The NOAA/CIMSS ProbSevere Model is a statistical model that combines, NWP environmental conditions, satellite tracking and growth rates, and radar tracking and storm intensity to predict a developing storm will first produce severe weather in the near future (0-60 min). The NOAA/CIMSS ProbSevere model is being demonstrated to National Weather Service forecasters at 2014 Big Spring Experiment at the Hazardous Weather Testbed. NWS forecasters are encouraged to evaluate the ProbSevere model output as a means to increase confidence and lead-time in issuing initial severe warnings on developing storms. Today the weather is rather quiet across much of the country. A strong storm developed in southwestern Virgina and the evolution of the ProbSevere model performance on this storm is highlighted below. Of note, this storm achieves high probabilities and as of 2030 UTC, has been the only storm over CONUS today to achieve appreciable ProbSevere values.
Figure 1. The NOAA/CIMSS ProbSevere at 1950 UTC 5 May 2014–the first time the model produced probabilities above 50%. Radar data is not yet seen in this display as a domain switch was in-progress within HWT.
The NWS office in Blacksburg, VA issued a severe thunderstorm warning at 1952 UTC. The following two figures show the continued increase of NOAA/CIMSS ProbSevere probabilities.
Figure 2. NOAA/CIMSS ProbSevere at 1954 UTC 5 May 2014–probabilities are now 80%+.
Figure 3. NOAA/CIMSS ProbSevere at 2006 UTC 5 May 2014 now exceeds 90%.
This storm went on to produce severe hail (1.00″) at 2009 UTC–19 minutes after the initial ProbSevere > 50%. While this storm was not located in the a CWA of focus for this afternoon, forecasters are using this storm to gain confidence in the ProbSevere model and ask questions about some of the technical details of the model.
On Sunday April 27th, 2014, a moderate risk for severe thunderstorms was forecast by the SPC across eastern Kansas and Oklahoma, most of Missouri and Arkansas, as well as portions of Texas, Louisiana, Mississippi, and Tennessee. Before 12Z on that morning, convection developed along the dryline/Pacific cold front across central Kansas and Oklahoma. These thunderstorms became elevated as they moved east northeast towards Kansas City and western Missouri due to mid to lower tropospheric warm air advection. The early morning convection added uncertainty to the forecast as there was a question whether the atmosphere would recover and destabilize for convective initiation (CI) before the dryline and Pacific cold front moved through across eastern KS and western MO behind the morning convection.
Visible satellite image from GOES-13, METARs, NWS Convective Watches and Warnings, and manually analized surface features valid 1815 UTC 27 April 2014.
In the image above at 1815 UTC, although there was clearing right ahead of the dryline, extensive cloud cover and cool temperatures were present in the wake of the morning convection across eastern Kansas and western Missouri. Ninety minutes later, at 1945 UTC, temperatures started to rebound into the lower to mid 70s across southeastern Kansas and a cumulus field developed ahead of the dryline across eastern Oklahoma.
Visible satellite image from GOES-13, METARs, NWS Convective Watches and Warnings, and manually analized surface features valid 1945 UTC 27 April 2014.
One of the GOES-R future capability products, Probability of Convective Initiation, provides probabilistic 0-1 h forecasts of cloud objects achieving convective initiation (35 dBZ or > radar echo). Inputs into the algorithm are convective cloud properties from either GOES-13/GOES-15 and 20 Rapid Refresh model output fields. This fused product is excellent at providing guidance to the mesoanalyst or warning forecaster on which portion of a cumulus field will develop into convection. In the image below at 1945 UTC, there were low probabilities of CI within the newly developed cumulus field across northeastern Oklahoma.
Visible satellite image from GOES-13, GOES-R Probability of Convective Initiation [%], and NWS COnvective Watches and Warnings valid 1945 UTC 27 April 2014.
At 2045 UTC, 60 minutes later, the cumulus field developed northward into southeastern Kansas and probabilities increased to 60% within that cumulus field. This indicates a higher likelihood of CI and is starting to provide confidence to the forecaster that the atmosphere is destabilizing enough for the potential of CI.
Visible satellite image from GOES-13, GOES-R Probability of Convective Initiation [%], and NWS COnvective Watches and Warnings valid 2045 UTC 27 April 2014.
Another GOES-R future capability is the Convective Cloud-Top Cooling (CTC) product. This algorithm uses GOES-13/GOES-15 imager data and cloud phase information to provide situational awareness on which convective cloud objects are quickly growing vertically (i.e., a proxy for initial updraft strength). A stronger CTC rate is directly correlated with updraft strength and larger hail when compared to the WSR-88D maximum expected hail size algorithm. At 2125 UTC, 40 minutes after the elevated CI probabilities, two thunderstorms were developing across southeastern Kansas and northeastern Oklahoma. This is evident by the strong CTC detections in those areas.
Visible satellite image from GOES-13, GOES-R Convective Cloud-Top Cooling [K per 15 minutes], and NWS COnvective Watches and Warnings valid 2045 UTC 27 April 2014.
Fifteen minutes later, the first severe thunderstorm warning was issued on the thunderstorm with the northern CTC detection in southeastern Kansas. These two thunderstorms eventually developed into the supercells that produced the two EF2 tornadoes that affected Baxter Springs, KS (southern CTC detection) and Bates/Linn County, KS (northern CTC detection). Although the two products shown are GOES-R future capabilities, they are used today with GOES-13/GOES-15 data to demonstrate the algorithms and provide observational information of the convective environment that is not currently available with other datasets. When these two products are used together with observations forecasters are already comfortable with, situational awareness of the convective environment is elevated and more accurate short-term forecasts of convection may possibly be provided to partners.
~ Chad Gravelle, NWS Operations Proving Ground Satellite Liaison
Today marks the first day of the 2014 Hazardous Weather Testbed (HWT) Spring Experiment, which will run through the first week in June (Experimental Warning Program (EWP) Big Spring Experiment will be off for Memorial Day week). The HWT provides the GOES-R Proving Ground with an opportunity to demonstrate baseline and future capabilities products associated with the next generation GOES-R geostationary satellite system that have the potential to improve short-range hazardous weather nowcasting and forecasting. The availability of GOES-R products will demonstrate, pre-launch, a portion of the full observing capability of the GOES-R system, subject to the constraints of existing data sources to emulate the satellite sensors.
GOES-R products being evaluated this year include: Synthetic Satellite Imagery, NearCast System, Convective Initiation, Probability of Severe Model, Overshooting Top Detection, PGLM Total Lightning products, Tracking Tool and Lightning Jump Algorithm. These products will be demonstrated by National Weather Service forecasters and broadcast meteorologists within a simulated warning operations environment using a real-time AWIPS-II framework within the HWT EWP. When and if appropriate and if time permits, several of these products may be demonstrated informally in the HWT Experimental Forecast Program (EFP) during the mid-afternoon when the EFP severe storm forecasts are being updated.
As in previous years, participants, in addition to myself and visiting scientists, will make frequent posts to the following blog regarding the days activities, product performance, product feedback, etc.: http://www.goesrhwt.blogspot.com/