the Southern Appalachian region, 1222-1357 UTC, 14 Sep 2018

Lastly, to demonstrate the advantage of this type of imagery, we thought we’d show a simple GOES-16 visible loop (Image 5) compared to a 3D visible loop (Image 6).


Image 5.  GOES-16 Visible image loop (0.64 µm) centered over south TX, 1447-1627 UTC 14 Sep 2018


Image 6.  GOES-16/17 3D visible image loop (0.64 µm) centered over south TX,

Now, you may notice a lack of “brightness” in the 3D imagery, which is due to the layering process.  But, perhaps you can get a better sense of the complex layered cloud scene over southern portions of TX in the 3D loop as we did.  Of course, as stated previously, there’s generally something lost in translation when moving and viewing graphics between various screens and viewing platforms.

So, now to answer the question…how did we do this?  Well, it was somewhat simple actually.  As you can see in the images, the GOES-17 image is layered on top and GOES-16 on the bottom.  Now, it doesn’t actually matter which satellite image is layered on top.  But, whichever one that is, it will need to be set to 50% transparency.  Then, we modified the color map in AWIPS, applying a pure black to red color curve for the GOES-17 reflectivity values, and black to cyan (or equal contributions of blue and green) for GOES-16.  When doing this initially, we used a simple linear stretch to the color map.  However, we realized a more appropriate methodology utilizes the default non-linear ABI VIS gray scale color map.  So, we simply modified that color map by changing all of the blue and green color values to 0.0, saving this as a new color map and applying this to GOES-17 imagery.  Taking the original color map again, we changed all of the red color values to 0.0 for the GOES-16 imagery.  Voila!  When viewing through the standard red (left eye), cyan (right eye) 3D colored glasses, the left and right eye will see the two GOES images from their respective viewing angles and the imagery appears in 3D.

The lingering question may be…so this is cool and all, but what is the application?  As suggested, this type of imagery does offer a more realistic depiction of the atmosphere and helps to differentiate different cloud layers.  Sure, there are some fantastic RGBs now that can aid in this too.  But, this is another tool in the forecaster toolbox, so to speak.  Additionally, I noticed yesterday and today that it is easier to get a sense of shear in tilted convective updrafts, and when speaking with forecasters at the WFO here, it helps provide them a more thorough and realistic conceptual model of the troposphere.  So, these are some things to consider.  We’ll be exploring more use of this imagery over the coming days/weeks.  The are some caveats to all of this.  First, people with significant red/green color deficiencies may not be able to view the 3D imagery as intended.  Second…we don’t know if this will still work once GOES-17 gets shifted to its eventual GOES-West position later this year.  There may be too great of a difference in the viewing angles.  A quick inspection of GOES-15/16 imagery using this same format seemed to indicate an issue there.  We’ll see.  Anyway, for now, this is a fascinating way to view the visible cloud scene.

-Kris White & Kevin McGrath

Geostationary Lightning Mapper detects lightning in the Volcanic Plume from the Fuego Volcano in Guatemala (3 June 2018)

During the eruption of the Fuego Volcano on the afternoon of Sunday June 3, 2018, the Geostationary Lightning Mapper observed a rare, but important, phenomenon: volcanic lightning.  A total of five lightning flashes were observed between 1814 and 1834 UTC with the rising plume.  The first three flashes between 1814 and 1818 UTC were 8 to 10 km north-northeast of the volcano. Then as the plume continued to advect to the northeast of the volcano, the position of the lightning followed. A flash at 1822 UTC was 13 km from the cone of the volcano, and the flash at 1833 UTC was farthest away from the cone of the volcano at 15 km.

Animation of GLM group densities from 1810 to 1835 UTC on 3 June 2018. The location of the volcano is circled.

One of the unique features of GLM is the ability to measure the size of the flash directly as each flash is observed.  In thunderstorms, flash size is a good indicator of vertical motion, which is often hard to directly measure within thunderstorms, or in this case, a volcanic plume.  Between 1814 and 1822 UTC, flashes were occurring approximately every 2 to 4 minutes, and their size was on the order of 500-1000 km2.  Then between 1822 and 1834 UTC there was a lull in GLM-detected lightning activity, followed by the largest flash detected by GLM during the event at 1500 km2 as the plume continued to expand over central Guatemala.

