[Flooding in Houston County, Tennessee on August 21st. Image from NOAA]
[From NOAA NSSL written by Steven Martinaitis] Some of the costliest and deadliest weather events in the United States are flash floods. On average, more deaths are attributed to flash floods than to other short-term severe weather hazards, such as tornadoes, hurricanes and lightning.
Flash floods – the rapid rise of water in a normally dry area – is mainly linked to excessive precipitation leading to significant groundwater runoff and rapid rises in rivers. Forecasters rely on accurate quantitative precipitation estimates (QPEs). QPEs have entered diagnostic tools and models to help NWS forecasters predict and warn of potential flash floods, such as the flash floods that occurred in Tennessee on August 21, 2021.
Areas west of Nashville, particularly in Humphreys County, received more than 1 foot of rain in a matter of hours. This included a period where 3-4 inches of rain fell per hour over several consecutive hours. About 17.02 inches of rain was recorded at McEwen located in Humphreys County. This preliminary total eclipses the state’s record for 24-hour precipitation, which was 13.60 inches in 1982. Twenty people perished in this Tennessee flood.
[A Multi-Radar Multi-Sensor reflectivity loop covering the duration of the western Middle Tennessee flash flood event ton Aug. 21. (Gif provided by Randy Bowers via NOAA NSSL.)]
NWS forecasters can use a series of products to diagnose an ongoing weather event to determine what might be happening. Researchers from the NOAA National Severe Storms Laboratory (NSSL) and the Cooperative Institute for Mesoscale Meteorological Studies (CIMM) at the University of Oklahoma has developed two systems to aid forecasters’ analysis and warning decision making – the Multi-sensor multi-radar system (MRMS) and the System of flooded locations and simulated hydrographs (FLASH).
The MRMS system is a platform that combines various weather observations and model data to create a suite of products, including various QPE fields.
A key to the MRMS system is the quality control of radar data. Quality control algorithms remove radar artifacts from blockages, wind farms, biological dispersal (like birds and insects), and other data contaminations. The MRMS system then applies the latest scientific advances in precipitation estimation using dual polarization radar technology to provide accurate real-time precipitation data every two minutes.
NSSL and CIMMS researchers regularly analyze MRMS QPE performances, including historical events like the Tennessee flash floods. Product evaluations are performed through internal web pages which allow statistical comparisons of QPE MRMS with independent gauge observations.
Using a 24-hour scan centered around 1200 UTC (7:00 a.m. local time) to collect both daily CoCoRaHS rain gauges in addition to the automatic hourly observations of the gauges, some notable trends appear in the data. The overall analysis showed well correlated and clustered comparisons between the QPE based on the MRMS radar and the gauge observations with rather low errors. The MRMS dual polarization QPE radar showed overestimates with totals less than two inches, while a slight underestimation was observed with totals in excess of four inches. Still, the nearly equivalent values between the gauges and the MRMS in the area of the heaviest rainfall show how well the system handled the event.
[Analysis of MRMS dual-polarization QPE ending 1200 UTC on Aug. 21 (left column) and Aug. 22 (right column) with bubble plots (top row) and scatterplots with statistics (bottom row) using hourly and daily gauge observations. (Screenshot provided by NOAA NSSL.)]
The second application developed by researchers at NSSL and CIMMS to aid in flash flood forecasting is the Flood Location and Simulated Hydrograph System (FLASH). The FLASH system is the first system to generate flash flood specific hydrological modeling products at the flash flood timescale – new models are generated every ten minutes – in real time for the entire country.
The FLASH system also provides products that compare QPE values to flash flood advice – a measure of how much precipitation is needed to flood small streams – in addition to average recurrence intervals – a measure to determine the scarcity of total precipitations based on the frequency they occur. All FLASH system products use QPE dual polarization MRMS radar as input.
[Analysis of the following FLASH products at 1300 UTC 21 August 2021: maximum QPE-to-FFG ratio (left), maximum QPE average recurrence interval (center), and CREST maximum unit streamflow (right). (Screenshot provided bty NOAA NSSL.)]
At the height of the precipitation over Humphreys County, Tennessee, the QPE comparison products were at the high end of the plotted scales. Accumulated precipitation was at least four times greater than that of the NWS flash floods for the region, and the mean recurrence interval of the rain was beyond the scale plotted in the system (at least 200 years – about 0 , 5% chance of occurring per year).
The product that best reflects the flash flood potential and its possible severity is the product of the maximum unit flow of the Hydrological model of coupled routing and excess storage (CREST). Maximum flow unit values - the amount of runoff normalized by its basin area – have been shown to capture the spatial coverage of flash floods and provide context for its potential severity.
Projected unit flow values based on MRMS precipitation rates during the Tennessee flash flood on August 21, 2021, showed three key characteristics:
- The speed with which the flash flood threat has escalated.
- How extreme values indicated a potentially catastrophic event.
- How the model routed water to show impacts on local rivers even after the precipitation ended.
[CREST maximum unit streamflow from the FLASH system from 0600–2100 UTC 21 August 2021. (Graphic provided via NOAA NSSL.)]
Researchers at NSSL and CIMMS are continuously working to improve the performance of MRMS and FLASH systems to improve rainfall estimates and flash flood forecasts. Machine learning and artificial intelligence efforts are paving the way for increased performance in areas where radars struggle to accurately capture precipitation. Probabilistic hydrological modeling with the use of rainfall forecasting with the FLASH system looks to the future of flash flood warning in the FACETS (Prediction of a continuum of environmental threats).
Edited for WeatherNation by Mace Michaels