Viewing an Eyewall Replacement Cycle and the Structural Evolution of Hurricane Dorian using NASA’s GPM Constellation

Viewing an Eyewall Replacement Cycle and the Structural Evolution of Hurricane Dorian using NASA’s GPM Constellation

Written by Erika Duran and Emily Berndt

In our previous blog post, we highlighted the value of using Red-Green-Blue (RGB) composite imagery from the NASA Global Precipitation Measurement (GPM) constellation to analyze the evolution of storm structure in Hurricane Dorian. Several structural changes were visible in the 37 GHz and 89 GHz passive microwave RGB imagery from September 1-3, 2019, as Dorian approached and made landfall in the Bahamas, and then remained nearly stationary over Grand Bahama Island for nearly two days.

Figure 1: Animation of the GPM Constellation 37 GHz Passive Microwave RGB from 06:48 UTC on September 1, 2019 to 06:33 UTC on September 3, 2019.

The above animation of the 37 GHz passive microwave RGB demonstrates an eyewall replacement cycle that occurred from September 1-2, as well as the erosion of the western eyewall from September 2-3. A secondary eyewall is visible at 20:46 UTC on September 1 (below, Fig 2c), followed by a wider, single eyewall and a much wider eye at 10:36 UTC on September 2 (Fig 2d), as compare to the previous day (Fig 2a). The erosion of the western eyewall is visible in Fig 2f, likely a result from the storm’s interaction with land.

Figure 2. Snapshots of the GPM Constellation 37 GHz Passive Microwave RGB on September 1, 2019 at a) 06:48 UTC, b) 16:36 UTC, and 20:46 UTC, on September 2, 2019 at d) 10:36 UTC and e) 17:18 UTC, and on September 3, 2019 at f) 06:33 UTC.

An animation of the 89 GHz Passive Microwave RGB (Fig 3) provides a slightly different perspective of these same events, highlighting changes in Dorian’s deep convection.

Figure 3. As in Fig 1, but for the GPM Constellation 89 GHz Passive Microwave RGB.

While the eyewall replacement cycle is much more clear in the 37 GHz RGB imagery, structural changes associated with this cycle are still evident using the 89 GHz RGB, showing the presence of a “moat,” or a region of low-echo reflectivity and subsidence between the primary and secondary eyewalls (e.g., Sitkowski et al. 2011, Kuo et al. 2009). The moat is seen as the darker red colors surrounding the eye in Fig 4c, which is located between the primary and secondary eyewalls indicated in the 37 GHz imagery. Additionally, the erosion of the western eyewall is much more clear using the 89 GHz RGB, showing the asymmetry in Dorian’s deep convection on the left side of the eye (Fig 4f).

Figure 4. As in Figure 2, but for the GPM Constellation 89 GHz Passive Microwave RGB.

References

Sitkowski, M., J.P. Kossin, and C.M. Rozoff, 2011: Intensity and Structure Changes during Hurricane Eyewall Replacement Cycles.Mon. Wea. Rev.,139, 3829–3847,https://doi.org/10.1175/MWR-D-11-00034.1

Kuo, H., C. Chang, Y. Yang, and H. Jiang, 2009: Western North Pacific Typhoons with Concentric Eyewalls.Mon. Wea. Rev.,137, 3758–3770,https://doi.org/10.1175/2009MWR2850.1

The Evolution of Hurricane Dorian as Viewed from NASA’s GPM Constellation

The Evolution of Hurricane Dorian as Viewed from NASA’s GPM Constellation

Written by Erika Duran, Emily Berndt, and Patrick Duran

As of Friday morning on August 30, 2019, Hurricane Dorian is forecast to steadily intensify to a major hurricane as it moves northwestward toward the Bahamas over the Labor Day weekend. Many factors can act together to contribute to storm intensification, and satellite imagery offers a variety of perspectives to monitor the evolution of tropical cyclone (e.g., hurricane) structure as a storm undergoes intensity change. Multispectral Red-Green-Blue (RGB) composite imagery derived from the Global Precipitation Measurement Constellation of passive microwave sensors provides value in monitoring the evolution of convection within a tropical cyclone, and can reveal structures such as developing and concentric eyewalls, as well as spiral rainbands.