There was a 3 hour lull in GLM-detected activity, until 2141 UTC, when a second set of 21 flashes was detected by GLM between 2141 and 2203 UTC. These flashes were located between 1 and 8 km south-southeast from the highest point of the volcano and correspond in time and reported location of the deadly lahar and pyroclastic flow that came down the south side of the volcano. GLM flash sizes ranged from 64 km2 up to 1500 km2 and there was not as clear of an increase in size as observed with the volcanic plume.

Animation of GLM group densities from 2139 to 2205 UTC on 3 June 2018. The location of the volcano is circled.

Shallow Snow and High Wind Event of 14 February during the PyeongChang2018 Winter Olympics

As the Winter Olympics come to a close this weekend, NASA/SPoRT continues its involvement in the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games (ICE-POP) through the gathering of field campaign observations and numerical weather prediction (NWP) model data.  The ICE-POP campaign extends through March to support the Paralympic Games, and obtain more event data to set the stage for future research activities.  During the first week of the 2018 PyeongChang Winter Olympics, another weather event worth highlighting is the shallow snow and high wind episode that disrupted downhill skiing competition at Jeongseon Hill on 14 February.  On this day, a potent shortwave trough embedded in strong northwesterly flow approached the Korean Peninsula (Fig. 1), which led to a relatively short-lived, but potent snow event accompanied by strong winds in the mountains, occurring mainly between 0000-0600 UTC 14 February.


Figure 1.  Animation of NASA Unified-WRF model 3-hourly 500-mb geopotential height (dam) and wind speed (m/s), valid between 1200 UTC 13 February to 1200 UTC 14 February 2018.

An animation of Himawari 10.4-micron infrared imagery from 1200 UTC 13 Feb to 1200 UTC 14 Feb (Fig. 2) shows enhanced cold cloud tops northwest of the Korean Peninsula associated with the shortwave.  However, between 0000-0600 during the snow event, we see relatively warm cloud top temperatures over the Korean Peninsula, indicative of the shallow nature of the snow.  Himawari visible imagery between ~0000-0800 UTC 14 February (Fig. 3) shows the presence of the low clouds that dissipate rapidly in coverage after 0600 UTC.  Experimental ICE-POP disdrometer measurements of hydrometeor size distribution confirm the timing of the snow event between 0000-0600 UTC (Fig. 4), showing predominantly small diameter hydrometeors (most likely snow).  However, the vertical “spikes” seen in Figure 4 between 0000-0200 UTC indicate some larger diameter snow aggregates associated with the more intense snow activity. Cloud profiling radar data (not shown) confirmed a shallow a nature to the precipitation, generally under 2 km depth.


Figure 2.  Animation of Himawari 10.4 micron infrared imagery between 1200 UTC 13 February and 1200 UTC 14 February 2018.


Figure 3.  Animation of Himawari visible imagery between 0000 and 0800 UTC 14 February.


Figure 4.  Experimental ICE-POP distrometer measurements, showing the concentration and size distribution of hydrometeors as a function of UTC hour on 14 February 2018.

The experimental NASA Unified-Weather Research and Forecasting (NU-WRF) model simulations being provided to South Korea during the Olympics captured this event fairly well.  Simulated composite radar reflectivity on the 1-km nested grid from the 1200 UTC 13 February model initialization (Fig. 5) shows a region of enhanced precipitation occurring between ~0000 to 0600 UTC 14 February, around the time of the observed snowfall.  The experimental NU-WRF run also depicts strong 10-m wind speeds during this time (orange shades exceeding 20 m/s, or ~45+ mph), particularly along the axis of higher terrain in the eastern Korean Peninsula (Fig. 6).  Finally, a time-height cross section of the NU-WRF simulated precipitation microphysics at Jeongseon Hill (Fig. 7) shows the precipitation episode timed between ~0000-0600 UTC 14 February, quite consistent with observational data.  The model also captured the shallow nature of the event, with the most substantial snow and graupel mixing ratios being primarily at or below ~1500 m above ground.

The combination of these experimental observations and NWP model data being collected during the Winter Olympics will serve as a foundation for future research to improve our understanding of snow processes in complex terrain.  Additionally, hydrometeor size distribution data from Fig. 4 along with other observations can help refine NWP model microphysical parameterization schemes to determine the proper distribution of precipitation species produced by the model.


