Advanced Weather Forecasting System Celebrates Over a Decade of Progress

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The Core of MRMS: Integration and Development

The Multi-Radar Multi-Sensor (MRMS) system, a cornerstone for forecasters since its inception in 2014, integrates data from radar, satellites, rain gauges, lightning networks, and predictive weather models. Developed through a partnership between NOAA’s Cooperative Institute at the University of Oklahoma and the NOAA National Severe Storms Laboratory (NSSL), MRMS is continuously enhanced with new scientific breakthroughs. Each update undergoes rigorous testing to ensure top-tier data quality for forecasters. Currently, the system supports 135 distinct tools and products used by the NWS.

Introducing MRMS v12.3: Key Enhancements

The newly deployed MRMS v12.3 introduces enhancements to radar processing and improves algorithms for severe weather and precipitation forecasting, according to Steven Martinaitis, a lead researcher at OU’s Cooperative Institute for Severe and High-Impact Weather Research and Operations (CIWRO). As this version goes live, CIWRO scientists are already analyzing its performance to identify areas for further improvement in future updates.

This update includes several technical advancements, such as support for the National Weather Service’s radar Volume Coverage Pattern (VCP) 34, an upgrade to the ProbSevere system from version 2 to version 3 for more reliable severe storm probabilities, and integration of the Multi-PRF Dealiasing Algorithm (MPDA) to enhance rotation track products. Additional improvements focus on lightning probability generation for better efficiency, quantitative precipitation estimates (QPE) with refined melting layer detection, and quality control routines to handle ground clutter, beam blockage, and wind farm interference more effectively. These changes aim to boost the overall accuracy and timeliness of forecasts, particularly in operational settings.

Advancing Flash Flood Prediction – Weather Forcasting

A key focus for CIWRO researchers is advancing the prediction of flash flooding, a critical issue given recent events across the U.S. this summer.

“The MRMS system, paired with its companion Flooded Locations and Simulated Hydrographs (FLASH) system, delivers vital data on rainfall estimates, precipitation analysis, and flash flood forecasting. These tools have been indispensable for our NWS partners during critical moments,” Martinaitis said. “Skilled forecasters combine MRMS and FLASH data with their expertise to make confident warning decisions, but we’re always assessing performance to pinpoint opportunities for improvement.”

Integration with Emerging Technologies

Recent efforts have explored integrating MRMS and FLASH with the Warn on Forecast System (WoFS), a collaborative project between CIWRO and NSSL. WoFS leverages high-resolution ensemble forecasts, incorporating MRMS data to enhance prediction accuracy. Early tests combining these systems have shown promise for issuing earlier flash flood warnings.

“Our experiments with WoFS, MRMS, and FLASH have demonstrated potential for predicting flash flood locations more accurately,” Martinaitis noted. “In some cases, we’ve achieved an additional 10 to 30 minutes of warning lead time, which can make a significant difference in protecting lives and property.”

Historical Evolution of MRMS and FLASH

The MRMS system originated in 1998 through a project funded by the U.S. Weather Research Program and Arizona’s Salt River Project, aimed at improving radar data integration. Over the years, it evolved with advancements in data processing, dual-polarization radar, and expanded coverage to regions like Alaska, Hawaii, the Caribbean, and Guam.

Concurrently, the FLASH system was developed to integrate MRMS precipitation data into national hydrologic models for flash flood prediction. FLASH began testing in 2012 and became operational at the NWS in 2016.

Future Directions and Research

Looking forward, Martinaitis emphasized plans to incorporate higher-resolution data, expand probabilistic forecasting, and integrate additional predictive inputs to enhance flash flood forecasting. Field research into weather phenomena is also expected to yield new insights for refining MRMS, FLASH, and WoFS.

“Insights from our field studies on precipitation and flash flooding directly inform improvements to these systems. We’re constantly testing new approaches to advance the science behind MRMS, FLASH, and WoFS,” he said.

With ongoing evaluations and potential for even greater lead times in warnings, the integration of these systems could further revolutionize severe weather response strategies, potentially saving more lives during events like heavy rainfall and flash floods.

About CIWRO

CIWRO, the largest research entity at the University of Oklahoma, accounts for roughly 25% of the National Weather Center’s workforce and is primarily funded by NOAA.