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.

Passive Microwave Views of Hurricane Florence…

As Hurricane Florence has developed and flourished in the warm waters of the central and western North Atlantic, the NHC has been using data from microwave sensors aboard polar-orbiting satellites to obtain information about important physical characteristics of the hurricane not otherwise observed by conventional imagery from geostationary satellites.  Not only does the microwave data provide important information about the location, intensity and extent of precipitation bands and deep convection within the hurricane, but can also provide better fixes for the storm center location.  The first image below (Image 1) shows a GOES-16 visible image (~0.64 µm) at approximately 1812 UTC 12 Sep 2018.

Image 1.  GOES-16 Visible Image (~0.64 µm), 1812 UTC 12 Sep 2018

The visible image can be used to ascertain information about some physical characteristics of the hurricane, but the broad canopy of cirrus over much of the hurricane can obscure important, relevant features about banding structures, in particular.  Image 2 shows microwave data (~89 GHz) derived from the AMSR2 sensor at about the same time as the visible image (in Image 1).  Notice that much of the intense banding observed in the microwave data was concentrated along the W to N portions of the hurricane at this time, which might not have been immediately obvious based on the visible imagery alone.  In fact, notice the fairly thin band of convection along the SE side of the eyewall at 1812 UTC.

Image 2. 89 GHz (Horizontal) image from AMSR2, 1812 UTC 12 Sep 2018

Even an inspection of color-enhanced LW IR data/imagery (~10.34 µm) might have suggested a fairly even distribution of deep convection around the eyewall at this time (Image 3).

Image 3.  GOES-16 LW IR image (~10.34 µm), 1812 UTC 12 Sep 2018

However, the 10.34 um will observe cold cirrus cloud tops where present, which may have resulted from earlier convection, and ice crystals that have since been distributed more evenly around the upper-level outflow and not necessarily from recent convection.

Lastly, I thought I’d finish quickly with a loop of the available polar-orbiting passive microwave imagery over Hurricane Florence since early yesterday.  The background color that appears mostly static through the loop is the sea surface temperature data derived from the VIIRS instrument, which is produced by NASA SPoRT and sent to collaborative NWS offices through AWIPS.  Notice the abundance of orange/red colors in the basin through which the hurricane is moving, which is indicative of water temperatures in the mid 80s F (scale not shown).

Image 4. Available polar microwave imagery/data passes over Hurricane Florence since early Sep 11th, background data is sea-surface temperatures derived from the VIIRS instrument

High Winds Impacting Olympic Events Captured by NASA/SPoRT Model and Satellite Products

High Winds Impacting Olympic Events Captured by NASA/SPoRT Model and Satellite Products

As summarized in a previous blog post, NASA/SPoRT is providing one of many numerical weather prediction (NWP) model solutions to South Korea during the 2018 PyeongChang Winter Olympic and Paralympic Games during February and March.  The field campaign is known as the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games (ICE-POP). In combination with the suite of radar, satellite, and in situ observations during the field campaign, the SPoRT configuration of the NASA Unified-Weather Research and Forecasting (NU-WRF) will serve as a benchmark for future research to improve our understanding of snowfall in complex terrain, our ability to estimate snow using satellites, and for improving prediction models that parameterize these intricate processes.

A key component of the Olympics field campaign is to improve forecast models through comparison to observations and satellite retrieval products.  The constellation of passive microwave imagers being assembled in support of the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement mission (IMERG) precipitation dataset also provide information on near-surface meteorology necessary to estimate the surface turbulent fluxes. Algorithms designed to retrieve surface temperature, humidity, and wind speed are used together with bulk-flux algorithms to estimate the latent and sensible heat fluxes over the ocean surface. These fluxes are a source of energy and moisture for the overlying atmosphere.  One of the research goals of ICE-POP is to improve heat and moisture fluxes in prediction models through assimilation of these retrieval products.

During this past weekend, the Men’s Downhill Alpine was postponed until Thursday, and the Women’s Giant Slalom Qualifiers were canceled due to high winds that impacted Jeongseon Hill.  Figure 1 shows a 24-hour animation of NU-WRF simulated maximum 10-m wind speeds in 30-minute intervals on 11 February, on the 1-km nested grid centered on the Olympic venues.  We can see a substantial maximum in wind speed impacting the mountains along the eastern Korean Peninsula as well as offshore in the Sea of Japan.  Simulated wind speeds reached 15-20+ m s-1 (~35-45 mph) in the vicinity of Jeongseon and other mountain Olympic locations.  Wind speed observations at nearby Daegwallyeong (north-east of Jeongseon; not shown) peaked around 13 m s-1 (~30 mph) on 11 February, but speeds were most likely stronger in the higher terrain around Jeongseon.  In this particular situation, the higher resolution of the 1-km grid was critical to resolve the fine-scale variations in wind speeds within the complex terrain.

Figure1_maxwind10md03_2018021100_anim

Figure 1.  Twenty-four hour animation of NU-WRF simulated 10-m maximum wind speeds in 30-minute increments, valid from 0000 UTC 11 February through 0000 UTC 12 February 2018.

Meanwhile, the 10-m wind speeds, sensible, and latent heat fluxes are shown in Figure 2, comparing the 9-km model grid simulation with the satellite flux retrievals produced by NASA/SPoRT.  In Figure 2, the retrievals are hourly-averaged composites produced for the ICE-POP campaign, derived from swaths of the constellation of passive microwave satellites.  As the bitter cold Siberian air mass flows over the warmer open waters of the Sea of Japan, Yellow Sea, and western Pacific Ocean, substantial heat and moisture fluxes are directed from the sea surface to the atmosphere.

