Both examples provide information about the texture of the clouds; however, there is greater contrast with the colder cloud tops in the raw imagery when compared to the dry land convection.
-Lost Met
Tuesday, June 20, 2017
GOES-16 ABI Raw Imagery vs. RGB
The example below compares the GOES-16 Raw Imagery vs. Day Land Convection RGB:
In the example, the GOES-16 raw imagery is visible imagery with semi-transparent IR overlay. This combination of raw imagery provides similar and even more information than the dry land convection RGB.
Both examples provide information about the texture of the clouds; however, there is greater contrast with the colder cloud tops in the raw imagery when compared to the dry land convection.
-Lost Met
Both examples provide information about the texture of the clouds; however, there is greater contrast with the colder cloud tops in the raw imagery when compared to the dry land convection.
-Lost Met
CG lead time
CG lead time with GLM:
Looked at two cases of initial convective activity of the day to see if GLM could provide some lead-time to a CG strike. In this case the GLM Event bump (orange) appear at the same time as a CG strike in both NLDN and Earth Networks. Zero lead-time in these cases. --Tahoe
Looked at two cases of initial convective activity of the day to see if GLM could provide some lead-time to a CG strike. In this case the GLM Event bump (orange) appear at the same time as a CG strike in both NLDN and Earth Networks. Zero lead-time in these cases. --Tahoe
Shifting Severe Threat Focus
Main Points:
After inspecting GOES16 derived stability plots, have not seen any changes to the environment in the southern CWA ahead of the line of storms. Basically low instability and lack of Cu field development in VIS. MSAS dewpoint depression shows 30+ degrees of dew point depression, so this piece of information was used to continue to monitor threat for outflows. Think usefulness in lightning and Prob-severe is of limited use at this stage since not looking at renewed deep convection due to low instability and overall low lightning amounts due to the lack of deep convection as well. --Tahoe.
- GOES-16 derived stability: No changes to southern CWA, still not expecting deep convective growth.
- Main focus is dry sub-cloud layers and convective outflow threat. Surface obs/msas were main data used to have confidence in outflow threat
After inspecting GOES16 derived stability plots, have not seen any changes to the environment in the southern CWA ahead of the line of storms. Basically low instability and lack of Cu field development in VIS. MSAS dewpoint depression shows 30+ degrees of dew point depression, so this piece of information was used to continue to monitor threat for outflows. Think usefulness in lightning and Prob-severe is of limited use at this stage since not looking at renewed deep convection due to low instability and overall low lightning amounts due to the lack of deep convection as well. --Tahoe.
KDDC: SVR issuance based on Prob Severe
At 4:32pm, right when the warning was issued, a report of 2.5" inch all was reported.
These storms today in the NW DDC area have been producing large hail, and the Prob Hail model within Prob Severe has been very consistent with what has been observed, and giving confidence in issuance of other experimental severe thunderstorm warnings in the region.
Testbed observations yields ProbSevere training point
The post about a severe wind gust in the Chicago WFO (http://goesrhwt.blogspot.com/2017/06/prob-severe-severe-outflow-wind-report.html) offers insight on a subtle, yet important point that should be communicated to ProbSevere users in the training module. In this example, a storm produced strong outflow winds that raised away from the reflectivity core far enough such that it no longer was encompassed by the ProbSevere object. As a result, the ProbSevere (ProbWind) probability was 0%. For storms were outflow is expected to race away from the reflectivity core, users should be aware the ProbWind model may underestimate (possibly by a large amount) the probability of severe winds. Additionally, this is another example of where maximum velocity magnitude could be a very useful observation for the automated prediction/detection of severe winds.
-Sieglaff
-Sieglaff
Severe hail from storm in Dodge City WFO
A severe thunderstorm had developed over the northwestern Dodge City, Kansas CWA Tuesday afternoon. The NOAA/CIMSS ProbSevere values cycled between 45 and roughly 70% from 1925 until 1952 UTC; then radar observed reflectivity core rapidly increased, causing the ProbSevere values to correspondingly jump from 71% at 1952 UTC to 94% at 1956 UTC. The jump in ProbSevere values as well as other features on radar (very strong storm top divergence and 3-body scatter spike (see post: http://goesrhwt.blogspot.com/2017/06/probsevere-compared-to-classic-radar.html)) warranted the DDC team to issue an experimental severe thunderstorm warning. Shortly after the warning, 2.00" hail reports were received.
 |
| Figure 1. KDDC 0.5 degree reflectivity and ProbSevere contours valid 1926 - 1958 UTC 20 June 2017 for select times. |
Another valuable discussion between myself and the forecaster was had where we examined the storm top divergence with this storm. Strong storm-top divergence is something that often precedes a rapid intensification of a thunderstorm (and often severe reports). Storm-top divergence is something a forecaster can quickly identify by analyzing all-tilts of base velocity data, but an automated storm-top divergence field is unavailable from the MRMS suite of products. Such a field being made available in the MRMS suite could would be valuable for evaluation and possible inclusion into the ProbSevere model.
-Sieglaff
Prob-Severe: Severe outflow wind report.
Prob-Severe: Severe outflow wind report.
Main Points:
At 1957z (below) the time of the spotter report, the radial velocity displayed an outbound velocity of about 60 knots, while the max was still displaced to the south from the ProbSevere boundary which still showed 0% probs. --Tahoe
Main Points:
- Spotter reported outflow wind of 67 mph with a cell 1957z.