Figure 1 shows the evolution of Dorian from Wednesday, Aug 28, 2019 through Thursday, August 29, 2019 as viewed from the 37 GHz RGB, which is sensitive to warm precipitation (i.e., rain; Lee et al. 2002). Light blue colors demonstrate regions of lighter rain, indicative of mainly stratiform precipitation, and pink to red colors demonstrate areas of heavier rainfall, indicative of convective precipitation. As Dorian moves through the eastern Caribbean, it consistently demonstrates spiral rainband structure, as well as the presence of an eye as it moves north of Puerto Rico (Fig 1b,c). Such features suggest a maturing tropical cyclone, and indicate environmental conditions that are favorable for development. Notice that the wide eye present at 10:56 UTC on August 29, 2019 (Fig 1c) appears to erode on the southern edge by 16:06 UTC on August 29, 2019 (Fig 1d), and most of the precipitation is found north and east of the center of Dorian; this asymmetry in precipitation suggests a negative influence on storm intensification, such as the presence of wind shear, or dryer air being ingested into the storm from the south.

Figure 1: 37 GPM Constellation 37 GHz Passive Microwave RGB on Wednesday, August 28 at a) 05:33 UTC and b) 2106 UTC, and on Thursday, August 29 at c) 1056 UTC and d) 1606 UTC.

Fig 2 illustrates the same snapshots of Dorian on August 28th and 29th, but using the 89 GHZ RGB imagery, which is sensitive to frozen precipitation (i.e., ice; Lee et al. 2002). Red colors indicate regions of strong convection. Similar features such as rainbands and an eye/eyewall are also visible at this frequency, but this RGB demonstrates some structural differences; for example, the 89 GHz RGB indicates the presence of an eye and a symmetric eyewall at 21:06 UTC on August 28th (Fig 2b), while the 37 GHz RGB demonstrates an asymmetric eyewall (Fig 1b). Comparing features from these two RGBs can help to highlight differences in the storm structure at different levels of the atmosphere, since the 89 GHz RGB is more sensitive to cloud microphysical characteristics found at higher altitudes of the storm.

Figure 2: As in Figure 1, but for the GPM Constellation 89 GHz Passive Microwave RGB.

Figure 3 demonstrates the satellite-derived instantaneous rain rate (in/hr) for the same snapshots described for the RGBs above. These images provide another perspective on storm structure by demonstrating where precipitation is occurring. Similar spiral rainbands are visible in these images as well, and Fig 3c shows a well-defined eye and eyewall structure as Dorian moves northwest of Puerto Rico. As in Fig 1d and 2d, notice how at 16:06 UTC on Aug 29, most of the precipitation is occurring north and east of the center of Dorian (Fig 2d.)

Figure 3: As in Figures 1 and 2, but for the satellite-derived instantaneous rain rate (in/hr).

Comparing the RGBs and rain rate with GOES-East water vapor imagery can help diagnose the environment surrounding Dorian at this time. The black and orange colors in Fig 4a and 4b and the red to orange colors in Fig 4c and 4d illustrate the presence of dry air south of Dorian, which appears to have penetrated into the core of the storm. This drier air likely contributed to the degradation of the eye and eyewall structure visible in Figs 1d, 2d, and 3d, and helped to create the asymmetry in precipitation.

Figure 4: GOES East imagery of Hurricane Dorian on Thursday, Aug 29 for the mid-level water vapor infrared band (Channel 9) at a) 1050 UTC and b) 1610 UTC and the low-level water vapor infrared band (Channel 10) at c) 1050 UTC and d) 1610 UTC.

