Multi-Radar Multi-Sensor (MRMS) Quantitative Precipitation Estimation: Initial Operating Capabilities

By Jian Zhang, K. Howard, C. Langston, Brian Kaney, Y. Qi, Lin Tang, H. Grams, Yadong Wang, S. Cocks, S. M. Martinaitis and 4 more. 2016

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Skilful precipitation nowcasting using deep generative models of radar (2021, methodology): “We refer to [2] for details on how reflectivity fields are converted to precipitation rates and how precipitation classification informs this transformation.”
MetNet: A Neural Weather Model for Precipitation Forecasting (2020, methodology): “Target precipitation rates are estimated by the Multi Radar Multi Sensor (MRMS) ground based radars as a function of the returned radar echoes (Zhang et al., 2016).”
THE GLOBAL PRECIPITATION MEASUREMENT (GPM) MISSION FOR SCIENCE AND SOCIETY. (2017, unknown): “The system creates a gridded mosaic of quantitative precipitation estimate (QPE) products on a 0.01° × 0.01° grid at a 2-min temporal resolution [see Zhang et al. (2016) for the most recent updates].”
Simulating North American mesoscale convective systems with a convection-permitting climate model (2017, background): “The overestimation can partly be attributed to deficiencies in the observational dataset since precipitation systems in the mountains are not well captured with US radars and the merging of Canadian radar data into the stage-IV dataset is error prone (Zhang et al. 2016).”