I was privileged to be invited as a participant in the GOES-R/MRMS portion of the 2010 Experimental Warning Program, week 6 (mid-May). We had a fairly busy week with tornadoes and other severe weather occurring in the Amarillo and Pueblo WFO’s along with the hometown Norman WFO (the Amarillo and Norman experiment days happened to feature Vortex II providing live on-site data of the tornadoes). Going into the program, I was expecting to be more interested in the GOES-R side of the experiment; however, as the week progressed, it became apparent that the MRMS system was a more promising innovation at the present time. The GOES-R tools proved to be difficult to fully analyze because their namesake satellite with its quicker routine scan intervals had yet to be launched. GOES product issues and other technical glitches aside, the week was successful and I very much enjoyed my stay. Here is a brief collection of my thoughts on each of the experimental tools:
MRMS
This system was by far the most impressive tool premiered during the week. The technology has been around for several years, but this was the first I had heard of it. The concept is simple: avoid radar-data overload and simplify warning operations by combining ancillary radars (TDWR, CASA) and neighboring WFO radars into one streamlined product. This provides an excellent way to analyze multiple radars at the same time, provided a WFO has overlapping radar coverage. Traditional cell diagnostics such as POSH (probability of severe hail) can then be constructed from this base data, along with new products that take advantage of the isothermal plotting capabilities (i.e. reflectivity plotted on an isothermal surface).
One readily apparent drawback of the MRMS system we previewed was the sheer number of different analyses available. It was nearly impossible in the time allotted to adequately test or even plot all of the fifty or so products listed for us. I settled into using about 5 of the products and was able to try about 15 over the course of the experiment. Continued experimentation (such as the EWP program) should help whittle this down to a more manageable list when MRMS products are made available to WFO’s.
I found several of the MRMS products to be very helpful in forecasting severe hail. The traditional MESH and POSH algorithms available through MRMS performed well, both in highlighting the onset of severe hail and following its track. Curiously, the bias-corrected MESH performed the worst, being off-track by an appreciable margin for many of the storms. Reflectivity was available on isothermal surfaces; the reflectivity at the 0C and -20C surfaces in particular were handy for issuing warnings for severe hail. For tornado warnings, the 0-1 km azimuthal shear and 30-minute rotation tracks both provided valuable information of low-level rotation and tornadic history. I found that the rotation track tool gave a good first guess for shaping the path of the warning polygon in situations where the track forecast was more difficult.
One drawback of relying extensively on MRMS products is the slight data latency of approximately 2 minutes. Warning decisions which require up-to-the-minute radar data would be hampered by waiting on the next available data, which might be around 2 minutes late in comparison to the WFO radar itself. I suppose in this regard, MRMS data is probably more useful in tracking and updating existing warnings than in issuing new ones. [Note: The latency is a result of the experimental nature of the AWIPS set up. An operational system, and hopefully our future EWP system, should have reduced latency. -Stumpf]
Additionally, I suspect that WFO’s which lack overlapping radar coverage probably wouldn’t experience the full benefit of the MRMS system. In particular, it seems that the low-level shear products will suffer since some of required elevation scans might not be available at greater distances from the radar. [Note: The 0-2 km AGL azimuthal shear and rotation tracks products always use data from the 0.5 degree elevation scan even if it is above the 0-2 km AGL layer. -Stumpf]
GOES Overshooting Top/Enhanced-V Algorithm & U. Wisc Convective Initiation Product
We were provided with an overshooting top algorithm which located the colder clouds of an overshooting cloud top along with the associated “enhanced-v” signature. We were also given a convective initiation product which provided four discrete values indicating the likelihood of convection over a given area. I’ve lumped the two tools together in this review because it was difficult to gauge the usefulness of either in warning operations, due to the current GOES scan interval of 15 minutes. New convection and even overshoots were often easily diagnosed by radar within the time required for a new scan. To make matters worse, the scheduled afternoon calibration and full disc scan created occasional 30 minute gaps in the imagery, further hampering the tools. Needless to say, these wide gaps in the imagery updates rendered the products difficult to evaluate. However, when the GOES-R satellite is launched, the algorithms will receive 5-minute imagery at all times of the day (up to 30-second imagery with rapid scan mode), which should greatly enhance the utility of these products. Until that time, I would say the jury is still out.
