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.

Denver Area Snowfall Event Feedback

David Barjenbruch, a forecaster at the Denver/Boulder WFO working with SPoRT and NESDIS to evaluate the NESDIS Snowfall Rate product this winter, provided a nice case study for consideration.  He writes:

We received more snow across the Front Range of Colorado on Wednesday, January 21, and just wanted to attach a few comparisons of SFR, radar, obs, and METARS.  At 17Z, the SFR unfortunately missed the moderate snow across the Denver metro area (KDEN…1mm water in last hour…and KBJC 1/2 mile visibility in moderate snow, and 1/4 mile at KAPA…0.8mm water in last hour). Area of main concern is highlighted in pink, while at the same time it also overestimated snow toward the east toward ITR in eastern Colorado.

Comparison between radar and SFR product at 17Z on 21 Jan 2015

Comparison between radar (left) and SFR Product (right) at 17Z on 21 Jan 2015.  Circled area denotes region where SFR missed accumulating precipitation in the Front Range.  SFR overestimates snow in eastern CO.

 

Comparison between radar and SFR at 20Z on 21 Jan 2015.

Comparison between radar (left) and SFR Product (right) at 20Z on 21 Jan 2015.  SFR captures some of the snow in southern CO but continues to overestimate snowfall in parts of eastern CO.

After a fairly widespread precipitation event Wednesday morning, the snow turned more convective in the afternoon.  Checking the 2320Z radar, we had an intense convective cell which moved southwest across the western sections of the Denver metro area (highlighted in pink again).  This particular cluster of convection produced anywhere from 1.5 to 3″ of snow (2-5.5mm water) in an hour or less.

Comparison between radar and SFR Product at 2320Z on 21 Jan 2015.

Comparison between radar and SFR Product at 2320Z on 21 Jan 2015.  Circled area denotes convective snowfall that was not captured by the SFR.

An Evaluation of the SFR Product during a mid-December Winter Storm for Northern New Mexico

The Albuquerque NWS recently began receiving an updated NESDIS snowfall rate (SFR) product from NASA SPoRT. We were anxious to see how the updated product performed during our most recent winter storm. A fast moving upper level trough and associated Pacific Front blasted into western New Mexico on the afternoon of Saturday, December 13. The upper low deepened and closed off over New Mexico with wrap around snow impacting northeast New Mexico through mid-day Sunday, December 14.  Ahead of the system, temperatures were very warm with Albuquerque reporting a high of 61 and Santa Fe reporting a high of 57 on Saturday.  The RGB snow-cloud product from 2045Z on Sunday depicts snow cover following the event. Four areas in the state were impacted – the western high terrain, the San Juan and Sangre de Cristo Mountains (mainly west slopes) in north central New Mexico, and extreme northeastern corner of New Mexico. Four yellow ovals mark areas to be discussed in this blog entry. Strong westerly, downslope flow on the backside of this storm system resulted in the snow-free region along the eastern slopes between Taos and Raton.
SnowCloud121414_2045Z

In the loop below, the 0.5 reflectivity mosaic and surface observations show the surface front moving into western New Mexico (left most oval in the snow-cloud product) during the period from 1942Z to 2318Z. In the first image, the winds have shifted to the northwest in Farmington (FMN) and rain is reported as temperatures are too warm to support snow. Note that throughout the loop the Farmington area, especially west and north of the site, there are no radar returns. The Four Corners area has poor to no radar coverage and it is an area where we hope the SFR product will help us. Snow was reported at Gallup (GUP) by 2030Z.

0.5 Reflectivity 1942Z to 2318Z

The SFR product was limited during this initial period, with only one swath covering New Mexico at 2034Z (shown below). This image (obtained from the SPoRT product page) shows that snow is detected in northeast Utah and northwest Colorado, but not in northwest New Mexico.  The Gallup area ended up with about one inch of snow while higher terrain south of Gallup reported two to three inches. While only rain was reported at the Farmington ASOS, the snow-cloud product shows some snow just to the east of Farmington where reports of one-half to an inch of snow was reported.

SPoRT_SFR_121314_2034Z

The next SFR product with coverage over New Mexico had a timestamp of 0338Z (14 December 2014), and is compared to the composite reflectivity image of 0336Z in the image below. Reflectivity is strongest just west and northwest of the Albuquerque ASOS (ABQ), which is reporting rain. The cold front however was moving quickly from west to east toward the ABQ metro area. The strong reflectivity returns to the northwest of Albuqurque are actually bright banding as rain began changing over to snow. The dual polarization hydrometeor classification algorithm showed the rain/snow line shifting quickly eastward. Fifteen minutes prior to this image, rain transition to snow was reported in Rio Rancho, just northwest of Albuquerque. The higher terrain just east of Albuquerque, the Sandia and Manzano Mountains, did receive snow accumulations of two to four inches and the SFR product highlights that area with light rates (blue) of about .02 inches/hour. The Santa Fe area (SAF) is not reporting snow at this time, but is highlighted with the max values of SFR, though snow reports in the Santa Fe area were generally less than 2 inches.  Recall that afternoon temperature were quite warm, making it difficult for snow to accumulate. The SFR product also depicts rates up to .05 inches/hour over the Sangre de Cristo mountains north and east of Santa Fe, where accumulations of 4 to 8 inches were reported. Interestingly, the SFR product is estimating precipitation around Santa Fe when the radar reflectivity pattern and observation do not indicate rain or snow. A portion of this area to the immediate northeast and east of ABQ is beam-blocked by the Sandia Mountains (yellow oval southwest of SAF).

mosaic_Comp_Ref_20141214_0336_SFR_0338Z

A similar comparison is shown for 13 hours later, or around 1655Z on December 15. (Another image was available around 08Z, but is not discussed in the post.)  Note that the SFR product depicts accumulating snow, albeit light, from eastern Taos through all but extreme southern Colfax County. Two stations (KAXX and KRTN) are reporting snow, but radar composite reflectivities do not extend over either location. Snow did accumulate at KAXX, but not at Raton (KRTN) where temperatures hovered right above freezing.

mosaic_Comp_Ref_20141214_1642_SFR_1645Z

Snow that is evident in extreme northeast New Mexico occurred after mainly 16Z and was associated with persistent wrap around precipitation (a SFR product was not available). The SFR product was not used in near real time for this event but was re-examined only a short time thereafter. However, the product did validate that we will indeed be able to complement radar void coverage areas in an operational forecast environment using polar-orbiting satellite imagery. This example will also serve to highlight potential product applications, advantages, and disadvantages for forecaster training prior to the upcoming NESDIS evaluation period.