Figure 5. SPoRT/NU-WRF simulated composite radar reflectivity (dBZ) every 30 minutes on the 1-km nested grid centered on the ICE-POP Olympics venues, for the model run initialized at 1200 UTC 13 February 2018. Valid times are from 1200 UTC 13 February to 1200 UTC 14 February.


Figure 6.  Same as in Fig. 5, except for the maximum 30-minute interval 10-meter wind speeds.


Figure  7.  Time-height cross section of SPoRT/NU-WRF model simulated precipitation mixing ratios (g/kg) from the 1-km nested grid, valid between 1200 UTC 13 Feb and 1200 UTC 14 Feb 2018 at the Jeongseon Hill Olympics site for the lowest 2 km above ground.

Lightning’s Reach

Over the weekend of October 22, thunderstorms moved through eastern Texas.  One feature that stood out was the number of flashes that extended well behind the main convective line of storms.  The image below shows where lightning was observed for one minute at 1258 UTC.  The overall Geostationary Lightning Mapper (GLM) event density display shows the lightning activity in a broken line from just west of Austin, Texas eastward towards Lake Charles, Louisiana.  Overall, the lightning remained fairly close to the parent storm.

The image is much more dramatic one minute later at 1259 UTC.  Here, GLM observes lightning extending from Austin, Texas all the way to Bryan and Waco, Texas and continuing northeast of Tyler, Texas.  Just from Bryan to Tyler, Texas this extends approximately 145 miles!



NOTE:  NOAA’s GOES-16 satellite has not been declared operational and its data are preliminary and undergoing testing. Users receiving these data through any dissemination means  (including, but not limited to, PDA and GRB) assume all risk related to their use of GOES-16 data and NOAA disclaims any and all warranties, whether express or implied, including (without limitation) any implied warranties of merchantability or fitness for a particular purpose.


Passive Microwave Views of Three Atlantic Hurricanes This Morning…

Below are 89 GHz RGBs (composited) of the three hurricanes affecting the Atlantic basin this morning.  Notice a decent eye structure is observable in all of the storms, including Hurricane Katia in the SW Gulf of Mexico.  This was noted in the 4 AM CDT discussion about the hurricane from the National Hurricane Center (NHC), “Enhanced BD-curve infrared imagery and a GPM microwave composite image indicate improved banding over the western portion of the circulation and the earlier ragged eye presentation has become much more distinct.”  SPoRT helped with the implementation of the passive microwave data into the AWIPS platform at the NHC several years ago, which has aided forecasters there with the diagnosis and analysis of these systems.

For the latest, best up-to-date information regarding the hurricanes, please refer to the NHC website.


89 GHz RGBs from the GPM constellation of the three hurricanes affecting the Atlantic Basin this morning.  Approximate times for passes over the respective hurricanes are noted in the image.

GLM is coming: The instrument

The first beta-release data of the Geostationary Lightning Mapper (GLM) instrument will be out this week. (Update as of 12 June 2017:  GLM beta release has been delayed until July.)  As we get closer to having real-time GLM observations, here is a quick post about the GLM instrument itself.


Figure 1:  An artist’s image of the GOES-16 satellite with the Geostationary Lightning Mapper (GLM) shown as the zoom out in the upper right.

In the post describing the origin of the GLM (here), it was discussed how the GLM is not the first space-based instrument to observe lightning.  However, it is the first lightning sensor available in geostationary orbit.  Conceptually, the GLM can be thought of as a very large digital camera.  Each pixel of the camera is identifying optical brightness difference from cloud top.  Each pixel is monitoring if any light is observed and if the light observed exceeds a background threshold.  This check is occurring every 2 ms and these observations become the basic GLM “event” observations.  The background field and threshold criteria are designed to reduce false alarms.  The placement of the charge couple device, or CCD pixels, on the instrument designed to help with the instrument’s spatial resolution.  The instrument’s CCD pixels vary in size to help account for the increasing parallax the closer to the edge of the field of view the observations get.  This allows the resolution of the GLM to go from 8 km directly beneath the satellite to only 14 km at the edge of the field of view.

