A research framework to bridge the global precipitation measurement GPM level II and level III using multi-radar multi-sensor mrms objectives: the overarching goal of this research project is to…

This federal contract award, valued at $203,138.33, was granted by the Shared Services Center (an alternate name for a federal agency) to the University of Oklahoma (OU) to conduct research that aims to improve algorithms for the National Aeronautics and Space Administration's (NASA) Global Precipitation Measurement (GPM) mission. The overarching goal is to leverage multi-radar, multi-sensor data from the Multi-Radar/Multi-Sensor (MRMS) system to enhance the Level 2 and Level 3 GPM data products. Key tasks include in-depth comparisons between space-based and ground-based precipitation measurements, error characterization, and propagation of errors from Level 2 to Level 3 products. This research directly supports the agency's goal of validating and enhancing precipitation algorithms. The contract has no set-aside designation and runs through July 2020.

A research framework to bridge the global precipitation measurement GPM level II and level III using multi-radar multi-sensor mrms objectives: the overarching goal of this research project is to leverage multi-radar multi-sensor mrms quantitative precipitation estimation applications to provide a useful research framework for bridging CONUS-wide ground validation and trmm GPM algorithm enhancement. The research focus is on microphysics and precipitation error characterization by taking full advantage of the mrms multi-scale precipitation information merged with GPM validation network and ground validation GV field study datasets e.g., working from point-based microphysical profiles and rainfall measurements, site-based multi-frequency research radars, to CONUS-wide mosaicked radar network. Ultimately the research seeks to improve, in a self-consistent fashion, GPM retrieval algorithms for both level 2 e.g., retrieval algorithms and level 3 e.g., imerg products. Tasks are: 1. Perform an in-depth comparison analysis between space radars trmm-PR GPM-DPR, combined GCI and mrms under various regimes of performance. Complementary insight will be extracted by conditioning the analysis by respective mrms-based and gpmbased algorithm assumptions and methods. We will check consistency regarding precipitation detectability, analyze the impact of mallscale precipitation variability and evaluate the reflectivity attenuation correction algorithms applied to space radar data. Comparison of 3-d precipitation structures, microphysical properties hydrometeor types e.g. hail, snow-, particle size distribution, and surface precipitation between ground- and space-based retrievals will improve understanding and quantification of precipitation processes. 2. Perform an in-depth comparison analysis between space-borne radiometers TMI, GMI and other constellation sensors and mrms products. Aspects like precipitation detection, characterization and quantification will be addressed. The results of this error analysis will be compared to an equivalent analysis using the PR DPR GCI as a reference in the perspective of task 1. We will focus on the land surface state, which is critical for the new passive microwave algorithm for GPM. Future error analysis of GPM core and constellation satellites algorithms will target regional precipitation biases over different surface conditions e.g. soil moisture, vegetation, surface precipitation type and phase e.g. snow. 3. Bridge comparison analyses across the level-2 GPM constellation and propagate to level-3 precipitation products. Because satellite coincidences within a few minutes are rare, as a consistent reference mrms is the ideal tool to bridge in-depth characterization across constellation sensors from the GPM core to the constellation, directly assessing the influence of surface types, precipitation properties and sampling properties among sensors. We will break down the error components from the individual level-2 products and propagate these along through imerg fully understanding the errors across scales, for a more realistic, dynamic and end-to-end error quantification. Major differences across scales conditioned on several physical factors contributing to erroneous retrievals will be quantified to properly target regimes and or relevant precipitation physics required for analysis. Relevance and broader impact: this proposal directly addresses the research category 2.1: algorithm product validation and enhancement. IT will leverage the accommodation and integration of mrms dual-POL and GPM products, integrating various GV activities from field campaigns to national networks. The work is a larger multi-team effort designed to further cement the links between space and ground-based precipitation remote sensing so that synergistic physical validation and development of multi-sensor algorithms can proceed. The research represents components of a scientific framework for implementing meaning