A Statistical Analysis of Radar and MRMS QPE in the Northern Plains and Mid-Atlantic

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Authors

Steen, Matthew

Date

2023-05

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en

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ABSTRACT A Statistical Analysis of Radar and MRMS QPE in the Northern Plains and Mid-Atlantic by Matthew C. Steen Plymouth State University, May, 2023 Over the last 40 years weather radar has provided an immense amount of data across the United States. Radar precipitation estimates provide a much higher spatial and temporal density of observations than ground-based measurements. In recent years, dual- polarization capabilities introduced to NEXRAD WSR-88Ds provided improvements to precipitation estimations allowing for more accurate forecasts and warnings. Also, the Multi-Radar/Multi-Sensor System (MRMS) has developed a set of hydrometeorological based algorithms which take in data from radars, satellites, surface and upper air observations, models, and lightning detection systems to create a wide array of products that assist in decision-making and provide improved weather forecasting tools. The MRMS and Dual-pol radar Quantitative Precipitation Estimations (QPEs) are being used more by analysts in place of the previous radar precipitation estimation algorithm, the Precipitation Processing System (PPS). The goal of this research is to compare the Sioux Falls, SD (KFSD) and Dover, DE (KDOX) WSR-88Ds dual-polarized radar rainfall estimates and MRMS radar-only rainfall product estimates to rain gauge measurements for precipitation events in these regions. KFSD was selected because there have been few radar QPE studies in the Northern Plains. KDOX was selected for similar reasons (few studies in the mid-Atlantic) along with providing a perspective from a different climatic xi regime within the United States. Hourly rain-gauge precipitation estimates within 100 km of KFSD for events with at least one hour of observed rainfall greater than or equal to five millimeters were analyzed. These observed values were compared with high and low resolution dual-polarization QPE and MRMS radar-only estimates. Results demonstrate that the MRMS radar-only product produced better precipitation estimates than both high and low resolution dual-polarized estimates at both KFSD and KDOX. The mean absolute error (MAE) for MRMS was lower than both radar products at KFSD while the high-resolution radar product produced a similar MAE at KDOX. The differences in MAE between the low resolution dual-pol QPE and the MRMS and the high resolution dual-pol QPEs were determined to be statistically significant at both stations. The average bias of the MRMS was lower than both radar products for both radars, with a larger difference between the MRMS and low resolution dual-pol QPE than high resolution estimates. Like MAE, the difference between the low resolution dual-pol QPE and the MRMS and the high resolution dual-pol QPEs were determined to be statistically significant at both stations. Based on the results of this study, forecasters may be more inclined to favor the estimations of MRMS-based products for the forecasting of rainfall and issuing of rainfall related watches and warnings.

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