Fig. 5 shows an animation of the GPM Constellation 89GHz passive microwave RGB at 23:06 UTC on August 29 and 08:32 UTC and 11:17 UTC on August 30th. Notice how Dorian appears to organize as it moves northwestward, exhibiting more spiral rainband structures and an eye in the center of the storm, accompanied by deep convection (red colors).

Figure 5: An animation of the GPM Constellation 89GHz passive microwave RGB on (1) August 29, 2019 at 23:06 UTC, (2) 08:32 UTC and (3) 11:17 UTC on August 30, 2019.

As GPM Early Adopters since 2014, the NASA SPoRT center has a history of providing RGB imagery to national centers, including the National Hurricane Center (NHC) for use in operations. Today, the imagery is extensively used in hurricane analysis and forecasting, leveraging the ability to detect features of interest and to identify the hurricane center, structure, and intensity. Real-time products are also available on the SPoRT website. More information on GPM products and applications can be found in the NASA GPM Overview, which is a SPoRT contribution to the National Weather Service’s Satellite Foundational course for JPSS. These examples demonstrate how using a combination of satellite products can be helpful in diagnosing different structural features of tropical cyclones.

References

Lee, T. F., F. J. Turk, J. Hawkins, and K. Richardson, 2002: Interpretation of TRMM TMI images of tropical cyclones. Earth Interactions, 6, 1-17, doi:10.1175/1087-3562(2002)006<0001:IOTTIO>2.0.CO;2.

SPoRT LIS Shows Dry Soils During High Plains Blowing Dust Event…

Yesterday while working on some Dust RGB related training materials, I was looking at the RGB in AWIPS and noticed a dust event unfolding in real-time in the central High Plains.  The loop below shows Dust RGB imagery, generated by GOES-East, yesterday, 28 Jan 2019 during the late morning and early afternoon hours.  The loop is centered over NE Colorado and SW Nebraska where you’ll see the blowing dust develop and spread southeastward.  In case you’re not too familiar with this type of imagery, the dust is represented by the magenta colors.  It’s also possible to observe some of the individual dust streaks or plumes within the larger blowing dust event, which help to show their locations of origin.  (By the way, sorry about the loss of image fidelity when saving from AWIPS to an animated GIF).

Image 1.  GOES-East Dust RGB imagery, approx. 1737-2002 UTC, 28 Jan 2019. The blowing dust is defined by the magenta colors, near the center of the imagery.

Research has shown that it takes the right combination of factors to loft dust particles sufficiently to generate these larger scale blowing dust events, partly based on soil moisture and winds.  The SPoRT LIS 0-10 cm volumetric soil moisture (VSM) analysis at 18 UTC indicated very low values in the blowing dust source region, with VSM percentages generally around 12-16% (Image 2).  The METAR observations also indicate sustained winds were 35-40 knots with stronger gusts over 40 knots at one locations in the area.

Image 2. SPoRT LIS volumetric soil moisture (background colors) overlaid with surface METAR plots (yellow figures), valid at 18 UTC, 28 Jan 2019.

This last image is a snapshot of the Dust RGB taken at 1902 UTC, overlaid with surface visibility and ceiling observations.  Notice that at station KHEQ in far northeastern Colorado, a ceiling of 100 ft and visibility of 7 SM was reported, which was likely due to the blowing dust.

Image 3. GOES-East Dust RGB and ceiling and visibility observations from ground observation stations at approximately 19 UTC, 28 Jan 2019.

Some SPoRT collaborative NWS offices in the West CONUS have utilized LIS VSM values to locate areas where the probability of blowing dust events is heightened under the proper conditions.  However, SPoRT is looking into opportunities to better predict where these events will occur.

