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.

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

Winter Storm Jonas tracked across the eastern United States this past weekend dropping near-record amounts of snowfall in a track from West Virginia through southern New York.  Two things about this storm are particularly interesting:  1) the heavy amounts of snow that fell for long periods of time and 2) the relatively narrow swath of the heaviest snows.  Below is the 48-hour snow accumulations from the National Weather Service ending Sunday, January 24.  It is striking that New York City received on the order of 30 inches of snow, while areas less than 100 miles to the north received little if any snow.

NWS_SnowTotals

48-hour snowfall totals ending Sunday, January 24, 2016 (from NWS Central Region).  Contours are every 3″ with the darkest reds indicating 30″ of snow.

Select Eastern Region WFOs are currently evaluating the NESDIS Snowfall Rate product, which uses passive microwave observations from 5 sensors, to observe total column snowfall rates.  Below is a series of images from this past weekend showing the SFR product displayed as a 10:1 solid/liquid conversion.  The darkest greens indicate snowfall rates at the top of the sensor detection range at approximately 2″/hr.  Depending on the actual solid/liquid ratio in individual areas, rates may have been higher.

SFR_Collage_first4

SFR_Collage_second4

NESDIS SFR Product showing the evolution of Winter Storm Jonas from late on Friday through early Sunday.  The darkest greens indicate solid snowfall rates of around 2″/hr.

In the images, the NESDIS SFR product shows very good agreement with the location and track of the heaviest snows (greens) compared to the heaviest totals in the ground reports.  Additionally, the SFR product does well in picking up the abrupt northern edge of the snowfall (especially across southern New York).

UPDATE:  The Sterling, VA WFO included mention of the SFR product in a forecast discussion to confirm snowfall rates that would cause white out conditions:

Sterling_AFD

From drought to flooding in less than a week over the Carolinas, as depicted by SPoRT-LIS

A closed upper low over the Southeastern U.S. combined with a deep tropical moisture connection with Hurricane Joaquin led to historic rainfall and flooding over North and especially South Carolina over the weekend.  A wide swath of central South Carolina from the coast to Columbia received over 20 inches of rainfall in the past week (Fig. 1), much of it in the last 2-3 days.  Figure 2 shows the NASA Integrated Multi-satellitE Retrievals for GPM (IMERG) 24-h rainfall estimates displayed in AWIPS II compared to the official NWS/River Forecast Center rainfall estimate for the period ending 1200 UTC on 4 October.  This is erasing the prevailing drought in the Carolinas, which still had moderate to severe drought in the most recent U.S. Drought Monitor weekly product valid 29 September (Fig. 3).

SPoRT’s real-time configuration of the NASA Land Information System (SPoRT-LIS) runs the Noah land surface model to generate a “best modeled” soil moisture estimate at ~3-km resolution for enhanced situational awareness and input to local/regional numerical weather prediction models.  The SPoRT-LIS was assessed during summer/fall 2014 by the NOAA/NWS weather forecast offices (WFOs) at Houston, TX, Raleigh, NC, and Huntsville, AL. Following an expansion to a full Continental U.S. domain, the SPoRT-LIS was also evaluated more informally by the NWS WFOs at Tucson, AZ and Albuquerque, NM this past summer.  The primary areas of utility has been in drought monitoring and assessing areal and river flooding potential.  However, the Southwestern U.S. offices applied SPoRT-LIS soil moisture fields to enhance situational awareness for wildfire and blowing dust situations as well. Overall, a majority of the users during these assessments expressed substantial utility of the product due to a lack of other real-time high-resolution soil moisture products, and were confident enough to use the product as part of operational, public forecasts.

This extreme rainfall event in the Carolinas was captured nicely by the real-time SPoRT-LIS, which depicted some of the most dramatic changes in total column soil moisture ever documented by SPoRT collaborators.  Figure 4 compares the SPoRT-LIS 0-2 m total column relative soil moisture (RSM) from 28 September (left panel) and 5 October (right panel), with Figure 5 highlighting the 1-week change in 0-2 m RSM as displayed in AWIPS II.  The RSM represents how the volumetric soil moisture scales between wilting (0%) and saturation (100%) for a given soil composition, where the wilting point indicates that vegetation can no longer extract moisture from the soil and saturation indicates no more infiltration is possible (thus all new precipitation goes to runoff). Previous experience by the Huntsville WFO found that total column RSM values of ~60% and above tend to indicate an enhanced threat for areal and river flooding over northern Alabama; however, these thresholds can vary depending on river basin properties and regional soil composition.