GOES-R Geostationary Lightning Mapper (GLM)
The GLM was one tool which was not actually available for the EWP, and was instead mimicked with other data to give a rough estimate of how it might behave. In the future, GLM data will give forecasters a unique look at storm activity by providing the total flash rate via a visible channel on the GOES-R satellite. This provides much more information than the current cloud-to-ground lightning data provided by Vaisala (NLDN), not to mention the benefits of public-use lightning data instead of Vaisala’s proprietary data. As previously mentioned, for the purposes of our experiment it was intended to use a pseudo-GLM (GLM output being imitated by real total lightning data) in warning operations. Unfortunately, this also required the operations to take place in locations which featured the total (3D) lightning-mapping instrumentation, which was rarely the case for our week of operations. On the one day we did have pseudo-GLM data available, the storms were sub-severe. Other weeks of operation probably worked better for analyzing the GLM, so I would defer to participants of those weeks for more information on this tool.
Darren Van Cleave (Meteorologist Intern, NWS Rapid City SD – 2010 Week 6 Evaluator)
MRMS
This system was by far the most impressive tool premiered during the week. The technology has been around for several years, but this was the first I had heard of it. The concept is simple: avoid radar-data overload and simplify warning operations by combining ancillary radars (TDWR, CASA) and neighboring WFO radars into one streamlined product. This provides an excellent way to analyze multiple radars at the same time, provided a WFO has overlapping radar coverage. Traditional cell diagnostics such as POSH (probability of severe hail) can then be constructed from this base data, along with new products that take advantage of the isothermal plotting capabilities (i.e. reflectivity plotted on an isothermal surface).
One readily apparent drawback of the MRMS system we previewed was the sheer number of different analyses available. It was nearly impossible in the time allotted to adequately test or even plot all of the fifty or so products listed for us. I settled into using about 5 of the products and was able to try about 15 over the course of the experiment. Continued experimentation (such as the EWP program) should help whittle this down to a more manageable list when MRMS products are made available to WFO’s.
I found several of the MRMS products to be very helpful in forecasting severe hail. The traditional MESH and POSH algorithms available through MRMS performed well, both in highlighting the onset of severe hail and following its track. Curiously, the bias-corrected MESH performed the worst, being off-track by an appreciable margin for many of the storms. Reflectivity was available on isothermal surfaces; the reflectivity at the 0C and -20C surfaces in particular were handy for issuing warnings for severe hail. For tornado warnings, the 0-1 km azimuthal shear and 30-minute rotation tracks both provided valuable information of low-level rotation and tornadic history. I found that the rotation track tool gave a good first guess for shaping the path of the warning polygon in situations where the track forecast was more difficult.
One drawback of relying extensively on MRMS products is the slight data latency of approximately 2 minutes. Warning decisions which require up-to-the-minute radar data would be hampered by waiting on the next available data, which might be around 2 minutes late in comparison to the WFO radar itself. I suppose in this regard, MRMS data is probably more useful in tracking and updating existing warnings than in issuing new ones.
Additionally, I suspect that WFO’s which lack overlapping radar coverage probably wouldn’t experience the full benefit of the MRMS system. In particular, it seems that the low-level shear products will suffer since some of required elevation scans might not be available at greater distances from the radar.
GOES Overshooting Top/Enhanced-V Algorithm & UWisc Convective Initiation Product
We were provided with an overshooting top algorithm which located the colder clouds of an overshooting cloud top along with the associated “enhanced-v” signature. We were also given a convective initiation product which provided four discrete values indicating the likelihood of convection over a given area. I’ve lumped the two tools together in this review because it was difficult to gauge the usefulness of either in warning operations, due to the current GOES scan interval of 15 minutes. New convection and even overshoots were often easily diagnosed by radar within the time required for a new scan. To make matters worse, the scheduled afternoon calibration and full disc scan created occasional 30 minute gaps in the imagery, further hampering the tools. Needless to say, these wide gaps in the imagery updates rendered the products difficult to evaluate. However, when the GOES-R satellite is launched, the algorithms will receive 5-minute imagery at all times of the day (up to 30-second imagery with rapid scan mode), which should greatly enhance the utility of these products. Until that time, I would say the jury is still out.
GOES Lightning Mapper
The GLM (GOES Lightning Mapper) was one tool which was not actually available for the EWP, and was instead mimicked with other data to give a rough estimate of how it might behave. In the future, GLM data will give forecasters a unique look at storm activity by providing the total flash rate via a visible channel on the GOES-R satellite. This provides much more information than the current cloud-to-ground lightning data provided by Vaisala, not to mention the benefits of public-use lightning data instead of Vaisala’s proprietary data. As previously mentioned, for the purposes of our experiment it was intended to use a pseudo-GLM (GLM output being imitated by real lightning data) in warning operations. Unfortunately, this also required the operations to take place in locations which featured the lightning-mapping instrumentation, which was rarely the case for our week of operations. On the one day we did have pseudo-GLM data available, the storms were sub-severe. Other weeks of operation probably worked better for analyzing the GLM, so I would defer to participants of those weeks for more information on this tool.