SPoRT LIS Shows Low Soil Moisture Conditions Near Large N. Cal Fire…

Just making a quick post here as I noticed there were relatively dry soil moisture conditions at the site of a rather large fire that developed quickly in Butte County, CA today.  The first image is the Fire Temperature RGB from the GOES-16 satellite (mesoscale domain sector 1) at 2018 UTC, today, 8 Nov 2018.  In this RGB, the fire can be observed by  colors ranging from near red to near white, just east of Chico, CA.  Notice there are a few white pixels, indicating relatively high emissions from shorter wavelengths (1.61 µm), and thus, relatively hot fire temperatures.

FireTempRGB_2018Z8Nov2018

Meanwhile, soil moisture data from SPoRT’s Land Information System show low soil moisture percentiles (from the 33-year climatology, next image below) at the fire’s location east of Chico.  In fact, these values are  below the 2nd percentile at the fire’s location.

SoilMoisturePercentile_12Z8Nov2018

Lastly, the one year change in deep layer soil moisture values (0-200 cm) also show significant decreases in soil moisture centered at the fire’s location and especially just east over the last year.

OneYearChange_12Z8Nov2018

SPoRT is conducting research and working closely with members of the wildfire community in the western U.S. to transfer these and other data sets for operational decision-makers.

-Kris W.

Fog at Sunrise with RGBs using Visible Imagery

Fog at Sunrise with RGBs using Visible Imagery

NtMicro_southeast-20180813_112228

Nighttime Microphysics RGB via GOES-16 at 1122 UTC, 13 August 2018 over the Southeast U.S.

During the early morning of 13 August 2018, clear skies resulted in wide spread low clouds and fog over the East/Southeast.  The image above is the Nighttime Microphysics (NtMicro) RGB via GOES-16 at 1122 UTC or 7:22 and 6:22 AM for Eastern and Central times respectively.  At this time the low clouds and fog in shades of cyan are still apparent, but soon this coloring will fade as solar reflectance at sunrise will influence the shortwave IR used in the RGB and therefore, the NtMicro will be rendered ineffective (see mp4 animation).  Typically, visible imagery is used at sunrise to continue to monitor fog in small-scale valleys, often with a lack of in situ observations.  The new capabilities of GOES-16 provide new RGBs for daytime use that include the 0.64 micron visible channel.  The Natural Color RGB, originally developed by EUMETSAT is available within AWIPS (as ‘Day Land Cloud’), and it uses the visible channel in it’s blue component.  Below is a slide show of the NtMicro, Natural Color and Visible RGBs just after sunrise (1222 UTC).  Note that the Natural Color RGB (also see mp4 animation) shows the fog and water clouds in gray while ice clouds are in cyan.  The Natural Color RGB can be used through the day to monitor the microphysics of cloud tops due to the use of the 1.61 micron channel, and it also provides qualitative land surface information via the 0.87 micron channel.   A legacy ‘Visible’ RGB (also see mp4 animation) that uses the visible in the red and green components (‘Day Land Convection’ within AWIPS), also provides value to monitor fog after sunrise as it depicts warm clouds in yellows and cold clouds in grays to white in daytime.

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Dust RGB Imagery and NASA’s CALIPSO/CALIOP

Dust RGB Imagery and NASA’s CALIPSO/CALIOP

anigif850x484_DustRGB_Southwest_20180412_1732_2122

Dust RGB via GOES-16 from 1732-2232 UTC on 12 April 2018 over the U.S. Southwest

SPoRT used the MODIS and VIIRS imagers (on NASA’s Aqua & Terra satellites, and NOAA’s S-NPP satellite, respectively) within the NOAA’s Satellite Proving Ground to assess the value of a “Dust RGB Imagery” product for potential use with GOES-R (now GOES-16).  The Dust RGB proved useful on 13 April 2018 (animation above) where many dust plumes developed in the U.S. Southwest and Mexico.  Forecasters were able to monitor dust plume initiation and issue advisories and warnings.  In addition, several plumes continued to have impacts after sunset, and the Dust RGB, which uses only IR window channels (see Dust RGB Quick Guide), was able to continue monitoring the event at night while the visible imagery was no longer valuable.  Some advisories were extended beyond their original expiration time.  NASA SPoRT is using the NASA CALIPSO satellite and associated CALIOP lidar on board to validate and categorize dust signatures seen in the RGB and examine quantitative aspects like plume height and thickness.  The image below shows an event from 3 April 2018 where forecasters from the NWS Albuquerque WFO and CWSU evaluated the Dust RGB impact to operations as part of SPoRT’s assessment activities, and the CALIOP lidar backscatter captured the dust plume over west Texas.  From CALIOP the dust plume appears to be about 2 km thick in most locations, but the most concentrated region reached a height of about 3 km above ground.