The actual field of view for GLM is shown in Figure 2 for both the GOES-East (eventual location of GOES-16) and -West (future position of GOES-17) positions.  The underlying, normalized annual lightning flash rate comes from observations made by the Optical Transient Detector and Lightning Imaging Sensor from 1995-2005.  Currently, the GLM is in the GOES-16 check-out location (Figure 3).  The total field of view will range from 52 degrees north and south.  Additionally, the GLM does observe total lightning, or the combination of intra-cloud and cloud-to-ground observations.  However, the GLM will not distinguish between the two.  Still, observing total lightning, particularly over such a large domain will aid in warning decision support, lightning safety, as well as situational awareness in data sparse regions.  This will be helpful for detecting flash flooding (noting where is convection) in the inter-mountain west, convection monitoring for aviation, as well as opening up new avenues of research for tropical cyclone forecasting.  Lastly, the GLM was designed to be able to detect 70% of total flashes over the entire field of view over 24 hours.  The false alarm rate was designed to be less than 5%.  Recently, a calibration and validation field campaign had been underway to investigate the GOES-16 instruments.  Early indications are that the GLM will likely exceed the design specifications.  Exact values will be provided later after the field data has been analyzed.


Figure 2:  The field of view for GLM in the GOES-East and -West position.  The normalized, annual lightning flash rate shown is derived from 10 years of Optical Transient Detector and Lightning Imaging Sensor, low-Earth orbiting instrument observations.


Figure 3:  Same as Figure 2, but showing the current GLM field of view through November 2017.

Subsequent posts will start to focus on actual GLM observations once they are made available.

GLM is coming: The origin of the GLM

The Geostationary Lightning Mapper (GLM) successfully launched aboard GOES-R (now GOES-16) on November 19, 2016.  Now we are a week away from the initial preliminary, beta data observations being made available.  This is an exciting time, especially with some of the early public release imager from the GLM available on the GOES-R multimedia page (http://www.goes-r.gov/multimedia/goes-16DataAndImagery.html).  In advance of next week’s milestone here is some of the history that has led to the development of the GLM.

One of the earliest satellite-based instruments specifically designed for lightning observations was the Optical Transient Detector (OTD).  Figure 1 (below) shows the annual flash frequency for 1995 to 2000. This was developed by NASA’s Marshall Space Flight Center in Huntsville, Alabama.  Amazingly, the OTD was built in nine months.  Launched on April 3, 1995 the OTD was placed in a near polar orbit allowing it to monitor lightning over much of the Earth during both the day and night.  However, the OTD only provides a few minutes a day for any given location.  This prevented the OTD from studying local weather activities, but allowed the OTD to study global lightning patterns and their evolution.  The OTD also launched at a time when the awareness of the important role lightning played in the Earth’s atmosphere was becoming better understood and that lightning was likely an indicator of the strength of convective storms.  OTD efforts would contribute to the discovery of lightning as an indicator of potential severe weather, what we now call lightning jumps.  Additionally, OTD discovered that the global flash rate is approximately 40 flashes per second.  Ultimately, the OTD’s contributions reinforced the need for lightning observations from geosynchronous orbit, which would ultimately lead to the development and launch of the GLM.


Figure 1:  Annual flash frequency from 1995 to 2000 from Christian et al. (2003).

Given its short production time, the OTD served as a production prototype for a more robust, low-Earth orbiting lightning sensor.  This new instrument was the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measuring Mission (TRMM).  The LIS was designed by scientists at the University of Alabama in Huntsville as well as NASA’s Marshall Space Flight Center.  Launched in 1997, LIS, and the TRMM satellite as a whole, far exceeded their projected service life and provided 17 years of continuous observations.  Unlike the OTD, the LIS was on an orbit that focused on the tropical regions of Earth.  However, LIS had superior detection abilities for both day and night.  Figure 2 (below) shows the lightning activity in the LIS field of view for 2012.  Once operational, the LIS has provided significant contributions to investigating convective and precipitation processes.  The long operational life of LIS has also helped identify most lightning active regions on Earth, such as Lake Maracaibo, Venezuela with 232 flashes per square kilometer per year!  Like the OTD, LIS reinforced the importance of a geostationary platform where storm morphology can be monitored continuously.  Many concepts in the design of the LIS have been used in the GLM instrument.


Figure 2:  Lightning Imaging Sensor observations of lightning across the instrument’s field of view for 2012.  Image courtesy of NASA’s Marshall Space Flight Center.

Stay tuned for the next “GLM is coming” blog post that will focus on the efforts to prepare for the Geostationary Lightning Mapper.