MRMS Q3 Performance during the 2013-14 Cool Season

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Tuesday, 6 January 2015: 9:30 AM
127ABC (Phoenix Convention Center - West and North Buildings)
Stephen B. Cocks, CIMMS/Univ. of Oklahoma and NOAA/NSSL, Norman, OK; and S. M. Martinaitis, Y. Qi, J. Zhang, and K. Howard
Manuscript (2.4 MB)

Abstract: Multiple Radar-Multiple Sensor (MRMS) Quantitative Precipitation Estimate (QPE) Radar Only (Q3), Mosaic Dual Pol (DPR), National Center of Environmental Prediction (NCEP) Stage II (SII) and Stage IV (SIV) product performance was evaluated during the 2013-2014 cool season for nine winter weather events east of the Rocky Mountains. The cases evaluated were events that featured a variety of precipitation types, and occurred over the central and southern Plains, the Midwest and the Southeast. Initial analysis indicated hundreds of gauges likely became clogged or stuck for part or even the entirety of the evaluated winter weather events. In fact, in regions of ice and snow, it is nearly impossible to evaluate precipitation due to the gauges inability, the majority of which are of the heated tipping bucket type, to properly perform when temperatures are below freezing. Therefore, Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) twenty-four hour accumulation data was used to evaluate product performance while hourly automated gauge data (with quality controlled measures applied) were used for spatial and time series analysis. Statistical analysis indicated all three radar-only products (e.g. no gauge adjustments or biases applied) showed an inclination to under-estimate precipitation totals, likely due to radar beam overshoot and partial beam filling errors and the predominance of the shallower precipitation systems evaluated. For the radar-only products, Q3 performed better than DPR and SII and was comparable to SIV estimate statistics. Overall, the Q3, DPR and SIV performance statistics were substantially better than those seen with the SII product which is a mosaic proxy for the legacy Precipitation Processing System (PPS). These results show the significant progress that all three precipitation estimate products (Q3, DPR and SIV) have made since the advent of PPS in the 1990s.