Values of total column RSM typically ranged from ~25-35% on 28 September, prior to the significant rain event.  However, by 5 October, total column RSM increased to well above 65% in most areas of central South Carolina, and parts of southern and far western North Carolina.  The maximum weekly change in 0-2 m RSM (Fig. 5) exceeds 58% in central South Carolina — a value never documented in the recent years of real-time SPoRT-LIS output!  Most areas of SPoRT-LIS 0-2 m RSM exceeding ~60% correspond to areas of active minor to major river flooding across parts of southern Virginia and the Carolinas, as depicted in the USGS/NOAA river gauge network this morning (Fig. 6).

Finally, SPoRT is producing an experimental daily, real-time soil moisture percentile product based on a 33-year LIS-Noah county-by-county soil moisture climatology.  The soil moisture percentile map indicates where the current 0-2 m RSM soil moisture values lie in the present day’s historical soil moisture distribution for every county in the Continental U.S. The percentile product valid at 1200 UTC 27 September and 4 October is shown in Figure 7.  Primarily dry soil moisture values between ~5th-30th percentile are prevalent across the Carolinas on 27 September, corresponding reasonably well to the U.S. Drought Monitor moderate to severe drought areas from Figure 3. However, after the 10-20+ inches of rainfall over the past week, the 4 October soil moisture percentiles completely reversed across the region, with values > 98th percentile occurring in central South Carolina where the most severe flooding is taking place.  SPoRT plans to develop a brief training module on this percentile product prior to dissemination for display in AWIPS II at NWS WFOs, along with the current suite of SPoRT-LIS fields already available in AWIPS II.

Fig. 1. NWS River Forecast Center rainfall analysis for the week ending 1200 UTC 5 October 20125.

Fig. 1. NWS River Forecast Center rainfall analysis for the week ending 1200 UTC 5 October 2015.

Fig. 2. Comparison of NASA Integrated Multi-satellitE Retrievals for GPM (IMERG) rainfall estimate to the NWS/River Forecast Center analysis for the 24-hour period ending 1200 UTC 4 October 2015.

Fig. 2. Comparison of NASA Integrated Multi-satellitE Retrievals for GPM (IMERG) rainfall estimate to the NWS/River Forecast Center analysis for the 24-hour period ending 1200 UTC 4 October 2015.

Fig. 2. U.S. Drought Monitor weekly drought product valid 29 September 2015.

Fig. 3. U.S. Drought Monitor weekly drought product valid 29 September 2015.

Fig. 3. SPoRT-LIS total column (0-2 m) relative soil moisture valid on (left panel) 28 September, and (right panel) 5 October 2015.

Fig. 4. SPoRT-LIS total column (0-2 m) relative soil moisture valid on (left panel) 28 September, and (right panel) 5 October 2015.  Masked white areas represent water or urban pixels.

Fig. 4. One-week change in SPoRT-LIS total column relative soil moisture for the week ending 5 October 2015, as displayed in AWIPS II.

Fig. 5. One-week change in SPoRT-LIS total column relative soil moisture for the week ending 5 October 2015, as displayed in AWIPS II.  Maximum weekly change value > 58% is highlighted by the cursor position.  Masked black areas represent water or urban pixels.

Fig. 6. USGS and NWS River Forecast Center river gauge plot for the morning of 5 October 2015. River gauges experiencing flooding are indicated by the legend in the lower-right.

Fig. 6. USGS / NWS River Forecast Center river gauge plot for the morning of 5 October 2015. River gauges experiencing flooding are indicated by the legend in the lower-right.

Fig. 5. Experimental SPoRT-LIS total column relative soil moisture percentile product, valid at 1200 UTC on (left panel) 27 September, and (right panel) 4 October 2015.

Fig. 7. Experimental SPoRT-LIS total column relative soil moisture percentile product, valid at 1200 UTC on (left panel) 27 September, and (right panel) 4 October 2015.  Masked white areas represent water or urban pixels.