- ProbSevere showed probabilities of 0% throughout its track.
- GLM data (not shown) had an increase in activity but nothing that seemed significant compared to earlier in the day. Nothing eye-catching that is. Also, this storm did not produce subsequent CG strikes.
- Radar radial velocity was the only key piece of information that would allow you to issue a warning on this cell.
At 1957z (below) the time of the spotter report, the radial velocity displayed an outbound velocity of about 60 knots, while the max was still displaced to the south from the ProbSevere boundary which still showed 0% probs. --Tahoe
Visible Texuture + IR Cloud Top Temps
Another benefit of the GOES-16 "sandwich" procedure (which is visible with a semi-transparent IR overlay) is the ability to see texture associated with the visible imagery while seeing the cloud top temperature.
In this example, the cooling cloud tops are seen by the brighter red in conjunction with the overshooting top in the visible imagery:
-Lost Met
In this example, the cooling cloud tops are seen by the brighter red in conjunction with the overshooting top in the visible imagery:
ProbSevere Compared to Classic Radar Integration Techniques
It might be beneficial if ProbSevere included some form of storm-top divergence in its algorithm.
For example, on this 1946 UTC scan, there was ~150 knots of storm-top divergence at ~40,000 ft AGL:
ProbSevere did show intensification with a gradual increase in percentages (47% to 94%) between 1946 and 1956 UTC:
-Lost Met
NUCAPS Gridded Elevated Lapse Rates...
Hello from the Hazardous Weather Testbed in Norman, OK!
So, we were taking a closer look at the NUCAPS (NOAA Unique Combined Atmospheric Processing System) data, both in the sounding and in the gridded format for severe weather applications. Today, we are specifically focusing on the potential for deep/severe convection in northern Illinois and western Kansas...and surrounding areas. It's important to note here that NUCAPS soundings are satellite derived (Soumi NPP, Metop-A, Metop-B and JPSS (future)) and independent of model data. The NUCAPS soundings have been utilized in the HWT now for three years. The NUCAPS gridded data meanwhile are a relative new-comer to the HWT, having been implemented briefly at the end of last year's HWT...but are more of a formal product being evaluated this year. The efforts to get the gridded NUCAPS data into AWIPS were led by the SPoRT group at NASA MSFC and have played a role in weather forecasting in Alaska, especially for the Anchorage CWSU. Now, we are taking a closer look at the data for potential severe weather applications and trying to think of proper data displays and visualizations. One thought that came to mind was looking at lapse rates of the NUCAPS vs various model output. This image shows 700-500 mb lapse rates for the NUCAPS gridded data along with GOES-16 0.64 um imagery (upper left), HRRR (upper right), GFS20 (lower left) and NAM 40 (lower right).
Notice that the 700-500 mb lapse rates from the NUCAPS data are very similar in pattern to the various model data shown above. While specific values at various locations differ by relatively small percentages, patterns and gradients are overall fairly similar. However, the NUCAPS data suggests perhaps slightly steeper lapse rates (C/km) over portions of the Great Lakes than the suite of model data. In the environment in that area today, these levels correspond to temperature values roughly in the 0C to -20C temperature range...per NUCAPS soundings. So, we would expect to see perhaps slightly more robust convective development in this region today, than model data alone might imply.
Next, we're going to take a closer look at some of the NUCAPS soundings in context of both the gridded data and other analysis data sets.
-Kris W and Nadia S
So, we were taking a closer look at the NUCAPS (NOAA Unique Combined Atmospheric Processing System) data, both in the sounding and in the gridded format for severe weather applications. Today, we are specifically focusing on the potential for deep/severe convection in northern Illinois and western Kansas...and surrounding areas. It's important to note here that NUCAPS soundings are satellite derived (Soumi NPP, Metop-A, Metop-B and JPSS (future)) and independent of model data. The NUCAPS soundings have been utilized in the HWT now for three years. The NUCAPS gridded data meanwhile are a relative new-comer to the HWT, having been implemented briefly at the end of last year's HWT...but are more of a formal product being evaluated this year. The efforts to get the gridded NUCAPS data into AWIPS were led by the SPoRT group at NASA MSFC and have played a role in weather forecasting in Alaska, especially for the Anchorage CWSU. Now, we are taking a closer look at the data for potential severe weather applications and trying to think of proper data displays and visualizations. One thought that came to mind was looking at lapse rates of the NUCAPS vs various model output. This image shows 700-500 mb lapse rates for the NUCAPS gridded data along with GOES-16 0.64 um imagery (upper left), HRRR (upper right), GFS20 (lower left) and NAM 40 (lower right).
Notice that the 700-500 mb lapse rates from the NUCAPS data are very similar in pattern to the various model data shown above. While specific values at various locations differ by relatively small percentages, patterns and gradients are overall fairly similar. However, the NUCAPS data suggests perhaps slightly steeper lapse rates (C/km) over portions of the Great Lakes than the suite of model data. In the environment in that area today, these levels correspond to temperature values roughly in the 0C to -20C temperature range...per NUCAPS soundings. So, we would expect to see perhaps slightly more robust convective development in this region today, than model data alone might imply.
Next, we're going to take a closer look at some of the NUCAPS soundings in context of both the gridded data and other analysis data sets.
-Kris W and Nadia S
Subscribe to:
Posts (Atom)