DustRGB_CALIOPbackscat_20180403

Dust RGB via GOES-16 (upper) over the CONUS and lidar backscatter via CALIOP (on NASA’s CALIPSO satellite) for 2007 UTC on 3 April 2018.  Annotations in yellow point out the dust plume and clouds along the path of CALIOP shown by white arrow/text.

Dust RGB analyzes “dryline” for 3/23/17

Dust RGB analyzes “dryline” for 3/23/17

 

The Dust RGB, originally from EUMETSAT and a capability of GOES-R/ABI, can be helpful in identifying features other than dust, including drylines. A dryline represents a sharp boundary at the surface between a dry air mass and moist air mass where there is a sudden change in dew point temperatures. In this event from 3/23/17, a dryline in eastern New Mexico and west Texas is distinguishable via the Dust RGB imagery animation from GOES-16 (Fig. 1), while a large dust plume (magenta) is impacting areas further west. Note that the visible imagery (Fig. 2) shows clouds forming along the dryline, but these clouds drift downwind toward the northeast as they mature, away from the dryline itself, making it difficult to monitor the dryline position.  However, the dryline position can easily be seen via the color difference of the Dust RGB across the boundary of dry and moist air, and in fact, the dryline appears fairly stationary or moves in a slight westward direction, opposite of the cloud motion.  In situ observations (Fig. 3) are a primary tool for monitoring the dryline location, but the advantage of satellite imagery is an increased spatial and temporal resolution for forecasters.

Dust_SENM_2022to2322_loop

Figure 1. GOES-16 Dust RGB valid from 2022 to 2322 UTC, on 23 March 2017 centered on extreme western Texas.  Dryline seen in color difference of cloud-free area in eastern New Mexico and west Texas while dust plume is in magenta shades.

Vis064_SENM_2027to2322_loop

Figure 2. GOES-16 Visible (0.64u) channel valid from 2027 to 2322 UTC on 23 March 2017 as in Figure 1.

For the above and subsequent images/animations: 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.

UCAR_RAP_METAR2143Z

Figure 3. METAR station plot of surface observations at 2143 UTC on 23 March 2017 centered over New Mexico.

The ability to identify drylines using the Dust RGB gives the forecaster the capability to analyze these boundaries in ways not seen before. In the Dust RGB (Fig. 4), the surface area on the dry side is seen as a purple color (i.e. increased red contribution), and the moist side appears more blue (i.e. less red). This dryline can be noted more easily than in visible imagery (Fig. 5) due to the sensitivity of the 12.3 micron channel used in the 12.3 – 10.35 micron difference within the Dust RGB red component.  The 12.3 micron channel goes from warmer to cooler brightness temperatures with changes in density from very dry to very moist air. The blue contribution is consistent on each side of the line because the surface temperature, and hence the 10.35 micron channel, does not change much from either side of the dryline. There is limited ability to identify drylines using high resolution visible imagery, as seen in the Midland WFO Graphicast (Fig. 6) where cumulus clouds are documented forming along the dryline. Unfortunately, visible imagery is only useable during daylight hours and a user is dependent on cloud features along the dryline in order to analyze its position. However, aside from the obvious value of the color difference in cloud free areas to depict the dryline, the Dust RGB, is viable both during daytime and nighttime hours.

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