The 10-m model and retrieved wind speeds both depict a similar broad pattern of high wind speeds up to and exceeding 15 m s-1 across favored corridors downwind of the Korean Peninsula, China, and Russia (Figs. 2a and b).  The model sensible heat flux on the 9-km grid valid at 0600 UTC 12 February (panel c) has a broad pattern similar to the retrieval composite (panel d), but with an axis exceeding 500 W m-2 from the east coast of the Korean Peninsula to central Japan, and a broader amplitude between ~200-400 W m-2, generally higher than the retrievals values  The model latent heat flux (panel e) shows a similar pattern, except for a larger coverage of values exceeding 500 W m-2 between the Korean Peninsula and Japan, and offshore of central and southern Japan.  The maxima offshore of Japan show good agreement between the model and retrieval patterns (panels e and f).

The NU-WRF flux amplitudes are generally higher than that of the retrieval, likely due to several factors such as the retrieval being an hourly-averaged composite compared to instantaneous model fluxes, differences in product resolution, input sea surface temperatures, and model errors in simulated wind speed, and near-surface temperatures and moisture.  Following the Olympics, additional research as part of ICE-POP will involve examining the viability and benefits of assimilating the surface meteorology retrievals into the model for improving the predictions of oceanic heat and moisture transports into the atmosphere and their attendant impacts on air-mass modification.

Figure2_fluxComparison_match

Figure 2. Comparison between NU-WRF 6-h forecast and passive-microwave hourly-averaged composite retrievals of 10-m wind speed (m s-1), sensible, and latent heat flux (W m-2) valid 0600 UTC 11 February 2018. (a) NU-WRF 10-m wind speed, (b) 10-m wind speed retrieval, (c) NU-WRF sensible heat flux, (d) sensible heat flux retrieval, (e) NU-WRF latent heat flux, and (f) latent heat flux retrieval.

Passive Microwave Observations of Category 5 Hurricane Irma…

The NASA SPoRT program has been providing Passive Microwave data to the National Hurricane Center for use in the NWS Automated Weather Interactive Processing System (AWIPS), which allows for data-layering capabilities, and has helped improve the method for tracking center fixes on tropical systems.  These data have been provided to the NHC as part of an on-going collaborative effort for several years now.  These first two images are 89 GHz RGBs taken over Cat-5 Irma from this morning.  Importantly, these data/imagery help forecasters to better analyze the internal hydrometeorological structure of tropical systems over other traditional satellite imagery.

Image 1.  89 GHz image over Cat-5 Hurricane Irma from approx 0548 UTC 7 Sep 2017.  Background imagery is SPoRT SSTs from approx 18 UTC 6 Sep 2017.

 

Image 2.  89 GHz image over Cat-5 Hurricane Irma from approx 1112 UTC 7 Sep 2017.  Background image is SPoRT SSTs from approx 18 UTC 6 Sep 2017.

Sea surface temperatures to the west of the system, and ultimately where it will be tracking are on the order of about 85-87 degrees F, according to the SPoRT data.  The warmest waters are found generally in the SW portions of the Bahamas.

Lastly, here are the 89 GHz Horizontal and Vertical data/imagery for each of these times, that comprise the RGB.

Image 3. 89 GHz Horizontal image over Cat-5 Hurricane Irma from approx 0548 UTC  (left) and 1112 UTC (right) 7 Sep 2017.

Image 4. 89 GHz Vertical image over Cat-5 Hurricane Irma from approx 0548 UTC (left) and 1112 UTC (right) 7 Sep 2017.

 

Precip Estimates Offshore Using NASA IMERG

If you are near the Gulf Coast, you’ve probably gotten a little drenched over the last few days. In fact, there have been reports of floods and flash floods as a result of the days of heavy rain developing off the coast and moving inland. This season, SPoRT is assessing a new suite of precipitation products derived from NASA’s GPM mission: GPM passive microwave swath rain rates and IMERG, a morphed rain rate product that is available every 30 minutes and also in accumulations. For those of you who aren’t readily familiar with passive microwave rain rate products, here is a quick key point. Passive microwave really shines where our WSR-88ds are totally in the dark, namely over the oceans. Here are some screen captures of the new precip products on AWIPS.

The accumulated IMERG products are helpful to determine how much rain has fallen in radar- and gauge-void regions. According the IMERG 24-hr accumulation estimates (lower right panel), greater than 4 inches of rain had fallen in the 24hr period ending in August 9 at 12Z just south of Tallahassee along the coast and another 3+ inches had fallen south of Melbourne. Just off the coast, there were pockets of 8 and even 12 inches of total rain fall in 24 hours, according to IMERG.

IMERGRR09Aug16_1200Z

For Aug. 9 at 12Z, IMERG instantaneous rain rates are shown in the upper left, IR in the upper right, IMERG 3-hr accumulation in the lower left, and IMERG 24-hr accumulation in the lower right.

The instantaneous rain rate product, shown in the upper left in the above image, can be compared to IR or other imagery or observations to help highlight areas with the heaviest rain fall. Passive microwave is especially sensitive to precipitation-sized ice, so it points out the locations of strong convective updrafts within the larger system, whereas IR is sensitive to the cloud tops and can miss some important components of storm development that lead to heavy rain. Note on the animation below that although the rain rates corresponde well the IR imagery, as it should, the locations of heaviest rain are not always the locations with the coldest cloud top temperatures.

IR_IMERG_animation

Aug. 9 at 14Z, IMERG rain rates are toggled over IR.  Note that the coldest cloud tops don’t always coincide with the heaviest rain rates estimated by IMERG.

 

 

 

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.

ABQ_160203_0052Z_annotated_zoom

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

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

ABQ_160203_0330Z_annotated

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

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